Team-Based Electronic Communication in the Care of Patients with Complex Conditions

Home , Friendica, Research participant

Team-based electronic communication in the care of patients with complex conditions

Rishi Teja Voruganti

A thesis submitted in conformity with the requirements

for the degree of Doctor of Philosophy

Institute of Health Policy, Management and Evaluation

University of Toronto

Team-based electronic communication in the care of patients with complex conditions

Rishi Teja Voruganti

Doctor of Philosophy

Institute of Health Policy, Management and Evaluation

University of Toronto

2017

ABSTRACT

Background: The management of patients with complex care needs often involves specialized care from multiple providers in different settings. Care coordination is often inadequate, leading to poor continuity of care. Digital health tools can connect patients and their team of providers to facilitate communication across institutions, disciplines and health events. This dissertation examines digital health tools for patient-provider team-based communication, their feasibility in practice and role in improving continuity of care.

Methods: Three studies were conducted. The first study was a scoping review of web-based tools for text-based communication between patients and providers, including those for team- based communication. The second study was a cluster randomized controlled feasibility trial evaluating the feasibility of implementation and preliminary effectiveness of a web-based tool for asynchronous, patient-provider team-based communication on continuity of care relative to usual care. Finally, a qualitative descriptive study was conducted with participants from the trial to understand their perceptions on the value of the tool.

Results: The first study identified tools for a variety of chronic conditions, the majority of which targeted diabetes, chronic respiratory diseases and mental illness for purposes of providing symptom updates or to facilitate lifestyle/behavior change. Few tools were found specifically for

team-based communication. In the second study, it was shown that implementation of a tool for

patient-centered, team-based communication was feasible. Numerically-higher continuity of care

scores were observed in the intervention arm relative to the control arm. In the third study,

participants felt that web-based communication tools provided more opportunity to seek

clarification between appointments. Patients, however, viewed such communication as

supplemental to clinical appointments, highlighting traditional face-to-face interaction with their

providers as an integral aspect of the therapeutic relationship.

Conclusions: Patient-provider team-based communication tools are promising. It is suggested

that patient-centered and team-specific implementation approaches are needed to optimize

uptake of tools for team-based communication in the complex care population. Further study is

needed to establish the effectiveness of improving continuity of care.

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ACKNOWLEDGEMENTS

First and foremost, I would like to thank my supervisor, Dr. Eva Grunfeld. I cannot express enough the gratitude I have for Eva for her incredible mentorship demonstrated both through her guidance in the development of my own capacities as a clinical epidemiologist, and through the excellence exhibited in her own academic practice as an expert trialist. I am indebted to her for the tremendous impact she has had on my learning through numerous research

opportunities and endless support.

I am grateful to my entire committee for being generous with their time and thorough

with their feedback. Their support and adaptability in guiding me through projects of vastly

different methodologies has been extraordinary. Dr. Jackie Bender is a phenomenal

behavioral/eHealth scientist who has brought a multitude of skillsets to this research and I am

grateful for her dedication to supporting me as a student. I am deeply appreciative of Dr. Amna

Husain, who leads the Loop Team; her vision for team-based care has been inspirational. I

appreciate the mentorship given to me by Dr. Monika Krzyzanowska, who is an exceptional

clinician and scientist, and great role model for handling both careers. Dr. Muhammad Mamdani

is a fantastic researcher and critical appraiser, often reminding me of the truths and limits of

methods. I am extremely thankful to Dr. Rahim Moineddin for his support and mentorship of my

statistical and methodological skills. Dr. Fiona Webster is the most gifted qualitative and social

sciences researcher; her guidance and friendship have been enormously meaningful to me as I

have completed this work.

Special thanks to Allison, Bhadra, and Trevor, without whom much of this work would

not have been possible. I greatly appreciate Alyssa’s commitment and dedication to the clinical trial and all of her hard work.

I would like to thank the patients who took part in these studies. I appreciate their contribution to our research, and my learning as a doctor-in-training.

The members of the DFCM Research Program have been pillars to my learning. I cannot thank enough Chris Meaney, Bojana Petrovic, Sumeet Kalia, Lindy Chan, Julia Baxter, and Dr.

Paul Krueger, who have supported me as colleagues and friends. Dr. Mary Ann O’Brien has been an exceptional mentor whose encouragement has meant a lot. I would also like to thank

Melanie Powis and Rebecca Prince who have been greatly supportive.

I love my family for supporting me in my endeavours.

I gratefully acknowledge the Canadian Institutes for Health Research and the

McLaughlin Foundation for their financial support of my MD/PhD.

I would like to thank the Clinical Epidemiology and Health Care Research Program at the

Institute for Health Policy, Management and Evaluation for providing an incredible training environment and great student support, as well as the Center for Global eHealth at the University

Health Network for their support of my research endeavours through the Kevin J. Leonard award, in memory of Dr. Kevin Leonard. I am especially thankful to Sandra for her encouragement in all aspects of this work.

TABLE OF CONTENTS

Acknowledgments...... iv Glossary of Abbreviations ...... viii Glossary of Terms ...... ix List of Tables ...... xii List of Figures ...... xiii List of Appendices ...... xiv Chapter 1: Background and Rationale ...... 1 1.1 Scope and Overview of Dissertation...... 1 1.2 Research Need ...... 3 1.3 Review of Major Concepts ...... 4 1.3.1 Complex care needs ...... 4 1.3.2 Team-based care ...... 7 1.3.3 Patient-centered care ...... 10 1.3.4 Continuity of care ...... 12 1.3.5 Communication in healthcare ...... 20 1.4 Health Information Technology ...... 23 1.4.1 Overview ...... 23 1.4.2 Digital health technology ...... 23 1.4.3 Information and Communication Technologies ...... 26 1.4.4 Evidence for effectiveness of online communication tools ...... 29 1.5 Rationale and Conceptual Model ...... 33 1.6 Purpose and Study Objectives ...... 38 1.6.1 Scoping review...... 39 1.6.2 Feasibility trial ...... 40 1.6.3 Qualitative study ...... 44 Chapter 2: A Scoping Review of Web-based Tools for Patient-Provider, Text-Based Communication in Chronic Conditions ...... 46 Abstract ...... 47 Background ...... 49 Methods...... 51 Results ...... 56 Discussion ...... 62 Conclusion ...... 67 Chapter 3: Feasibility Randomized Controlled Trial of a Web-based Communication Tool for Collaborative Care in Patients with Advanced Cancer ...... 85 Abstract ...... 86 Background ...... 88 Methods...... 90 Results ...... 97 Discussion ...... 100 Conclusion ...... 104 Chapter 4: Disruption or Innovation? A Qualitative Descriptive Study on Electronic Patient- Physician Communication in Advanced Cancer ...... 118 Abstract ...... 119

Background ...... 121 Methods...... 122 Results ...... 126 Discussion ...... 135 Conclusion ...... 138 Chapter 5: Discussion and Synthesis ...... 141 5.1 Summary of Results ...... 141 5.2 Interpretation ...... 143 5.2.1 Relation to the rationale ...... 144 5.2.2 Continuity of care ...... 145 5.2.3 Team-based care ...... 146 5.3 Comparison to the Literature ...... 149 5.3.1 Web-based tools for patient-provider communication ...... 149 5.3.2 Continuity of care in relation to the existing literature ...... 150 5.3.3 Team-based care in relation to the existing literature ...... 152 5.4 Strengths and Limitations ...... 156 5.5 Summary of Implications ...... 159 5.6 Knowledge Translation and Future Research ...... 161 Chapter 6: Conclusion...... 166 References ...... 167 Appendix ...... 194

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GLOSSARY OF ABBREVIATIONS

AHRC Applied Health Research Center

AHRQ Agency for Health Research Quality

CONSORT Consolidated Standards of Reporting Trials cRCT Cluster Randomized Controlled Trial

CVD Cardiovascular Disease

ECOG Eastern Cooperative Oncology Group scale

EMR Electronic Medical Record

IoM Institute of Medicine, now called the National Academy of Medicine

MeSH Medical Subject Heading

MRC Medical Research Council

NAM National Academy of Medicine

POS Palliative care Outcomes Scale

PRISMA Preferred Reporting Items for Systematic Reviews and Meta Analyses

RCT Randomized Controlled Trial

REDCap Research Electronic Data Capture

TIP Trial of Intervention Principles

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GLOSSARY OF TERMS

Complex care needs Patients with complex care needs may be defined1,2 by a combination of: • greater or more intensive use of medical services • care needing coordination across multiple providers • social supports to maintain functioning • associated conditions or multiple morbidities

Consumer health “Branch of medical informatics that analyses consumers' needs informatics for information; studies and implements methods of making information accessible to consumers; and models and integrates consumers' preferences into medical information systems.”3 Elements include3: • developing and evaluating methods, applications to support consumers in obtaining and use of health information • analyzing and integration of consumer needs/preferences in clinical practice, research, education • studying determinants, conditions to maximize effectiveness of systems • effects of these systems on public health, patient- professional relationship, society

Continuity of care “The delivery of services by different providers in a coherent, logical, and timely fashion”4 Informational continuity “use of information on past events and personal circumstances to make current care appropriate for each individual”4 Management continuity “consistent and coherent approach to the management of a health condition that is responsive to a patient's changing needs”4 Relational continuity “an ongoing therapeutic relationship between a patient and one or more providers”4

Digital health A newer term used to “[refer] to the use of information technology/electronic communication tools, services and processes to deliver health care services or to facilitate better health.”5

“The broad scope of digital health includes categories such as mobile health (mHealth), health information technology (IT), wearable devices, telehealth and telemedicine, and personalized medicine. Providers and other stakeholders are using digital health in their efforts to: reduce inefficiencies, improve access, reduce costs, increase quality, and, make medicine more

personalized for patients. Patients and consumers can use digital health to better manage and track their health and wellness related activities.”6 eHealth “the field [at] the intersection of medical informatics, public health and business, referring to health services and information delivered or enhanced through the Internet and related technologies.”7

Information and “a broad term used to describe a transmission or idea Communication exchange using equipment, tools, or networks. Examples of Technology ICTs include: the Internet, cell phones, and personal digital assistants.”8

Medical informatics “the field that concerns itself with cognitive, information processing, and communication tasks of medical practice, education, and research”3

Patient-provider Communication between patients and healthcare professionals. communication Digital health tools facilitating communication may be delineated into several paradigms by flow of communication9: • one-to-one: between a patient and a single provider • one-to-many: between a patient and multiple providers, in the form of multiple individual threads whereby providers cannot cross-communicate with other providers • many-to-many: between multiple individuals such as a patient and providers, allowing cross-communication between all individuals, such as in an online forum o Here, patient-provider team-based communication is used to refer to a form of many-to-many communication where communications from a patient are simultaneously viewable by the team of providers, and similarly, provider postings are viewable by the patient and other providers.

Supported self- Care management of a patient’s health condition, including management medical, coordinative and emotional aspects, by the patient themselves, supported by healthcare providers10,11

Team-based care “the provision of health services to individuals, families, and/or their communities by at least two health providers who work collaboratively with patients and their caregivers – to the extent preferred by each patient – to accomplish shared goals within and across settings to achieve coordinated, high quality care”12

Text-based communication As used in this dissertation, digital health tools which make use

of text (contrasted with audio and video) as the unit of communication

Therapeutic relationship As used in this dissertation, the relationship between provider of therapy and recipient of therapy (“patient”). Often connotes responsibility by the provider and trust from the patient. Therapy may be in the form of social support.

Web-based tool As used in this dissertation, digital health tools which are accessible on the web via a web browser

LIST OF TABLES

Chapter 1 Table 1: The term continuity of care contrasted with related concepts 14 Table 2: Comparison table of continuity of care with related terms 15

Chapter 2 Table 1: Published article characteristics 72 Table 2: Tool characteristics, Intended use and Users 74 Table 3: References by selected tool design and functions 76 Table 4: Evaluation characteristics of unique completed studies 79 Table 5: Tools identified from internet search 83

Chapter 3 Table 1: Baseline patient and family caregiver characteristics by 110 treatment arms Table 2: Baseline healthcare provider demographics 112 Table 3: Feasibility outcomes by treatment arm 113 Table 4: Preliminary measures of effectiveness by treatment arm, 114 Available case analysis Table 5: Complete case analysis preliminary measures of effectiveness 115 by treatment arm Table 6: Usage of Loop 116

Chapter 4 Table 1: Semi-structured interview guide 126 Table 2: Description of participants 127

xii

LIST OF FIGURES

Chapter 1 Figure 1 Continuity of care illustrated as having three interrelated 20 components Figure 2 eHealth Enhanced Chronic Care Model 34 Figure 3 Proposed eHealth solution to improve continuity of care 37

Chapter 2 Figure 1 PRISMA flow diagram 70 Figure 2 Published articles by year 72

Chapter 3 Figure 1 Screenshot of the Loop interface on desktop computer 107 Figure 2 Screenshot of the Loop interface on mobile phone 108 Figure 3 Participant flow diagram 109 Figure 4 Categories of messages on Loops with messages exchanged 117

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LIST OF APPENDICES

Appendix 1: Permission to Reproduce eCCM Diagram 195 Appendix 2: MEDLINE and EMBASE Search Strategy for Scoping Review 196 Appendix 3: Google Search Strategy for Scoping Review 208 Appendix 4: Data Extraction Form for Published Articles for Scoping Review 209 Appendix 5: Data Extraction Form for Internet Search Results for Scoping Review 213 Appendix 6: Coding Framework for Scoping Review 215 Appendix 7: Study Conclusions on Primary Outcome by Article for Scoping Review 217 Appendix 8: Coding Framework for Loop Usage for Pilot Trial 226 Appendix 9: Responses to Computer Usage Questionnaires by User Group for Trial 228 Appendix 10: Coding Framework for Qualitative Study 230 Appendix 11: Sample Consent Form for Pilot Trial 232 Appendix 12: University of Toronto Research Ethics Board Approval 238 Appendix 13: Loop Terms of Use 239 Appendix 14: My Team of Care Study Protocol 246 Appendix 15: Patient Screening Form 255 Appendix 16: Baseline Demographics, Computer and Internet Usage Questionnaire 258 Appendix 17: Palliative Care Outcomes Scale 262 Appendix 18: Picker Coordination and Continuity of Care Scale 264 Appendix 19: Edmonton Symptom Assessment Scale 266 Appendix 20: Ambulatory and Home Care Record 267 Appendix 21: Bedside Confusion Scale 279 Appendix 22: Eastern Cooperative Oncology Group Scale 280

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CHAPTER 1: BACKGROUND AND RATIONALE

1.1 Scope and Overview of Dissertation

As healthcare advances, patients are living longer and the care of those with chronic

diseases is becoming increasingly complex: treatment regimens are more sophisticated, more

options for supportive care are available, and there is greater choice for where and how care can

be delivered. However, the changing face of how a patient’s care is managed also necessitates greater use of healthcare resources in terms of financial costs, infrastructure and personnel. This is especially true for patients with complex care needs, such as patients with advanced cancer.

This translates to several different healthcare providers being involved in delivering specific, tailored care to patients over the course of illness and across different settings. The reality is that the healthcare system has not adapted to the need for a more collaborative nature of care, leaving informational gaps and relegating the burden of coordination to patients and their family caregivers.

Also, the recognition of patients as the stewards of their own health has led to a re- envisioning of healthcare delivery from traditional, paternalistic approaches to a patient-centered

model of care, taking patient values, experiences and perspectives into consideration. The last

decade has also seen the burgeoning of health information technologies on the coattails of near-

universal computer and internet access in North America and wide-spread use of social media.13

Aware of the potential to improve connectedness, access, and information archival in the setting

of medical record digitalization, several healthcare organizations have recommended leveraging

technology to address problems with care continuity.14-21 Accordingly, tools for information

exchange and communication, especially among teams, are a logical step towards these goals.

This dissertation examines digital health tools for team-based communication, their feasibility in practice and role in improving continuity of care. To this end, three studies were conducted. The first reviews the current landscape of web-based communication tools for patient-provider, text-based communication in the context of chronic conditions, and is presented in Chapter 2. The second study is a feasibility trial evaluating implementation and potential effect of a web-based tool for team-based communication in the advanced cancer population, and is presented in Chapter 3. The third is a concurrent qualitative study nested within the trial which contextualizes the role of the tool on patient-centered care and the patient-provider relationship, and is presented in Chapter 4.

This introductory chapter provides an overview of relevant material to frame this

dissertation. Section 1.2, Research Need, describes the impetuses of this dissertation. Section

1.3, Review of Major Concepts, introduces pertinent concepts motivating the overarching

objective. Section 1.4, Health Information Technology introduces digital health tools as solutions

suitable to addressing the gaps identified in Research Need and Review of Major Concepts.

Section 1.5, Rationale and Conceptual Model delineates the rationale for this dissertation.

Section 1.6 outlines the three studies pursued in this dissertation to address the presented

purpose.

1.2 Research Need

This research is based on the premise that patients with advanced cancer have complex care needs addressed by multiple healthcare providers. The current setup of different

professionals working in different settings/disciplines, and not adequately communicating and consulting with each other, could be jeopardizing patient well-being, increasing inefficiency, increasing costs to the healthcare system, and adding burden to patients and family members.

Developing strategies to improve clinical communication is seen as one of the solutions to address these concerns. The focus on communication is fueled by the growth of information technology, and popularity of different communication media. Availability of a secure, web- based, asynchronous communication system could significantly improve access to care for patients and family members, enhance coordination of services, ensure continuity of care and lead to better outcomes such as improved quality of care and symptom management.

1.3 Review of Major Concepts

This dissertation is based on a number of key concepts drawn from the literature and an

awareness of current care gaps, as summarized:

1. Care delivery in patients with complex care needs is fragmented

2. Such needs are best addressed by a team of specialists with varied expertise

3. The common, unifying objective of the team should be patient-centered care

4. Efforts should be coherent to improve continuity of care, and

5. Enhancing communication between patients, their families and providers will help to

accomplish these objectives and improve outcomes.

1.3.1 Complex care needs

Several definitions for “patients with complex care needs” can be found in the literature.

The Agency for Health Research Quality (AHRQ) specifies that these patients, “require more intensive medical services coordinated across multiple providers, as well as a wide range of social supports to maintain health and functioning.”2 The American Geriatrics Society includes in its definition conditions requiring continuous care22 and the Robert Wood Johnson Foundation indicates that such patients have, “multiple chronic conditions, frequent hospitalizations, and limitations on their ability to perform basic daily functions due to physical, mental and psychosocial challenges.”1 Family members or paid caregivers are often needed to assist with keeping track of and transportation to medical appointments, assisting with activities of daily living and ensuring combinations of medications are taken as prescribed. Given the multifaceted nature of how “complex care” has been defined by these different organizations, identifying the subset of the patient population that can be termed complex is challenging. Common elements

include higher utilization of healthcare services, involvement of several different healthcare

professionals, ongoing care needs and potential functional limitations due to multiple comorbid

conditions.

Moreover, the complexity of illness gets mirrored in the complexity of how a patient’s

care is managed by providers. In Canada, nearly 1 in 4 individuals have at least two chronic

diseases23,24 with greater comorbidity corresponding to a greater number of healthcare providers

needed by a patient.25 A study of Medicare beneficiaries in the United States found that patients

with 1 to 2 chronic conditions saw a median of 3 physicians in a given year and up to 16

different physicians as the number of comorbidities increased.26 Furthermore, clinical practice

guidelines are often disease-specific, and unaccommodating of patients with comorbidity or

complexity.27,28 With the healthcare system organized to focus on treating a single disease at a

given time, as reflected in specialization of healthcare providers and disease-specific clinics, care

is often delivered in silos. The consequences of this structure of care provision is poor

coordination between healthcare providers, patients and care facilities29-31, and missing or late

clinical information like diagnostic tests or reports between settings32,33 or after hospital

discharge34,35. Moreover, patients and their caregivers end up as the only common thread

between providers and settings, shouldering the burden of care coordination themselves.36

Care coordination refers to the integration of patient care activities between two or more providers to facilitate delivery of health services.37 The issue of fragmented care delivery in the

care of chronic conditions translates to significant negative impacts on quality of care in terms of increased costs38,39 and decreased safety40,41. From the cost perspective, Berwick et al. (2012)42

highlighted care coordination and administrative complexity as “wedges of waste” which cost

the American healthcare system billions of dollars annually. From the safety perspective,

Schwappach (2014)43 identified that patient-reported medical errors were correlated with the

number of providers a patient had, with the odds being two times higher when a patient had three

physicians. Patients may be at risk of severe adverse events if exchange of information is not

timely.34 Bodenheimer (2008),44 reflecting on care coordination in patients with medical

complexity, suggested among many possibilities, four barriers to coordination that should be

addressed. The first was an under-reliance on primary care to manage coordination because of

overwhelming patient loads preventing adequate attention to each. The second was the slow

uptake of electronic medical records (EMRs) and lacking interoperability of EMRs across

settings. As a means to store a potentially unlimited and easily accessed archive of patient

medical information, EMRs could revolutionize information exchange and communication if

systems are interoperable between different healthcare institutions. In Ontario, EMRs between

institutions, hospitals and community-based practices have yet to become interoperable.45 The

third was a lack of financial incentives for physicians to spend time on care coordination,

especially in fee-for-service models. The fourth relates to poor healthcare system integration

especially between independent practices, hospital services and emergency departments, which

are functionally separated because of inadequate information sharing.

As survival increases due to advances in screening and treatments, cancer is increasingly

viewed as a chronic disease. Two in five Canadians will develop cancer over their lifetime with

an average five-year survival rate of 60% across all cancers, though survival for some cancers

such as of the thyroid can be as high as 98%.46 As patients are living longer, more patients with

cancer also have comorbid conditions, in addition to being older (the median age of incident

cancers is between 65 and 6946).47 The complex care needs of cancer patients are exemplified acutely in advanced cancer where patients tend to have greater emotional and psychological

7 stresses due to anxiety and uncertainty, and greater communication/informational needs.48-51

Fragmentation of care is aggravated by multiple professionals, such as medical oncologists, radiation oncologists, primary care physicians, surgical oncologists, therapists, nurses, social workers, and complicated care plans that are frequently revised and modified. As advanced cancer patients have progressed through a trajectory of care involving screening, diagnosis, treatment, and survivorship or palliative care (“cancer care continuum”), there is a greater chance for gaps in information sharing and poor care coordination across health events as well as between providers.52

1.3.2 Team-based care

The National Academy of Medicine (NAM) (formerly known as the Institute of

Medicine) is an American organization of healthcare professionals, scientists and policy-makers whose mandate is to identify important issues in healthcare and inspire change.

In the setting of chronic diseases, effective care is benefited from a team of providers because of the different skills, knowledge and specialized observations brought by individuals from different disciplines. In a discussion paper about effective team-based healthcare,12 the

NAM adapted a definition from Naylor et al.53 to define team-based care as “the provision of health services to individuals, families, and/or their communities by at least two health providers who work collaboratively with patients and their caregivers – to the extent preferred by each patient – to accomplish shared goals within and across settings to achieve coordinated, high quality care”. The NAM paper highlights five principles of team-based healthcare: 1) shared goals – goals should be understood by all team members, including patients and caregivers; 2) clear roles – the expectations from each team member are clear and each is held accountable; 3)

mutual trust – respect for the role each plays, which is necessary to strengthen reciprocity; 4) effective communication – consistent channels for communication which are accessible to team members across all settings; 5) measurable processes and outcomes – agreed upon methods for

sharing feedback on functioning of the team and achievement of goals.12

Implicit in this definition are the expectations that team-based care will enable

coordinated delivery of care (organized care delivery by two or more providers), and that teams

should work collaboratively. Collaboration has been defined by Health Canada as, “a

patient/client-centered process in which two or more professions/disciplines interact to share

knowledge, expertise and decision-making in the interest of improved patient/client care”.54 In

the business literature, Katzenbach et al.55 is noted for distinguishing a team as a group that

collectively works toward a goal of higher significance than could be achieved by individuals in

the group working independently.

While definitions of team functioning share a common theme of striving for effective

collaboration between multiple parties, the way in which teams are described as functioning

varies considerably.56 A conceptual framework by Boon et al.57 outlines seven models of how

team-based care might be realized in practice along a spectrum: parallel, consultative,

collaborative, coordinated, multidisciplinary, interdisciplinary, and integrative. On one end of the

spectrum, parallel models involve healthcare providers working in a shared setting but

performing independently within the scope of his/her practice – this approach does not

incorporate the collaboration implicit in the NAM definition. On the other end, integrative

practice involves a non-hierarchical, interdisciplinary approach focused on treating the whole

person and accordingly involves providers from outside mainstream medicine, including

complementary healthcare. As the terminology surfaces frequently in the literature of this field,

Boon et al. distinguish multidisciplinary and interdisciplinary as follows: a multidisciplinary

model involves multiple providers from different disciplines making their own decisions which

are integrated by a team leader (may be a care manager) to create care plans; an interdisciplinary

model is similar to multidisciplinary but decisions are made by the team members as a group

through face-to-face meetings.57 According to the authors, as one moves from one end of the

spectrum to the other, complexity increases, provider autonomy (and thus hierarchy) decreases

and the diversity of outcomes affected increase.

An outline of such models is helpful in recognizing the breadth of approaches that a group of providers caring for a given patient might adopt. However, in practice, team structure may vary by situation, care needs of the patient and availability of resources. In the context of cancer care, specialization of oncologists occurs by treatment modality (medical, radiation and surgery) and cancer site (breast, lung etc.) and as such, as a patient’s disease progresses and treatment required changes, the responsibility for care changes.58 Within the cancer center,

interventions such as multidisciplinary rounds for complex case discussion, and sharing of

information sources, through shared EMRs or clinical notes have been shown to be effective at

engaging providers from different disciplines in decision-making at a given point in time.12,59

However, models of multidisciplinary care that involve providers outside the care teams at the

cancer center, such as primary care physician-led60 and patient navigator-led61 models, aim to

facilitate smoother transitions along the cancer care continuum or serve as a common thread

across these transitions by virtue of being detached from a single center.

The effort required to develop team-based care approaches may be considerable,

however, such that the transactional cost of team-development outweighs the benefits.62 Barriers

to effective team-based care may include, among others, “cultural silos” – discipline

territoriality,62 differing perspectives on care goals by specialty or setting, lack of reimbursement

for team development/team-based implementation approaches, poor infrastructure to facilitate

teamwork, and lack of synchronized schedules.63 While observance of the aforementioned

principles may better facilitate team-based care delivery, interventions such as team huddles64,

checklists65, team-building workshops and interprofessional education63 have been shown to

improve outcomes by providing a means for team development and collaboration.66 As the awareness that effective communication of care plans and information exchange are central, if not foundational, to team-based care, there is an increasing recognition that health information technology may serve as a new catalyst to enhance team functioning.20,67

1.3.3 Patient-centered care

As an authoritative body, reports commissioned by the NAM lay out a roadmap of

priorities concerning the healthcare system at large, and provide a template for bringing about

change. Three of these reports have particular relevance to the coordination of care issues discussed in section 1.3.1.

The first report, Crossing the Quality Chasm20, directly recognized that in the context of

chronic conditions, especially in patients with multimorbidity, the delivery of care is generally

complex and uncoordinated. The report proposed a re-envisioning of healthcare delivery to better

meet the needs of patients by making care safer, more effective, efficient, timely, equitable, and

patient-centered. Patient-centered care is defined as, “providing care that is respectful of and

responsive to individual patient preferences, needs, and values, and ensuring that patient values

guide all clinical decisions.”20 The report presented a framework connecting patient-centered,

team-based care delivery to improving these system-level outcomes and suggested six strategies

in order to accomplish improvement:

1) Redesigned care processes

2) Effective use of information technologies

3) Knowledge and skills management

4) Development of effective teams

5) Coordination of care across patient conditions, services, and settings over time

6) Use of performance and outcome measurement for continuous quality improvement

and accountability

At the time the report was published in 2001, strategies 2, 4 and 5 were very novel, and held

great potential for innovation in healthcare with the emergence of patient-centered approaches.68

As discussed further in section 1.4, the emergence of health information technology has

anticipated these issues in a manner that could facilitate these proposed strategies.

The second report, Patient Safety: Achieving a New Standard for Care (2004)69, proposed that a crucial step to improving the healthcare system was to improve the quality of care through gains in patient safety. The report emphasized the need for better sharing of health information, further highlighting imperatives of the previous report as its first recommendation: Improved information and data systems are needed.

The third report, Delivering High-Quality Cancer Care (2013)69, reiterates these stances

in the context of cancer care. Recognizing the complex needs in cancer care and the deficiencies

in care coordination, the report’s framework envisions the cancer care continuum occurring from

diagnosis to survivorship/end-of-life care, and again highlights the need for greater patient

engagement to make cancer care specifically more patient-centered and relying on information

technology to improve coordination and quality of care.

Again and again organizations, from the Agency for Health Research Quality70, the

American Society for Clinical Oncology71, in the cancer context, and Cancer Care Ontario in the

Ontario Cancer Plan IV72, in the local context, have pointed to a lack of care coordination as a

key detriment to patient safety and healthcare costs, and the need for patient-centered care

delivery, delivered by teams and leveraging the potential of health information technology, as

part of the solution.

Epstein et al., in a discussion of patient-centered care as it relates to health outcomes, reflected on how healthcare institutions misapply the lens of patient-centeredness to justify

“greeters, greenery, and gadgetry”; this includes implementing EMRs and patient portals.73

However, such simplistic upgrades are not patient-centered, the authors assert, unless they

contribute to better communication and development of the patient-physician relationship. The authors also make clear that, ultimately, patient-centeredness means that a good outcome should be defined by what is meaningful to the patient.73

1.3.4 Continuity of care

In the Crossing the Quality Chasm report,20 the fifth strategy to making care more

patient-centered highlights, “coordination of care across patient conditions, services, and settings

over time.” Similarly, many related terms are used, often interchangeably, to describe provider

and health system efforts to make care more organized: coordination of care, care management

and integration of care. However, these terms often refer to organization at the health system or

provider level, and not as viewed from the perspective of the patient.74

Continuity of care has been defined by Haggerty and others as the “delivery of services

by different providers in a coherent, logical, and timely fashion”.4 The authors distinguish continuity from coordination or care integration by a focus on the patient’s medical needs, context, and care delivery over time. Continuity of care is further delineated into three related components: informational, management and relational continuity.4 Informational continuity is

“the use of information on past events and personal circumstances to make current care

appropriate for each individual”.4 Management continuity is the coherent delivery of services,

and sharing of care plans and management goals among providers, in a manner that is responsive

to a patient’s needs.4,75 Relational continuity is the “ongoing therapeutic relationship between a

patient and one or more providers”.4 In their paper, the authors indicate that each component of continuity may be emphasized depending on the type and setting of care (see Figure 1, pg. 20 for a representation). A comparison of continuity of care with related terms (coordination of care, care management and integration of care) is presented in Table 1 and Table 2, noting distinguishing elements and overlap with continuity of care. Continuity of care definitions tend to be focused on the patient perspective, thus lending a stronger view of the importance of the relationship with providers compared to related terms. There is also an explicit noting of the longitudinal nature of all components of continuity; that continuity changes over time and across

health events.

Table 1 The term continuity of care contrasted with related concepts Term Definition Continuity of care The “delivery of services by different providers in a coherent, logical and timely fashion.”74 Haggerty and colleagues distinguish continuity of care from other related concepts by two core elements4: • experienced care by a single patient with one or more providers • received over time Continuity fundamentally differs from similar concepts in that it is from the perspective of the patient. Reid et al.74 have further described how the interrelated components of continuity of care are understood from this perspective. Regarding informational continuity, documentation of health conditions and its treatment “links care from one provider to another and from one health event to another”, but also refers to accumulated knowledge of “patient’s values, preferences, and social context.”74 Management continuity represents a common understanding of the plan of care between providers, facilitating “timely and complementary services”74 for patients. The longitudinal nature of the relationship, as defined in relational continuity, creates patient confidence and trust in their provider, and “ongoing provider responsibility to the patient.”74 Coordination of care Defined here as integration of patient care activities between two or more providers to facilitate delivery of health services,37 care coordination is typically understood from the health system perspective. The definition adopted here, from an AHRQ review, comprises of five elements37: 1. several participants involved 2. participants are dependent on each other to carry out “disparate activities”37 3. participants must have knowledge of their roles and others, and available resources 4. exchange of information is central 5. the goal is to facilitate appropriate delivery of health services

Uijen et al.76 has noted that the term has evolved over decades, with the definition arising in the 1990’s being defined according the patient perspective as “the patient’s perception of their care provider’s knowledge of other visits to them and visits to specialists as well as follow-up of problems through subsequent visits or phone calls.”77 Uijen et al. remarked on the similarity to the above definition of continuity of care. Care management Used in this dissertation to refer to planning and organizing individual patient care; not necessarily by multiple providers. However, organizations like the AHRQ78 and Center for Health Care Strategies,79 have described care management at a programmatic level “apply[ing] systems, science, incentives, and information to improve medical practice and assist consumers and their support system to become engaged in a collaborative process designed to manage medical/social/mental health conditions more effectively.” • care management is intended to improve care coordination78 Integration of care Early uses of the term, integration of care, were used to contrast with care fragmentation.80 That is, bringing together disparate entities involved in care delivery (providers, resources, finances from different systems). As Uijen et al.37 noted, this reflects management or team continuity most closely but also intersects with informational continuity. However, organizations like Health Quality Ontario, refer to the experience of integrated care as including care coordination and good communication, suggesting a system and provider-level perspective.81 Singer et al.,82 in a highly-cited paper, discuss integrated care referring to coordination within teams, across teams, across support systems, over time, and care that is responsive between visits, patient-centered, and based on shared responsibility with patients.

Table 2 Comparison table of continuity of care with related terms

Continuity of care Coordination of care Care management Integration of care

Perspective Health system or Health system- provider/patient- dominant (some Provider/Program Patient dominant (some authors also refer to level-dominant authors also refer to program-level or program-level) patient-level) Temporality Not specified but Not specified, but often implicit that likely implicit that Longitudinal coordination is over Not specified integration is time and between considered over time providers Focus Informational Resources, consistency across Role awareness, Organized delivery of management of providers and health informational health services with patient care, sharing events, coherent consistency, aim of effective of information, management among organized delivery of collaboration degree of providers, ongoing health services coordination relationships Measurement Several tools exist for Several care Measurement tools In a systematic measurement of coordination specifically focusing review of instruments continuity of care, as measures exist, often on measuring care to measure described on pg. 17. in relation to, or a part management could integration of care, Examples include the of, measures of not be found, but Bautista et al. 92 Picker scale,83 the patient experience, surveys like the identified 209 Nijmegen scale,84 and care transitions, National Survey of instruments. the Haggerty et al. decision-making, Physician However, the authors scale85 addressing care needs Organizations and the acknowledged that etc. The AHRQ has Management of there remains conducted a review Chronic Illness II,90 ambiguity in identifying 80 such include domains on definition, and instruments. 86 care management.91 recognize that conceptual Examples include the As described below, frameworks show Consumer care management is overlap with Assessment of often implicit in continuity, Healthcare Providers definitions of care coordination and and Systems coordination. management of care. Patient Centered Medical Home Example instruments Survey,87 identified in the Collaboration and review include the Satisfaction about Cancer Services Care Decisions Integration tool,93 and (CSACD),88 Picker Patient Perceptions of Patient Experience Integrated Care Survey (PPE-15)89 Survey.94 In this review, many of the same instruments for continuity of care and coordination of care were also present.

Discussion The authors of the Haggerty et al.4 framework of continuity of care specifically distinguish continuity of care as being a patient-perspective concept that is understood over time. Related concepts such as coordination of care, care management and integration of care are often less explicit about these elements, though many authors imply that any of these concepts may be understood from the health system perspective, program/provider-level perspective or patient perspective, and over time. Furthermore, in examining measurement tools, review authors often used each of these concepts as key terms in searches of the respective concept under study, suggesting that the these terms are used interchangeably.

Drawing on the definitions from organizations such as the AHRQ and systematic reviews,86,91,92,95 some general (but certainly not definitive or universally-accepted) points can be made: • Care management, according to the AHRQ, is a subordinate element of approaches to improving care coordination. It may not be considered an independent outcome but rather a process of care.96 • Definitions of integration of care also suggest health system- or program-level coordination as inherent. A cursory review of example instruments for measuring integration of care identified perceptions on care coordination and care management as common domains of measurement tools. • Systematic reviews86,91,92,95 of coordination or integration of care measurement tools also retrieved instruments for measuring continuity of care. These suggest that distinction between all of these concepts requires ongoing work to establish clarity of definition, though research making use of any one should be clear on the specific definition is used.

Continuity of care is an important outcome in chronic disease care because it signifies

stability in management and shared responsibility in coordination between patients and

providers. During transitions, it connotes sufficient overlap in management of a patient’s care so

that information does not get misplaced or forgotten. Over the course of an illness, constancy in

relationships with providers helps patients feel well-cared for. Furthermore, much research demonstrates the importance of the concept of continuity of care through its correlation with outcomes such as quality of care,97 information at follow-up,34 supportive care needs,98 and self-

management behaviours.99 Also, associations of quantitative measures of continuity (as

described below) have been shown with healthcare utilization100 and use of preventive

services.101

To briefly review, the measurement of continuity of care can be considered from the

perspectives of quantitative, claims-based ratios for application in population administrative data, or patient-reported outcomes by way of validated measurement instruments assessing an

underlying construct or related constructs.

Claims-based measures focus on the extent to which a patient is seen by the same

provider over multiple visits, or number of handoffs between providers.102 For example, the

103 ( ) Bice-Boxerman Continuity of Care Index , 푝( 2 ) , represents the degree to which ∑푖=1 푛푖 −푛 푛 푛−1 individuals use different providers (p), with number of visits (n), and number of visits to provider

104 i, (ni). The Breslau et al. method , , represents the concentration of visits with a given 푛푖 푛

provider. The Sequential Continuity Index, 푛−1 , additionally considers the number of ∑푗=1 푐푗 푛−1 sequential visits to the same provider (cj), representing handoffs in care. While these metrics

have the advantages of being relatively simple and broadly applicable (a necessity for use in

administrative data), they do not account for the nuances of the continuity of care components

described above nor can they be considered sufficiently from the patient perspective.

In contrast, several patient-reported instruments aim to measure continuity of care in a

way that reflects its multifaceted nature, and adopt a patient-centered perspective.95 The

Nijmegen Continuity Questionnaire84, for example, is a 28-item measure evaluated in the general

primary care population among patients with chronic diseases. The key domains informing item

generation were 1) the patient having a personal care provider with whom to develop an ongoing

relationship (“relational continuity”), and 2) communication and cooperation between providers

(“informational/management continuity”). The internal consistency (Cronbach’s α) ranged from

0.82-0.89 and inter-item correlation (Pearson correlation coefficient) ranged from 0.42-0.61.

Test-retest reliability, responsiveness and criterion validity had not been evaluated.

Haggerty et al.85 developed the Patient Experience of Continuity of Care instrument with

the initial intent of measuring management continuity but found that it could not be extricated

from the informational and relational components. Validated in the general primary care context,

the 37-item instrument reflected role-based components related to a main clinician

(“management/relational continuity”), additional clinicians (“team relational, management and

informational continuity), and patient as care partner (“management/informational continuity”).

The internal consistency ranged from 0.8-0.93 and inter-item correlation ranged from 0.44-0.81,

varying by set of items within each dimension.

The drawback of these measures has been that they have not been fully evaluated or

validated in the population of interest here, the advanced cancer population, because of their novelty. In the cancer context specifically, the Picker Ambulatory Oncology Instrument, developed by the National Research Corporation (2003)83, is an early instrument initially utilized

as a patient experience tool. It has been widely validated in the cancer setting among 6400

patients across the United States. The 8-item Coordination and Continuity subscale has an

evaluative aim. The average internal consistency is 0.83 and inter-item correlation is 0.33. The

tool has been evaluated for criterion validity against the overall impressions subscale achieving

an average Cronbach’s α=0.68. The instrument has further shown to be correlated with

supportive care needs and been validated in the advanced cancer population.98,102

As discussed above, the nature of cancer care is one that often involves the delivery of

services across settings, providers and time. Consequently, the concept of continuity of care

serves as a strong foundation for improving the quality of care delivery and patient

experience.105,106 A Cochrane systematic review by Aubin et al. (2012) of interventions to

improve continuity of care in cancer has been conducted but showed no evidence to support or

refute interventions to improve outcomes across reviewed studies.107 Heterogeneity in types and

delivery of interventions and outcomes were cited as reasons for inconclusive findings. Fifty-one

studies were identified and interventions were classified into three different “models”, delineated

and defined by the authors: case management, shared care or interdisciplinary team. Case

management was described as coordinating human services for a patient by a designated

individual or team (“case manager”). Shared care was described as primary care and specialist

physicians jointly participating in delivery of care, and includes enhanced information sharing.

Interdisciplinary team was described as healthcare providers from different professions, usually

within the same setting, jointly participating in decision-making. Studies were included if they aimed to improve continuity of care, but outcomes included a variety of measures such as functional status, physical status, quality of life etc. Interventions designed to improve continuity of care on outcomes were compared to usual care, but the quality of evidence was rated as “very

low”. Meta-analyses showed improvement on satisfaction and quality of life but other outcomes,

such as functional and physical status showed negligible effect sizes. Case management models

were designed to affect relational and management continuity while shared care and

interdisciplinary models were designed to affect management and informational continuity. The

authors noted that newer technologies, such as patient-portable health records and case

discussion tools for distant health professionals, were promising new avenues for study.

Figure 1 A representation of continuity of care as per Reid, Haggerty et al.5 illustrated as having three interrelated components: informational continuity, management continuity and relational continuity.

Continuity of care

1.3.5 Communication in healthcare

Communication is a central theme to care coordination and team-based care delivery. It is defined as, “a process by which information is exchanged between individuals through a common system of symbols, signs, or behavior”.108 In the context of healthcare delivery to a

patient, this bidirectional exchange occurs between healthcare providers or between patient and

provider.

Between healthcare providers, the objective of interaction, at its most basic level, is the

exchange of patient-related clinical information.109 This would traditionally occur in the form of

face-to-face interaction, orders/clinical notes in the medical record or telephone messages. In typical practice, it is rare that healthcare providers from different disciplines or at different institutions would communicate in real-time in the way that groups of clinicians working on the same ward or in the same hospital do. Individuals who work together in the same setting every day become naturally familiar with each other’s work habits, preferences and communication styles.110 As such, these groups build greater trust and understanding for each other, and thus

work, from a functional perspective, as a team.111 There is less opportunity for team building

among providers from different settings. Nonetheless, barriers to communication between

providers and broader teams, whether working within the same organization or not, may prevent

effective functioning: a) structural barriers like location, such as between hospital and

community-based providers, and absence of venues for information sharing; b) organizational

barriers, such as differing priorities between specialties and perceived loss of autonomy by

sharing decision-making responsibilities; and c) relational barriers, such as social hierarchies (ex.

between staff and residents), role ambiguity or ethnic/cultural/language barriers.41

Substantial research has established the importance of patient-provider communication to

the function of clinical practice and the therapeutic role of physicians.112,113 The interaction

between a patient and physician during a typical clinical encounter involves sharing of

information while aiming to accomplish the objectives of history-taking, discussing treatment

options and charting out a care plan.114 Epstein et al.115 contextualized the importance of good

patient-physician communication and its impact in cancer. The communication tasks of a

physician in the treatment phase and end-of-life phase of the cancer care continuum include

presenting treatment information, eliciting side effects and symptoms, and communicating

prognosis. As proximal effects, patients have a better understanding of treatment options, more

22 trust in clinicians, greater motivation and self-efficacy, and are more engaged in decisions.115

However, patient-provider communication is itself a form of social support, providing encouragement, hope, and greater quality of life, which are ultimate outcomes in palliative care.116 With multiple clinical encounters over the course of a health event, the patient-provider relationship becomes strengthened as a partnership, and relational continuity is improved because of predictability and confidence in future care.75 As such, “patients’ experience of continuity goes beyond health encounters to include connectedness between their personal lives and the health system.”75 That is, to patients, the relationship with the healthcare system is not viewed as separate from other relationships, but as a facet that is continuous with all other interactions.

Health information technology has the potential to liberate care delivery from the usual arc of a single health encounter, and empower patients with their team to share in deliberation and care planning, and foster optimal decision-making – processes founded on communication.117 In the following sections, information and communication technologies

(ICTs) are introduced as a means to address the outcomes articulated by the NAM in the

Crossing the Quality Chasm report20 to make care safer, more effective, efficient, timely, equitable, and patient-centered:

1) safer, timely and efficient through better documentation and more immediate sharing

of information among all members of the team,

2) equitable and patient-centered through improved patient accessibility to care and

involvement in care decisions,

3) and more effective as a result of these improvements, and as discussed further below.

1.4 Health Information Technology

1.4.1 Overview

Relatively few innovations have the potential to practically address the problems at hand

while also aligning with demographic trends in internet use as health information technology; it

is one of the few inevitable changes to the healthcare system where others might require

substantial upgrades to physical infrastructure and reorganization of care delivery.118

One of the early precursors to the modern day internet, ARPANET, comprised of a

distributed computational network based on the concept of packet switching, in which blocks of

data were transmitted across processing nodes. The earliest network, in 1969, was between

Stanford University, UCLA, UC Santa Barbara, and University of Utah.119 Today, an average of

88.5% of Canadians have access to the internet (based on World Bank data from 2015) and 82%

have access to mobile phones13. From Statistics Canada data in 2012, 93% of internet users had email, 66.8% of users searched the web for medical or health-related information, and 67% used social networking websites.120 Many sectors of society have become reliant on networked

computer-based technologies like email; in 2007 (latest available Canadian statistics), 81% of

private sector enterprises used email, including 96% of professional, scientific and technical

services, 80% of healthcare and social assistance and 82% of finance and insurance

companies.121 One hundred percent of public sector enterprises, including government agencies

reported using email, the form of digital communication described in available data.121

1.4.2 Digital health technology

The ubiquity of information technology in society as a whole is reflected within healthcare as well, and is often encapsulated by the terms digital health and eHealth. Digital

health is a newer term that tends to be used in conjunction with tools: it “includes categories such

as mobile health (mHealth), health information technology, wearable devices, telehealth and

telemedicine, and personalized medicine.”6 eHealth refers to the “field [at] the intersection of

medical informatics, public health and business, referring to health services and information

delivered or enhanced through the Internet and related technologies.”7 It broadens the scope of

health information technology from a focus on the system or application at hand to its wider

place within the societal fabric.122 While tools or technologies are still associated with this term,

the study of eHealth, as it is understood here, often has to do with the place of these tools in

terms of their use and utility to providers and patients.

Of Bodenheimer’s four barriers to effective coordination of care (introduced in section

1.3.1),44 two of them, the lack of interoperable computerized records and the lack of integrated

systems of care, imply clear opportunities for digital health tools to address the issues related to

care coordination from a system and provider perspective. The myriad tools should facilitate

systematic collection of data and rapid sharing of information which should therefore improve

quality, efficiency and safety of care.70 This has been echoed by countless organizations

(National Academy of Medicine,21 Agency for Healthcare Quality and Improvement,17,123

American Medical Association,14 American Association of Nursing,18 Canadian Medical

Association,15,16 Canada Health Infoway19) who view the eHealth field as a means to make

information “accessible, timely, customizable and portable.”18

Black et al.124 mapped digital health technologies, as used by providers in the healthcare

setting (i.e. hospitals, clinics), into three main categories. The categories and examples provided

by Black et al. are summarized here to provide context to the electronic environment:

1) to enable the storage, retrieval, and transmission of data

a. EMRs- digitized health record, preferably across providers and events. Can

function in “data input, storage, display, retrieval…and sharing of

information.”124

b. Picture archiving and communication system- exchange system of digitized

images like radiographs; facilitates sharing and preservation of images.

2) to support clinical decision-making

a. Computerized provider order entry (CPOEs)- used by clinicians to

communicate referrals and test orders, review test results. Considered point of

care/workflow enhancements.

b. ePrescribing- systems used to submit, review and change medication

prescriptions

c. Computerized decision support systems (CDSSs)- information systems which

“integrate clinical and demographic patient [inputs]”,124 to generate prompts

or notifications requiring actions to be taken based on a series of logic

algorithms. Used as reminder system or method of standardizing care

according to protocols.

3) to facilitate remote care- this category was not discussed at length in the Black et al.

article but would include such technologies as tools for telemedicine/telehealth (e.g.

telepathology/teleradiology), including video conferencing consults, and devices for

remote monitoring (e.g. blood pressure monitors).19

However, the field encompasses much more beyond technologies used in the immediate healthcare setting by providers. The branch of consumer health informatics looks at the needs,

determinants, integration and effects of applications for health consumers, such as patients.3 This

includes digital health technologies like web-based patient portals which enable patients to

access their clinical data, informational/educational websites, and interactive health

communication applications which include e-consultations (such as the eConsult service125),

peer-to-peer online communities, online tailored education and feedback, and secure

messaging.14,118,126 The last of these categories, falling within information and communication

technology (ICT), is the focus of this dissertation.

1.4.3 Information and Communication Technologies

As access to the internet and other technologies has grown, patient consumption of health

information127 and their desire to make use of information to assume greater responsibility for

their healthcare has increased.128 Accordingly, the age of eHealth has contributed to, and

enabled, the evolution towards patient-centered care. Patients are thus responsible for

“producing” their own health by taking charge through actively accessing information, self-

managing, and making decisions informed by their own preferences and values to become well

according to their own standards.129 The paradigm of evidence-based medicine has similarly shifted the emphasis away from physicians who justify a clinical decision based on authority to justification based on evidence of effectiveness.130 The modern role of healthcare providers is

therefore to curate and integrate patient-specific clinical information, guided by an understanding of the evidence, to allow informed, empowered patients to be partners in their care.130

Digital health tools for patient-provider communication are an emerging venue by which supportive healthcare may be provided.131 In the context of chronic diseases, tools for patient- provider communication could facilitate patient self-management through routine check-ins with

healthcare providers, and facilitate the opportunity to ask questions outside of appointments. By

allowing for the patient to address issues most immediately while in their own context (i.e. at

home), providers can help patients handle their care themselves. Such supported self-

management fosters better patient empowerment, a patient’s capacity to make informed decisions.132 Especially with chronic conditions, empowerment represents respect for patient

preference and autonomy, and, practically, it enables self-stewardship of health. This has been

substantiated by research relating empowerment to improved quality of care, safety and clinical

outcomes.133,134

Unlike traditional modes of communicating outside of appointments (i.e. telephone),

patient-provider communication tools can function asynchronously (not requiring real-time

responses), accommodating the schedules of busy clinicians. A wide variety of tools for

asynchronous communication exists, and can include remote monitoring of symptoms or

teledermatology, for example.135 Web-based tools for text-based communication, specifically, allow users (patients or providers) to carefully construct a message to include personal information otherwise not available in raw clinical data. Email, secure messaging, and communication components of patient portals serve this same function but through different interfaces. In the healthcare setting, web-based tools, specifically, often have added layers of security to ensure confidential transfer of patient-related clinical information.136 These tools typically store messages on a server rather than on the recipient computer (like standard email), involve encryption of the message, and must comply with regulatory standards for privacy (such as the Health Insurance Portability and Accountability Act).136,137

Drawing on the lexicon of computer network/telecommunication paradigms,

communication tools could be delineated as facilitating one-to-one, one-to-many, and many-to-

many communication.9,138 One-to-one involves communication between one user and another single user; email between two individuals is such an example. One-to-many involves a single individual communicating to multiple other users; listservs or massive online open courses are examples of one-to-many. Many-to-many communication allows individuals to cross- communicate with other individuals; this category could include peer-to-peer forums and group messaging.

The focus of this dissertation goes beyond tools for one-to-one communication in the healthcare field. As described earlier in section 1.3.3, the sentiments expressed in seminal papers and by organizations envision interdisciplinary patient-provider partnerships driven by patient values. Collaboration between healthcare professionals with patient input is antagonized by the existing organization of healthcare: expertise is physically-separated by different clinic space, healthcare providers function at different rates per patient and on different schedules, and information is siloed within incompatible institutional record systems. Bafoutsou et al.139

conducted an early review of collaborative tools in business/management, dividing them into four categories: 1) group file and document handling, 2) computer conferencing - defined as a threaded discussion forum, 3) electronic meeting systems - audio and video conferencing for real-time multi-user communication, and 4) electronic workspaces - common space for document storage, online discussion board, address books and sorting functions.

Transposing this nomenclature to healthcare, electronic workspaces, which allow document sharing, threaded discussions and accessibility to anyone involved in the patient’s care and that involve direct communication and information exchange with the patient could significantly foster coordination, continuity and collaboration in the current healthcare environment.

1.4.4 Evidence for effectiveness of online communication tools

The evidence of benefit for communication tools in healthcare has shown variable but promising results through a number of reviews of this area.

Ye et al. (2010)140 systematically reviewed 24 studies of patient-physician communication using email and found that emails were used for medical condition updates, exchange of medical information and subspecialty evaluation. Providers’ use of email with patients varied significantly but was positively associated with being in primary care, coming from larger practices, and being from academic institutions. Patients’ use of email with providers was relatively low despite patients indicating a desire to use it, possibly because of provider reluctance to share their email address.

In a Cochrane review of patient-healthcare provider email use, Atherton et al. (2012)141 found mixed evidence of effectiveness on healthcare utilization and patient outcomes. Two studies showed weak evidence that email use reduced office visits to the GP142,143, and a study from 2003144 showed phone call volume did not decrease with availability of email, and there was inconclusive evidence of impact on patient outcomes. Many of the included studies were from the early 2000’s.

In a parallel Cochrane review, Pappas et al. (2012)145 attempted to review secure messaging tools between healthcare providers, and identified only one randomized controlled trial. The findings were that EMR messaging between providers and reminders improved healthcare provider adherence to treatment guidelines and improved patient receipt of guideline- recommended treatments.146

Walsh et al. (2013)147 reviewed provider-to-provider communication within EMRs finding 25 studies. Studies focused on physicians only. The authors found evidence of an increase in electronic prescribing and higher provider satisfaction associated with the speed of information turnaround with use of these tools.

de Jong et al. (2014)135 more recently reviewed internet-based asynchronous patient- provider communication tools. The review identified 15 studies that broadly looked at interventions ranging from informational websites, peer-support, and discussion boards to facilitated management programs delivered online. Increases in patient self-efficacy, improvement in clinical outcomes and improvement in psychosocial outcomes were observed.

However, the authors commented that results were not uniform and that electronic communication itself was not the focus of evaluation in these studies.

Kruse et al. (2015)148 reviewed 27 studies on the impact of patient portals on improving

quality of care outcomes. Use of portals was associated with higher patient satisfaction, an

increase in patient-provider communication, with only a mild increase in workload.

Improvements were also observed in medication adherence, disease control, and self-efficacy.

The reviewer noted limitations related to the heterogeneity in the quality of studies (including

risk of bias) and variability in selection of outcomes as factors preventing comparison between

studies.

Hanlon et al. (2017)10 conducted a meta-review of systematic reviews of randomized

controlled trials (RCTs) assessing the impact of telehealth interventions for supported self-

management on disease control and healthcare utilization for major chronic diseases. Synthesis

indicated that telemonitoring tools were effective at improving glycemic control, and reduced hospital admissions for heart failure patients across studies. The authors indicate that in

synthesizing effects for other conditions, the results were mixed. Of note, few reviews focused

on cancer, and included studies suggested that internet-based self-help and internet-based

education programs showed no improvements in quality of life or physical/emotional well-being.

In summary, a number of reviews have examined digital health tools for communication

between patients and providers, or between providers. As expected with such a diverse set of

communication modalities, participants, and outcomes, evidence of effectiveness is mixed. There

is also a likely temporal trend: newer reviews which include more recent studies (where

patient/provider comfort with computers/internet may have increased) appear to suggest

increasingly positive evidence regarding the impact of tools on patient outcomes and provider

willingness to use such tools. The continued review of this area is critical as development and

implementation of ever more sophisticated digital health tools becomes mainstay in healthcare.

However, the literature is limited regarding the examination of specific communication

modalities, like text-based communication, over ICTs in general, despite a marked increase in

use between patients and providers.149 It is unclear, in considering tools beyond email and texting

on mobile devices, how such tools are structured, how they function and how they are intended

to be used. As patients view their role in healthcare as more active, providers and the

organizations they work for are expected to respond to increasing demands for patient access and

be more transparent in sharing a patient’s health information with them. Furthermore, there has

been little attention to patient-provider team-based communication in the healthcare context,

which may improve the seamlessness of care across different providers. An early paper by

Househ and Lau (2005)150 reviewed collaborative technologies used by teams of healthcare

providers (but did not involve patients) terming such tools “groupware”. None of the studies

included looked at the effects of groupware on patient outcomes. The authors found that

groupware interventions which existed at the time (i.e. email, teleconference, pagers) could keep

conversations more context-specific, and did support “collaboration” (measured as sharing of data). The authors further indicated that for collaboration to occur, a precondition is text, voice or video communication.151 Given the strong rationale and shortage of research into patient-

provider communication, and especially team-based communication, more investigation is

needed to understand the role and impacts that this new model of communication can have to

address the unique challenges posed in the complex care population.

1.5 Rationale and Conceptual Model

The Chronic Care Model by Wagner et al.152 is an oft-used framework illustrating the

interrelationships between organizational domains in the care of patients with chronic diseases.

The framework recognizes the complexities of care in chronic conditions, and emphasizes that

such care should be situated in the ambulatory setting to acknowledge the ongoing, community-

based support required, over acute care settings which are designed to address emergent needs.

This framework emphasizes the critical role of greater patient activation, prepared team-based

interdisciplinary care, and productive interactions between patients and their healthcare team to

produce improved outcomes. Gee et al.153 adapted the framework to the current environment

where healthcare is invariably affected by health information technology in the eHealth

Enhanced Chronic Care Model (eCCM). The eCCM “incorporates information and

communication technologies in the presence of a complete feedback loop and enables the use of

data and information, to generate health management knowledge and wisdom.”153

The eCCM is depicted in Figure 2. The overarching setting encompasses the community

and the health system, from Wagner’s model, but now includes the eCommunity (such as social

networks and online peer support groups) and eHealth (including the aforementioned tools and

systems) as meaningful components to patient support structures. Within the setting are several

enhancements brought about by health information technology, including clinical information

systems (e.g. EMR’s, patient portals, wearable devices). The revised model is centered on a

complete feedback loop between the patient and the healthcare team, which reinforces

“cooperative effort” as essential to “self-management and productive interaction.” Adapted from

Jimison et al.,154 the complete feedback loop in five stages are: 1) transmission of patient health

34 information, 2) interpretation of data/information using evidence, knowledge and wisdom, 3) addressing needs, 4) timely feedback, and 5) repetition.

Figure 2 eHealth Enhanced Chronic Care Model. Reproduced with permission (see Appendix 1). Gee PM, Greenwood DA, Paterniti DA, Ward D and Miller LMS. J Med Internet Res 2015;17(4)e86, http://www.jmir.org/2015/4/e86/

Technological innovations in clinical practice are always appealing but tend to be utilized before they are adequately studied.155 A theoretical framework which models the expected process and effects of an intervention, such as a digital health tool, can guide selection of outcomes, predict success and identify areas for improvement.156 The eCCM is a macro-level framework that considers the broad role of digital health tools in the chronic care setting, and suggests that a core function of the breadth of digital health tools is to support a complete feedback loop between the patient and their healthcare team.153 Taken as an example of one such digital health tool, a communication tool which facilitates a complete feedback loop between

patients and their healthcare team might enhance patient self-management of chronic conditions, improve patient-provider interactions and foster productive team-based care delivery.154

Adapting this concept to the care of patients with advanced cancer, who exemplify

patients with complex care needs, the implementation of a digital health tool for team-based

communication should improve accessibility to timely healthcare, and address deficits in

continuity of care through interdisciplinary communication and increased patient involvement. A

diagram of this relationship is shown in Figure 3, pg. 37. Currently in Ontario, EMRs lack

interoperability between healthcare institutions, preventing sharing and exchange of patient data,

and, in most circumstances, they are not accessible to individuals outside of those institutions.45

Therefore, a patient-provider team-based communication tool that is standalone, web-based, and intended for use by patients/caregivers, and healthcare providers from all settings and disciplines would bring together otherwise separated units (Figure 3a). For such broad accessibility, the design of this tool would need to adopt a many-to-many communication paradigm using a secure virtual space where all users can post and respond to messages viewable by everyone on the healthcare team. The process (Figure 3b) of posting a question, an update, or request, the corresponding viewing of the message, and the response represents the complete feedback loop intrinsic to the eCCM.

An expected proximal outcome of patient-provider team-based communication is improved continuity of care. The web-based tool could be expected to affect continuity of care whereby the patient, family caregiver(s) and the healthcare providers designated as members of the care team by the patient are able to asynchronously communicate updates, plans, and convey contextual information about management. With a single place for all members of the care team to communicate, informational continuity could be expected to improve because past and current

36 medical information can be shared among providers to tailor care according to what is appropriate for the patient’s personal circumstances. Management continuity could be expected to improve because all providers can get up to speed with the current plan of care and management strategy, such that care can be consistent and coherently delivered among the team.

With the opportunity for a patient to communicate with their providers over time at intervals outside of appointments, the opportunity for dialogue reflective of ongoing support, rather than periodic, formal assessments may therefore improve relational continuity. Collaboration is thus promoted (Figure 3c). Improved continuity of care is associated with distal outcomes such as quality of care and psychological wellbeing,98,157 better management of symptoms,158,159 and reduced health services utilization.100 Reduced symptom distress is also associated with reduced emergency department visits.160 As important consequences of improvement in continuity of care

(as summarized in section 1.3.4), these distal outcomes are clinically-important in the context of advanced cancer. Also, these outcomes may be recognized more tangibly by patients, and appreciated more broadly by stakeholders as sequelae to improved continuity.

37 Figure 3 Proposed eHealth solution to improve continuity of care a) Web -based tool allowing a patient/caregiver, their providers at the cancer center/hospital, and providers outside of the hospital setting to post and respond to messages in a secure, private virtual space

b) Proposed process of communication demonstrating the complete feedback loop: 1) transmission of information, 2) interpretation 3) addressing needs, 4) timely feedback, and 5) repetition. The expectation is that better communication will enhance team-based care

c) The construct of continuity of care as an anticipated proximal outcome of team-based communication and its association with related clinically-meaningful outcomes in the advanced cancer setting, as justified in the text

1.6 Purpose and Study Objectives

The purpose of this dissertation is to examine digital health tools for patient-provider team-based communication, their feasibility in practice and role in improving continuity of care.

This is addressed through three studies. The first study is a scoping review of digital health tools for web-based, patient-provider, text-based communication. This will provide an understanding of what tools have been studied to date. The second study is a feasibility trial of a web-based communication tool with the intended purpose of promoting patient-provider team-based care, as described in section 1.5, and its effect on continuity of care and other outcomes. The third study is a qualitative descriptive study with patients, caregivers and cancer physicians involved in the trial regarding their perspectives on their experience with and the value of web-based communication in the healthcare context. It serves to provide contextual support to understand the findings of the trial, as discussed in Chapter 5, Discussion.

Digital health tools are a form of complex intervention. Complex interventions “comprise a number of separate elements which seem essential to the proper functioning of the intervention although the ‘active ingredient’ of the intervention that is effective is difficult to specify.”161 As such, there is growing recognition that the use of and successful implementation of digital health tools requires an understanding of the interrelationship of technology with human/social factors in addition to empirical, objective study to understand their multifaceted nature.162

Sociotechnical evaluation is such an approach which aims to study processes, benefits and impacts of a new system, and employs multiple methods (including quantitative and qualitative methods) to understand organizational impacts, participant attitudes and experiences.163 The second and third studies, related to the evaluation of a digital health tool, constitute a sociotechnical evaluation involving a multi-method evaluation paradigm.164

The objectives and methodological considerations of each study, beyond what is

presented in subsequent chapters, are detailed in the following sections.

1.6.1 Scoping review (Chapter 2)

Objective: 1) To conduct a systematic search of the published literature and the internet for web-

based tools for text-based communication between patients and physicians in the chronic disease

context, 2) map tool characteristics, their intended use, contexts in which they were used and by

whom, 3) describe the nature of their evaluation, and 4) understand the terminology used to

describe tools and index articles.

Study Design: According to the Rationale presented in section 1.5, a web-based tool for text- based communication among a patient, caregiver(s) and healthcare providers may positively impact continuity of care. However, as discussed in section 1.4.4 further characterization focused on web-based tools for text-based communication is warranted to understand how common such tools are, what form they take, how they have been used, in what contexts they have been studied and for what purpose.

With the exponential growth in number of publications in the field of eHealth, efforts to synthesize the literature have begun to take several forms reflecting differing needs and goals.

The scoping review methodology proposed by Arksey and O’Malley165 was chosen to address the goals of the first study objective. Scoping reviews: “map rapidly the key concepts underpinning a research area and the main sources and types of evidence available.”166 Arksey

and O’Malley suggest that this may manifest as aims to: 1) examine the “extent/range/nature of

research activity” and type of evidence; 2) “determine the value of undertaking a full systematic

review”; 3) “summarize and disseminate findings” to inform practice, policy-making and research; 4) “identify research gaps/[key concepts] in the existing literature…and draw conclusions regarding the overall state of research activity”.165

While the purpose of a systematic review is to “sum up the best available research”;

scoping reviews “present an overview of a potentially large and diverse body of literature”.167

Scoping reviews are appropriate when little is known about a topic or the literature is

heterogeneous. Systematic reviews specify selection criteria for particular study designs and outcomes, and often make assessments of study quality. The product of a scoping review is typically descriptive in nature and does not involve appraisal of study quality or claims of effectiveness.

1.6.2 Feasibility trial (Chapter 3)

Objective: To evaluate the feasibility of implementation and preliminary effectiveness of a web- based tool for team-based communication on continuity of care, quality of care, health services utilization and symptom distress relative to no intervention in patients with advanced cancer.

This was accomplished in the second study through an evaluation of a patient-provider

team-based communication tool called “Loop”. A description of the Loop tool as it was

implemented is presented in Study 2 (Chapter 3).

Intervention: Loop is a web-based tool for non-urgent, clinical communication between a

patient, their caregivers and the healthcare providers involved in their direct care. It is a tool for

patient-provider team-based (“many-to-many”) communication. Loop provides a secure online space for unstructured, asynchronous communication among those members who are a part of

the space (a patient’s Loop). Each patient’s Loop is partitioned from the Loop of other patients

such that a patient cannot be a part of another patient’s Loop. As electronic medical records

(EMRs) have yet to be integrated across institutions, Loop functions as a standalone tool,

accessed online from any web browser, in order to fulfill the purpose of facilitating

communication across institutions, settings and disciplines.

The tool was previously developed, with a user-centered participatory design approach

engaging end-users (patients, caregivers and healthcare providers) throughout its development

process.168 Beginning with end-user/stakeholder consultation, needs assessments, ethnographic

study, followed by prototyping, and usability and beta-testing, the development approach has been iterative in nature.

The intended purpose of the tool is to encourage interdisciplinary team-based

collaboration– for all Loop members, including healthcare providers, patient, and caregivers, to

engage in shared goal setting and care planning. By connecting the patient and their healthcare

providers, the tool should connect individuals from across the settings from where the patient

receives care, and also across the healthcare events and phases that the patient has experienced.

The purpose is reflected in the structure and function of the tool. The tool adopts a

patient-centered view, whereby the patient and their caregivers can engage with all others on the

tool at the same time. Healthcare provider members consist of those providers involved directly

in care by the patient. This may include those outside the traditional silos of a healthcare setting,

or disease-based care. Only individuals involved in provision of care, as decided by the patient,

can join the patient’s Loop. Patients can share updates with the care team between visits and

providers can corroborate information with other providers. Providers can thus be consulted with

relative ease and actively take part in care planning where they would not have before.

Patients create a profile which includes demographic information (see Chapter 3 Figure

1). The key elements of the tool169 are:

1) Text-based messages can be composed and posted to the Loop, and responded to, such that messages are organized by conversation.

2) Healthcare providers can post messages to other healthcare providers, using a “team only” feature, which is not visible to the patient and caregiver(s). The healthcare provider view allows them to view all patients whose Loops they are team members of, and access each one individually.

3) Messages can be labelled with tags to organize and filter conversations. This might include tagging by symptom or medical issue, for example.

4) Using an “Attention to” feature, individuals can be alerted via email to a posted message.

5) Messages are indefinitely viewable on the patient Loop while the patient is active on the system. Audit trails of user log-ins, views of a patient Loop and invitations to join Loop are available for research and maintenance purposes.

Study Design: The Medical Research Council (MRC) Framework for the Evaluation of

Complex Interventions is a widely-adopted and broadly-applicable guide to the longitudinal study of interventions. In 2000, the MRC suggested a sequential approach to evaluating complex interventions beginning with preclinical/theoretical and modelling/phase I development, exploratory trial/phase II, definitive trial/phase III, and long-term implementation/phase IV.170 In

2008, the framework was revised to a circular model reflecting the need for iterative and overlapping development, piloting, evaluation and implementation phases.171

As part of the continuous, systematic evaluation162 of the Loop tool, this second study is a

feasibility RCT examining feasibility of implementation of this tool along with preliminary

measures of effect. The data from this trial is expected to inform the success of implementation

within the advanced cancer patient context, and inform the design of future studies with a

mandate of evaluating effectiveness. A sample size reflective of typical pilot/feasibility trials of

50 participants across both study arms was selected. The hypothesized mechanism of action of

the Loop tool’s design on the expected effects was outlined in section 1.5.

RCTs are a type of study design which aims to maximize internal validity. By

randomizing participants to a study arm (i.e. intervention or control group), known and unknown

factors that could potentially confound the association between exposure and outcome may be controlled for, and selection bias is reduced.172 Drug therapies are required by regulatory bodies

like the Food and Drug Administration to undergo RCTs to establish effectiveness. Frequently, it

is expected that the same level of rigor is adopted in the evaluation of other types of

interventions, including those designated as complex.173 Elements such as blinding participants

and outcome evaluators, strict eligibility criteria, and prescribed implementation of the

intervention aim to minimize bias. However, the tradeoff of these designs is that the stringency

in design also limits their real-world applicability, or generalizability.162,174 More commonly,

complex interventions are adopting pragmatic approaches to RCT design.175 With broader

participant selection criteria, a wider variety of study settings, less restrictive intervention

delivery and expectations of adherence, and selection of outcomes that are relevant to

participants, pragmatic designs address the limitation of generalizability that is commonly

associated with RCTs. Trials can therefore fall along a continuum of explanatory to pragmatic as

different aspects of design are adjusted to reflect methods aimed at determining efficacy (true

effect captured in a tightly-controlled environment) or effectiveness (real-world effect).176

In this feasibility trial, a pragmatic design was adopted, namely at the levels of participant

selection, practical value of the study outcome to participants and in flexibility of implementing

the intervention; no expectations around use were prescribed.

1.6.3 Qualitative study (Chapter 4)

Objective: To explore trial participant perceptions of the Loop tool with the overarching goal of

understanding the value of patient-physician communication tools in the advanced cancer context.

Study Design: This qualitative study was conducted with participants of the intervention arm of the trial (study 2). Conducted as a concurrent nested study,177 the study reflected a

complementary but distinct purpose to that of the trial, seeking to understand participant attitudes

towards and experiences of using the tool. The study employed a qualitative descriptive

approach, analyzing data using thematic analysis.178,179 Qualitative description is a method of

qualitative research that, “[produces] findings [that are] closer to the data,” unlike

phenomenology, which seeks to understand participant experiences of an event/phenomen, or

grounded theory, which is a systematic method of analysis predicated on the emergence of

themes to formualte theoretical understanding.180,181 However, like all qualitative methods,

qualitative description still embraces an interpretive lens, and is not “stripped of [theory]”.182 In

this study, we drew on principles outlined by the Technology Acceptance Model (TAM) to

inform the interview guide.183,184 The TAM postulates that the use of a new technological

intervention by end-users is predicted by acceptance (“intention to use”), and acceptance is

predicted by perceived usefulness (“value”).183,184 Within the trial, this qualitative study sought

understanding of the value of the tool to participants, as a means to shed light on participant

acceptance of patient-provider communication tools. The study was guided by the assumption

that the Loop tool may make clinical care more patient-centered (as discussed in section 1.3.3).

The final chapter of this dissertation presents the overarching conclusions drawn from these studies with interpretation in the context of the rationale presented in section 1.5, the Reid,

Haggerty et al.4,74 definition of continuity of care, and the notion of team-based care. Findings

are reviewed in relation to the existing literature, specific contributions and implications of this

research are discussed, and proposed future directions are considered.

CHAPTER 2: SCOPING REVIEW

TITLE: A Scoping Review of Web-Based Tools for Patient-Provider, Text-Based Communication in Chronic Conditions

Author(s): Teja Voruganti, Eva Grunfeld, Tutsirai Makuwaza, and Jacqueline L. Bender

A version of this paper has been published: Voruganti T, Grunfeld E, Makuwaza T, Bender JL. Web-Based Tools for Text-Based Patient- Provider Communication in Chronic Conditions: Scoping Review. J Med Internet Res 2017;19(10):e366

Key Words: Text-based communication Secure messaging eHealth Digital health tools Patient-physician communication Complex conditions Self-care Chronic conditions Team-based communication

MeSH Terms: Internet Telemedicine and Telecommunication Chronic diseases Physician-Patient Relations Communication Electronic Mail Text messaging Patient Portal Patient Care Team Interdisciplinary communication

ABSTRACT

Background: Patients with chronic conditions require ongoing care which not only necessitates

support from healthcare providers outside of appointments but also self-management. Online text-based communication tools, such as secure messaging, allow for sharing of contextual information and personal narrative in a simple, accessible medium, empowering patients and enabling their providers to address emerging care needs.

Objective: Our objectives were to 1) conduct a systematic search of the published literature and the internet for web-based tools for text-based communication between patients and providers, 2) map tool characteristics, their intended use, contexts in which they were used and by whom, 3) describe the nature of their evaluation, and 4) understand the terminology used to describe the tools.

Methods: We conducted a scoping review using the MEDLINE and EMBASE databases. We summarized information on the characteristics of the tools (structure, functions and communication paradigm), intended use, context and users, evaluation (study design, outcomes) and terminology. We performed a parallel search of the internet to compare with tools identified in the published literature.

Results: We identified 56 articles describing 41 unique tools from 11 countries studied in 66 chronic health condition contexts. Tools were most common for diabetes (27%; 18/66), and chronic respiratory conditions (14%; 9/66). Few tools were identified for cardiovascular disease

48 and cancer. The majority of tools (85%; 35/41) had functions in addition to communication (e.g. viewable care plan, symptom diary/tracker). Eight tools (20%; 8/41) were described as allowing patients to communicate with the team/multiple healthcare providers. Most tools were intended to support communication regarding symptom reporting (46%; 19/41) and lifestyle/behavior modification (39%; 16/41). The type of healthcare providers who used tools to communicate with patients were predominantly nurses (29%; 12/41), and physicians (20%; 8/41) among others. Over half (56%; 23/41) of tools were evaluated in randomized controlled trials and eighteen (44%; 18/41) in non-randomized studies. Terminology of tools varied by intervention type and functionality, and did not consistently reflect a theme of communication. The majority of tools found in the internet search were patient portals from six developers; none of the internet findings were also found among published articles.

Conclusions: Web-based tools for patient-provider, text-based communication were identified from a wide variety of clinical contexts and with varied functionality. Tools were most prevalent in contexts where intended use was self-management. Few tools for team-based communication were found but this may become increasingly important as chronic disease care becomes more interdisciplinary.

BACKGROUND:

As the number of individuals living with chronic conditions increases185, the needs of

patients are shifting the delivery of healthcare services based solely on appointments to a patient- driven model which addresses supportive needs on an ongoing basis.186 This is because the

management of chronic diseases often entails a greater degree of patient self-management, supported by a relationship with several providers.56,187,188

Numerous organizations, such as the Agency for Healthcare Research and Quality and

National Academy of Medicine have advocated for the use of digital health technologies to improve the quality of care, pointing to their value in care coordination, enabling patients’ to have greater access to healthcare providers.17-20 Especially in the context of chronic or complex

conditions, such tools can give patients the opportunity to ask questions, refine understanding,

provide updates, and receive test results between appointments. As such, disease self- management may be improved because of timely support from healthcare providers involved in their care.135,189 Research has shown that with provider guidance, treatment adherence and

motivation to be involved in decision-making are improved.190 Furthermore, although much of

the care delivery by healthcare providers is disease-specific or based on medical specialty20,

patients often do not view care in the form of health encounters, but rather as continuous

between their personal life and the healthcare system.75

While much attention has been paid to tools for telemedicine that allow for patients to upload clinical data (like hemoglobin A1C levels or blood pressure values) for the purpose of remote monitoring10,191,192, less is known about tools that facilitate dialogue with healthcare

providers. These tools allow patients to share contextual information, personal narrative and

perspective which are crucial to the therapeutic function of the patient-provider relationship.109

Text-based electronic communication, specifically, has grown in popularity due to its simplicity

and accessibility.193-195 This includes formats such as email, phone-based texting, and secure messaging through web-based online portals. Furthermore, because communication may be asynchronous (users do not have to be online concurrently), tools for text-based communication have the potential to facilitate discussion across multiple healthcare providers, in addition to supplementing dialogue during individual appointments.196,197

As the field of eHealth has rapidly expanded with digital health tools taking on a variety

of configurations, there is a need for more focused study on specific forms of digital health tools.

Recent reviews have broadly examined digital health tools in the healthcare setting for

communication between healthcare providers198,199, in the pediatric context200, and the effect on

health-related outcomes.135,201-205 However, such reviews often limited their inclusion to

randomized controlled trials (which not always be appropriate designs for eHealth evaluation206),

and synthesized the effects across several chronic diseases, which may be misleading because

such measures are often too heterogeneous to be objectively compared. Furthermore, granularity at the level of features, functions and implementation of these interventions is often lacking, with studies instead compromising on depth of description to focus on outcomes.207

Previous reviews have concentrated on text-messaging (“Short Message Service” (SMS)) with mobile phones,208,209 or patient-provider communication via email.140,141 Web-based tools,

by comparison, often have added layers of security (because messages are not stored on local

servers),136 have the capacity to be linked to other electronic health information systems (like an electronic medical record (EMR)), and may have configurations beyond exchange between a

single patient and single provider. Given the potential value of web-based tools for text-based

communication in the healthcare setting, there is a need to identify and document how common

such tools are, what form they take, how they have been used, in what contexts and for what

purpose. Therefore, we undertook a scoping review, as described by Arksey and O’Malley,165 of

the published literature and the internet on web-based tools for patient-provider, text-based

communication. The scoping review approach is suitable for reviews that aim to examine the

extent, range and nature of a topic, identify key concepts in the field, and to identify gaps in the

existing literature167. Scoping reviews are especially useful when little is known about a topic or

a field is broad, and where a formal systematic review (with narrow selection criteria, focus on

study design) may limit what is retrieved. Our specific objectives were to: 1) conduct a

systematic search of the published literature and the internet for web-based tools for text-based

communication between patients and providers, 2) map tool characteristics, their intended use,

contexts in which they were used and by whom, 3) describe the nature of their evaluation, and 4)

understand the terminology used to describe tools and index articles.

METHODS

Review type and process: We conducted a scoping review following the Arksey and O’Malley

framework to identify web-based tools for patient-provider, text-based communication in the published literature and on the internet.165,210 We followed six steps articulated in this

framework: 1) identify the study aim 2) identify relevant studies 3) study selection 4) chart the

data 5) collate, summarize and report results, and 6) expert consultation.165,167

SEARCH OF PUBLISHED LITERATURE

Search strategy: The search protocol is presented in Appendix 2. Given that our target was web- based tools used in healthcare, our search was focused on MEDLINE and EMBASE for articles in the published literature. The search strategy was developed in consultation with an academic librarian with expertise in eHealth using key concepts, keywords and controlled vocabulary. We confirmed the completeness of the search strategy by testing it with seed articles that represent expected articles for inclusion (211-214). We included original studies and captured tools described in editorials and commentaries published up to March 2016. Findings were restricted to those in

English because of limited resources for translation services.

Selection criteria: Following the scoping review methodology,165 screening articles for inclusion was done in two stages: title and abstract review, and full article review. Studies were considered for inclusion if they described a tool that:

1. Supports web-based communication between patients and health professionals for within-

tool communication (i.e. message sent within the tool are responded to using the tool

rather than via phone call, outside the tool environment. For example, educational

website with separate email use outside of the intervention, or non-specific email without

a described web-based interface are not included) (ex. secure messaging, electronic mail

exchange accessed via a website or portal)

2. Uses text-based method for dialogue (conversation/discussion; not exclusively

directed/prompted communication i.e. step-by-step modules; must allow for patient-

initiated contact)

3. Involves communication with patients with chronic condition(s), defined as a condition

that is ongoing or persistent, or requiring complex care, defined as requiring nearly

continuous care or otherwise high healthcare resource utilization, and multiple health care

providers

4. Is used in the healthcare context

5. Is intended for patients and health care providers (physician, nurse, pharmacist, social

worker etc.) to communicate regarding direct patient care (defined as private

communication about care specific to the patient between healthcare provider and the

patient/surrogate (such as a caregiver)), rather than general health advice findable on the

open web. Communication may be guided but not restricted (i.e. patient should have the

opportunity to ask any question)

6. Involves communication between a minimum of one patient and one health care

professional (i.e. at least two end-users)

From the published literature, we excluded:

1. Tools that function for information transfer but not communication (ex. lab results,

telepathology, telemonitoring of vitals/symptoms (heart rate), algorithm-based automated

feedback)

2. Audio/video-based forms of communication that do not include text-based

communication

3. Electronic medical records, patient health data repositories, portals that do not have a

communication component

4. Online support forums, even if they support communication between many patients and

many health professionals

5. Tools for communication exclusively between patients

6. Theoretical or conceptual papers, frameworks, descriptions

7. Offline or native applications (“apps”) for mobile devices (i.e. SMS, texting: those which

are not connected to the internet)

8. Tools to support behavior change interventions in otherwise healthy patients (i.e. without

a chronic condition) (e.g. smoking cessation, diet, alcoholism)

Study identification, selection and data extraction: In the first step of study identification, two

reviewers (TV and TM) independently reviewed retrieved titles and abstracts from MEDLINE

and EMBASE. The reviewers tested agreement on a sample of 100 citations, prior to reviewing

all retrieved citations. Where there was uncertainty, citations were included for full article

review. We hand searched the reference lists of identified reviews for potentially relevant

articles. We reviewed the full texts of articles designated for inclusion or those labelled as

“maybe”. From included articles, two authors (TV and TM) independently extracted relevant information.

The data extraction form was pilot-tested and revised. It is presented in Appendix 4. At each step, where there were disagreements, the senior author (JB) was involved to achieve consensus. We extracted data on 1) article characteristics (i.e. study setting, disease context), 2) tool characteristics- structure (such as medium of communication), functions (i.e. additional components such as viewable care plan), and communication paradigm, 3) intended use, context and users, 4) evaluation (i.e. study design, stage of evaluation, outcomes), and 5) terminology

(i.e. tool label/description and Medical Subject Headings (MeSH) terms used to index studies on

MEDLINE or keywords on EMBASE). With respect to communication paradigm, identification of team-based communication tools findings suggested that several designs of communication flow exist in patient-provider team-based tools.138 Here, we refer to one-to-one communication as exchange between a single user (i.e. patient) and another user (i.e. provider). One-to-many communication refers to exchange between a patient and multiple providers (for example, a tool which enables multiple, separate communication threads). Many-to-many communication allows multiple users to communicate amongst each other, such as in online forums. In this context, a many-to-many communication tool could allow a patient to communicate with multiple providers and all users the opportunity to view and respond to messages.

INTERNET SEARCH

Internet search strategy: The search of the published literature was supplemented with an internet search using Google.com on September 16, 2016 to identify tools that are used but may not have been evaluated or published. Five search queries composed of keywords and Boolean operators were created with the help of the same academic librarian who guided the search of published articles. The first 100 retrieved search results for each query were examined. The same inclusion/exclusion criteria that was used for the published literature was applied to the Google search results, except that we did not exclude findings to tools for chronic diseases because such detail was lacking on most websites.

Selection criteria, selection process and data extraction: The internet search protocol is

presented in Appendix 3. In the first step, the initial page accessed from the search result was

examined. If it appeared relevant or mentioned a tool, it was included. At this stage, search

results that led to published primary research articles from an academic database were excluded,

as were theoretical or conceptual papers, or those not from the healthcare context. In the second

step, if a search result linked to a specific tool, the website was explored for further information

about communication tools that could be used for a patient/caregiver to communicate with a

healthcare provider. Data extraction involved exploring the search result and directly-linked (one step away) websites for additional information. We modified the data extraction form used for published literature to reflect the lack of detail typically available on websites (presented in

Appendix 4). Two authors (TV and TM) reviewed 20% of search results to establish consistency in extraction, and then the first author (TV) extracted the remaining data.

Synthesis: Data extracted from published articles and the internet search was summarized

separately. A coding framework was iteratively developed by the reviewing authors (TV and

TM) to categorize extracted data according to pre-specified definitions based on the published

literature or white papers (for example, the Cochrane Collaboration definitions of various study

designs215), common patterns observed in the data, and expert consultation (JB). The coding

framework is presented in Appendix 6.

RESULTS

The search of published literature retrieved 6443 results from MEDLINE (n=4296) and

EMBASE (n=2147). After removal of duplicates (n=1756), 4687 titles and abstracts were

screened. Forty-three review articles were identified, of which 19 were hand-searched for articles meeting the selection criteria. From 4784 records, the full text of 221 articles were reviewed and

56 articles were included (see Figures 1 and 2).

Article Characteristics

Of the 56 articles, there were 55 unique studies describing 41 unique tools (after accounting for multiple articles per tool). The earliest article identified was published in 2002.

As shown in Figure 2, the number of published articles on this topic has been increasing annually. The majority of articles were from the USA (45%; 25/56) (see Table 1). Most studies were conducted at outpatient clinics (69%; 38/55), though a large number were from the primary care setting (29%; 16/55). Only four studies (7%; 4/55) were conducted in exclusively pediatric populations (<18 years old).

Tool Characteristics

Characteristics of tools from published articles are organized according to tool structures, functions and communication paradigm, presented in full in Table 2 (by characteristic) and Table

3 (by study).

Structures

Of 41 tools identified, the majority (81%; 33/41) were exclusively web-enabled

applications, while 8 (20%; 8/41) were hybrid applications involving web and an internet-

connected software/app. Most (83%; 34/41) were multidimensional tools with multiple features

and functions, of which 34% (14/41) were part of an informational/educational website and 49%

(20/41) were patient portals; 17% (7/41) were standalone communication tools.

Functions

Two categories of communication functions were identified: unstructured and structured

text-based communication. The majority of tools (85%; 35/41) involved unstructured text-based

communication which allowed a patient to enter open-ended free text. Conversely, 6 tools

involved structured communication whereby a patient would submit an inquiry into a form with

structured fields, which returned a response to questions (tools with automated responses were

excluded). The majority of tools (88%; 36/41) had other functions in addition to the

communication component, including disease information/education (63%; 26/41), symptom diary/tracker (59%; 23/41) and viewable care/treatment plans (29%; 12/41).

Communication Paradigm

The majority of tools (93%; 38/41) used asynchronous communication of which 7

specified that healthcare providers were to respond in a specified amount of time (i.e. within 3

days). With most tools (81%; 33/41), patients could communicate with one specific healthcare

provider (i.e. one-to-one communication). Only 20% (8/41) of tools were described as allowing

the patient to communicate with their healthcare team/multiple healthcare providers. These were

evaluated in the diabetes (3/8), respiratory conditions (1/8), HIV (1/8), depression (1/8) and

general outpatient (1/8) contexts. Of these, one tool clearly described having patient-

provider/interprofessional communication functionality (i.e. many-to-many communication) in

patients with cerebral palsy. Other tools (50%; 4/8) were vague about whether the patient could

59 communicate with all providers simultaneously such that messages were viewable to the entire team, or whether messages were exchanged as individual threads (akin to email). At least one tool description suggested that messages were triaged by a moderator who conveyed messages to the team. Eighteen tools (44%; 18/41) described allowing the patient to communicate with their

“own provider” (presumably, someone involved in their direct care).

Intended Use, Context, Users

The intended use of tools described in articles were grouped into four categories:

Symptom Reporting (46%; 19/41), Lifestyle/Behavior Modification (39%; 16/41), and Care

Planning (5%; 2/41). No intended use was stated in the articles for four tools though these were in non-randomized studies where the tool was not evaluated as an intervention.

Studies were conducted in several different chronic disease populations, with many studies evaluating tools in multiple disease contexts. In total, the studies covered 66 health conditions. Notably, 27% (18/66) were evaluated for diabetes and 14% (9/66) for chronic respiratory conditions. Few studies were evaluated for cardiovascular disease (CVD) (8%; 5/66) and one tool was evaluated in the context of cancer in seven studies.

The type of healthcare provider who used the tool varied greatly: 29% (12/41) were used by nurses, 20% (8/41) by physicians, and 20% (8/41) involved health professionals of various disciplines (see Table 2). Only 2 studies mentioned that providers were given monetary compensation for tool use.

Evaluation Characteristics

Study Design and Study Stage

The evaluation characteristics of completed studies (i.e. excluding protocols) are reported

in Table 4. Twenty-five studies were RCTs. Twenty-six were non-randomized studies, of which

9 were prospective cohort studies, 4 were retrospective cohort studies, 4 were quasi- experimental/non-randomized controlled trials, 1 was a cross-sectional study, 1 was a cost- effectiveness study and 7 were qualitative studies. All were real-world evaluations, and not in a laboratory setting. Regarding stage of study according to the 2008 MRC Framework for the

Evaluation of Complex Interventions171, 88% (22/25) of RCTs were at the evaluation stage

compared to 23% (6/26) of non-randomized studies. The only studies at the implementation

stage were non-randomized studies (42%; 11/26). The sample size of RCTs ranged from 15 to

415 patients and spanned 1 to 20 months of follow-up. By comparison, the sample size of non- randomized studies ranged from 2 in a standalone qualitative study, to 14102 in a retrospective analysis of administrative cohort data.

Study Outcomes

Regarding the types of results/outcomes captured (see Table 4 and Appendix 7 for

details), RCTs (n=34 outcomes measured) tended to focus mostly on clinical outcomes (71%;

24/34) (e.g. cholesterol reduction, depression symptoms, patient activation) while non-

randomized studies (n=41 outcomes measured) examined outcomes related to experience (24%;

10/41), acceptability (10%; 4/41), and usage (15%; 6/41) more often. Experience-related

outcomes (e.g. perceptions, open-ended feedback) were not captured in RCTs; however, they were captured in non-randomized studies either as stand-alone qualitative studies (12%; 5/41) or

as part of a study capturing quantitative and qualitative outcomes (15%; 6/41). Usage data was

reported in only 24% (6/25) of RCTs.

Terminology

The terminology used to describe the tools was explored in published articles by

examining author descriptions of the tool and the terms used to index the articles by academic

librarians. “Portal” was often used to describe tools with more than three additional functions

(40%; 8/20). Of studies where the communication component was the primary feature, “web-

based” (29%; 8/28) and “internet-based” (18%; 5/28) were frequently used as adjectives in intervention descriptions. However, the actual intervention descriptors varied considerably (i.e. diaries, self-management intervention etc.). Regarding the indexing terminology of articles, the

MeSH terms Internet (n=32), Telemedicine and Telecommunication (n=7), Physician-Patient

Relations (n=8), Cell Phones (n=6), and Electronic Health Records/Medical Records (n=5)

appeared 5 or more times.

Internet Search Results

The internet search identified websites for 63 unique tools, 82.5% (52/63) of which were

identified from healthcare institution websites (hospitals, care networks), and 17.5% from

businesses (including tool developer companies) (see Table 5). None of the tools identified on

the internet were also found in the published literature. The majority of healthcare institution-

based tools came from six developers/companies: FollowMyHealth (19%; 10/52), Athena Health

(15%; 8/52), MyChart Epic Systems (15%; 8/52), eClinicalWorks (11.5%; 6/52), NextGen

Healthcare Information Systems LLC (10%; 5/52), and Cerner IQ Health (8%; 4/52). Most

(94%; 59/63) websites described their tool as having a communication component integrated

with an electronic health record. Most websites (84%; 53/63) also reported that their tool allowed

the patient to communicate with one healthcare provider, 11 (17.5%; 11/63) of which stated in

the description that patients could talk with their “own provider” directly. Two websites

described tools that allowed patients to talk with multiple healthcare providers. Of 60 tools

(95%; 60/63) that used asynchronous text based communication, only 8 (13%; 8/63) of the

websites stated that a response from a provider could be expected within a specified time frame

(i.e. 3-5 days).

DISCUSSION

In this scoping review, we found 56 published articles that described text-based patient-

provider communication tools for chronic diseases. These tools were predominantly web-based

and mainly functioned as part of a multifunction platform such as patient-facing portals. Few tools enabled patients to communicate with multiple healthcare providers at the same time. Tools were used for lifestyle/behavior modification, symptom reporting, care planning, and medication adherence purposes. We found that the majority of tools were studied in the diabetes and chronic respiratory condition contexts. Around half of the studies were RCTs that focused on clinical outcome evaluations while non-randomized studies examined impact on outcomes such as experience and usability. Terminology used to describe the tools varied greatly by intervention type and functionality, and did not consistently include the theme of communication. The internet search results did not show overlap with tools found in the search of published articles and tools found on the internet were primarily produced by a small number of developers.

We found many tools that facilitated both communication and sharing of data. Most

studies (89%; 36/41) described tools with capabilities beyond communication such as access to

electronic health records, lab/test results, and care/treatment plans, among others. Because of the

shared infrastructure, platforms for communication can easily accommodate components for

information sharing (e.g. lab test results) to allow for more productive interaction. Building on

Wagner’s Chronic Care Model152 which delineates organizational domains needed to support

patient self-management and interaction with the healthcare team, the eHealth Enhanced Chronic

Care Model (eCCM) by Gee et al.153 re-envisions chronic care management as reinforced by the

breadth of digital health technologies. The eCCM postulates that the sharing of data and

information in different ways, and facilitated by technologies, can enhance patient and provider

knowledge and wisdom, making communication between patients and healthcare teams more

productive. Therefore, multifunction platforms may make communication more informed

through added access to medical data.

The growing recognition that care of chronic conditions is rooted in self-management has also been met with a parallel shift in the role of healthcare providers from experts to collaborators with patients.189 We identified 8 tools that allowed patients to communicate with

multiple healthcare providers (described as “communicating with their team”). Only one tool216

clearly described that it facilitated patient-provider and interprofessional communication (i.e.

many-to-many communication). Other tools descriptions were unclear as to the communication paradigm, though at least one tool217 description suggested that a moderator triaged sent by the

patient to the team.

Here, we found that nurses were most often the provider who used the communication

tool with patients (29%; 12/41). Twenty percent (8/41) of tools were described as involving

patient communication with individuals of one of several different professions (i.e. a nurse,

physician, social worker etc.) suggesting that patients are not necessarily in direct contact with

their own physician. The importance of patient-provider team-based tools may be magnified in

contexts where multiple providers are responsible for different aspects of care, and where

provider decisions can benefit from the insight of other providers. Tools for collaboration are not

novel139; in business, collaborative platforms, such as Microsoft’s Yammer©, Slack©, and

Hipchat©, which facilitate synchronous (such as live video), asynchronous individual and group-

based communication and data exchange with multiple users are prevalent218. Traditionally, responsibility for patient care transfers from physician to physician according to disease or treatment modality, and therefore tools for asynchronous collaborative communication may be better suited in healthcare.219 However, lack of financial compensation for physician consults

(including group-based interactions) and concerns about security of data are significant barriers to the use of information and communication technologies for physicians to communicate with each other about a case and with patient directly220 and may partly explain the dearth of tools for

teams. Only two articles221,222 identified here from the literature, and none from the internet-

based search, mentioned compensation for healthcare provider tool use.

Our findings indicate that the number of studies of patient-provider, text-based

communication tools has increased in the last decade for purposes related to self-management and for many conditions, pointing to the broadening appeal of this communication medium. We found that tools for certain chronic conditions with high prevalence were most common but found few tools for several less common conditions (e.g. cerebral palsy, cystic fibrosis). Notably, we found few tools for other common chronic conditions such as CVD (10%; 4/41) and one for cancer. This pattern could be reflective of the type of care associated with these conditions: for typical cases of diabetes223 and respiratory conditions such as asthma224, care protocols usually

emphasize supported self-management. Though CVD also entails a degree of self-management, our findings could suggest that dialogue with a provider is less necessary. Instead, it can be substituted with telemonitoring (e.g. cardiac telemetry, blood pressure monitoring), which are

part of usual CVD care.225,226 These conditions also make use of specialized diagnostic and

treatment protocols which involve different professions. As such these conditions may benefit

from tools allowing for patient-multiple provider communication to address complex needs.

However, none of the patient-multiple provider communication tools found here were from the

CVD and cancer contexts, and could suggest a potential gap.

Evaluations of effect of the identified tools tended to adopt RCT designs (n=25) where

outcomes were clinical while non-RCTs were more inclusive in capturing implementation outcomes. We found, however, that usage data was poorly reported across studies of all designs.

Usage data, as a measure of process, is critical to understanding why an intervention has functioned in a particular context because it provides insight into which components of an intervention were used and may be responsible for the observed effect.203 It is therefore

important for appreciating the generalizability of findings in other contexts. Traditional study

designs, like RCTs, may not adequately address the dual goals of unbiasedly ascertaining effect

and sufficiently capturing the practical realities of implementation.162 Furthermore, we

encountered few qualitative studies (14%; 7/51) and mixed methods studies (18%; 9/51), which

are better suited to understanding how the users, setting, and co-interventions in the existing

environment have affected the intervention.227 Novel designs, such as hybrid trials,228 for

evaluating complex interventions like digital health tools have emerged, and incorporate clinical

and process evaluations to better contextualize findings and shed light on the mechanisms of

action.

The terminology used to describe digital health tools presented a challenge for

conducting a review on this topic because of the diversity of terms, and the lack of standardized

vocabulary to label them. We found that the theme of communication was not always reflected in

descriptions or indexing terminology. Multifunction tools were often described as portals while

other tools made use of technology-related adjectives added onto standard intervention terms

(e.g. web-based self-help, e-coaching). Articles were sometimes indexed with MeSH terms that denoted specific functions such as “Patient-physician relations” and “Therapy, Computer-

assisted” or with recognized communication modalities like “Electronic Mail” and “Cell

Phones”. MeSH terms for narrower description such as “Secure Messaging” are lacking,

although “Patient Portal” was newly introduced in July 2016. These patterns reflect the inchoate,

rapidly evolving nature of this field and may indicate that structured taxonomies in eHealth are

yet premature. These findings are also suggestive of the tradeoff in performing searches between

the need for sensitivity to accurately detect articles on interventions of common functionality but

varied design, and specificity of labelling articles with descriptions that are transparent and

replicable. As noted elsewhere about reviewing complex interventions overall, keywords should

attempt to reflect both breadth and depth to maximize capture.229

In performing a parallel search of the internet, we found that most tools were developed by six healthcare software companies. This may speak to the greater internet visibility of those tools produced by companies with the biggest market share. None of the tools found on the

Internet were also found in the published literature search (or vice versa). This could suggest that many commercially-available tools bypass rigorous, research-driven evaluation (or research findings are not shared) in the process of creating a product whose goal is to meet demand rather than understand improvement in health outcomes.230 However, the compromise is that without

research to bolster the theoretical or evidentiary rationale of such products, they may not meet

effectiveness goals, and become defunct. Conversely, tools found in the research literature were

not found publically on the internet, suggesting that research-driven tools often lack the support

needed for iterative development and long-term sustainability if they do not have a commercial/business-driven foundation.

Limitations

The scoping review methodology appropriately pursues breadth in identifying articles with a tradeoff to performing an in-depth study of specific literature. While we aimed to conduct a comprehensive search with an extensive search strategy (using 159 technology-related terms), it is possible that we may have missed some relevant articles given a lack of standardized terminology in this field. We limited our search to MEDLINE and EMBASE because our objectives were health-related and because we found few articles of relevance in other databases

(e.g. CINAHL) while developing the search strategy. Through screening and selection, we did not find tools implemented in the cancer context. While cancer is considered a chronic disease by bodies such as the World Health Organization, it is possible that medical databases have only recently begun to index cancer-related articles within terms such as chronic diseases (we did not base our search protocol on named chronic diseases, which would have limited the contexts in which tools are found). Regarding the internet search, we acknowledge that, as the Google

search engine algorithms are continuously updated, it is unlikely that the internet search is

replicable. However, the purpose of the internet search in this study was to complement and

compare with findings from the published literature rather than report standalone results.

CONCLUSION

We conducted a scoping review of web-based tools for text-based patient-provider communication. In this review, we identified tools for a variety of chronic conditions, the

majority of which targeted diabetes, chronic respiratory conditions and mental health for purposes of updating providers about symptoms or for providers to facilitate lifestyle/behavior change. Our findings seem to suggest that asynchronous text-based patient-provider

communication is increasingly being used to support patient self-management functions for

conditions like diabetes, which, when properly controlled, are amenable to routine online check-

ins. On the other hand, we identified few tools for CVD and cancer, which could suggest that a

different pattern of care for these conditions may not support web-based communication as

much. We found that there were few tools for patient-provider team-based communication,

which will become a growing area of interest to patients, providers, developers, and organizers

of care as care for chronic conditions becomes more interdisciplinary. The terminology used to

describe tools and index articles is widely varied, suggesting that to optimize findability,

researchers need to label articles by both tool characteristics and communication functionality.

Reviewers may still need to cast a wide net to capture potentially relevant tools. The difference

in findings between the search of the published literature and internet could reflect the competing

need for rigorous evaluation and for real-world implementation to both generate revenue for

sustainability and upgrades of tools over time. In an era of healthcare where patients expect

information on demand, the provision of information supplemented by communication with their

providers can enable care when and where a patient needs it, contributing to the betterment of

chronic disease management.

NOTE: Study conclusions for each article identified in the published literature based on primary outcome are presented in Appendix 7. This information is provided for supplementary purposes as a review of outcomes fell outside the purview of this review.

CONTRIBUTIONS TV, EG and JB were involved in study conception. TV, EG and JB were involved in study design. TV created the study protocol. TV and TM screened and reviewed identified studies. TV and JB were involved in synthesizing results. TV drafted the manuscript and all authors contributed to revisions.

ACKNOWLEDGEMENTS We would like to acknowledge Marina Englesakis, the academic librarian who guided development of the search protocol.

T. Voruganti is supported by a Canadian Institutes for Health Research MD/PhD studentship and McLaughlin Foundation fellowship. E. Grunfeld is supported by a clinician-scientist award from the Ontario Institute for Cancer Research and the Giblon Professorship at the Department of Family and Community Medicine.

CONFLICTS OF INTEREST: The authors have no conflicts of interest to declare.

ABBREVIATIONS ICT: Information and Communication Technologies CVD: cardiovascular disease RCT: randomized controlled trial MeSH: Medical Subject Heading

TABLES AND FIGURES Figure 1 PRISMA flow diagram a) Published literature search b) Internet search

a) Published literature search flow diagram

Records identified through database searching MEDLINE (n=4296) EMBASE (n=2147) Total (n=6443)

Total records identified Identification Reviews identified (n=4687) (n=43) (duplicates excluded (n=1756)) Reviews included (n=19)

Articles screened from reviews

Records screened Records excluded

Screening (n=4784) (n=4563)

Full-text assessed for Full-text articles excluded, with reasons eligibility (n=165): (n=221) o Not a web-based tool for within-tool communication (n=38) o Not dialogue between two or more Eligibility individuals regarding patient care Publications (n=54) included in synthesis o Information transfer, telemonitoring (n =56) (n=13) o Not for chronic conditions (n=36) o Patient-to-patient communication (n=5) . Of which, peer-to-peer forum (n=3) o Not a text-based form of communication (n=4) o Theoretical paper (n=6) o Not between patient and healthcare provider (n=7) o Non-internet linked cellphone app (n=2)

b) Flow diagram for internet-based search

Records identified through internet search Google (n= 500) Duplicates removed (n=31)

Identification

Records screened Records excluded

(n=469) (n=350)

 Screening Additional records screened (n=15) Assessed for eligibility (n=3)

Full website assessed Search results excluded, with reasons

for eligibility (n=59):

(n=122) Described elsewhere (n=2) o o Not text-based communication (n=35)

o Did not mention a patient- Eligibility Tools included provider communication (n=63) component (n=13) Not accessible (n=4) o o Information transfer, telemonitoring (n=3)

o Not a web-based tool (n=2)

Figure 2 Published articles by year (n=56)

Publications by Year

10 9

8 7 6 5 4 3 # of Publications 2 1 0

Year

Table 1 Published article characteristics (n=56) Publication country of origin (n=56) – no. (%) Canada 5 (8.9) China 1 (1.8) Finland 2 (3.6) Germany 2 (3.6) Netherlands 2 (3.6) Norway 14 (25.0) Portugal 1 (1.8) Slovenia 1 (1.8) Spain 2 (3.6) Sweden 1 (1.8) USA 25 (44.6) Unique studies (n=55) – no. (%) Original study 51 (92.7) Protocol 3 (5.5) Editorial/Commentary 1 (1.8) Study context/setting of use (n=55) – no. (%) Business (i.e. CVS, Walmart) 1 (1.8) Primary care 16 (29.1) Tertiary care outpatient clinics 15 (27.3) Outpatient (unclear) 23 (41.8) Population (n=55) – no. (%) Adults/all 51 (92.7) Pediatrics (<18 y/o) 4 (7.3)

Disease/clinical area of interest by studies (n=66) – no. (%)a Cardiovascular disease/Stroke 5 (7.6) Cancer 7 (10.6) Chronic respiratory condition (Asthma, COPD 9 (13.6) etc.) Diabetes 18 (27.3) Mental health 5 (7.6) Chronic pain/fibromyalgia 6 (9.1) Other: Dermatology 2 (3.0) Irritable Bowel Syndrome 1 (1.5) Cerebral Palsy 1 (1.5) HIV/AIDS 1 (1.5) Obesity 1 (1.5) Hypertension 2 (3.0) Impaired mobility 2 (3.0) Chronic migraines 1 (1.5) Non-specific (“Chronically ill”) 5 (7.6) aSome studies evaluated the tool in multiple contexts, for example, in diabetes and mental health

Table 2 Tool characteristics, Intended use and Users (n=41)a Structures: Medium of communication/format– no. (%) Website-based tool 33 (80.5) Hybrid web and software application 8 (19.5) Component of another platform– no. (%) Patient portal 20 (48.8) Informational/educational Website 14 (34.2) Standalone 7 (17.1) Functions: Type of communication– no. (%) Unstructured communication (patient-provider free 35 (85.4) form dialogue) Structured communication (guided feedback) 6 (14.6) Number of tools with function(s) beyond patient-provider 36 (87.8) communication component – no. (%) With 3 or more additional functions 20 (48.8) Linked to a health record 10 (24.4) Linked to laboratory/test results 13 (31.7) Linked to appointment/scheduling 7 (17.1) Linked to viewable care/treatment plan 12 (29.3) Linked to new prescription requests 3 (7.3) Linked to prescription renewal 8 (19.5) Linked to symptom diary/tracker 23 (58.5) Linked to disease information/education 26 (63.4) Communication paradigm: Asynchronous tools – no. (%) Asynchronous 38 (92.7) Of asynchronous tools, time-limited 7 (17.1) (response from provider within a specified time window) Synchronous 2 (4.9) Both 1 (2.4) Patient-provider communication flow– no. (%) Patient-to-multiple providers (one-to-many; many- 8 (19.5) to-many) Communication with own provider 4 (9.8) Patient-to-one healthcare provider (one-to-one) 33 (80.5) Communication with own provider 14 (34.1) Of patient-multiple provider tools (n=8), number of many- to-many – no. (%) Yes 1 (12.5) No 3 (37.5) Unclear 4 (50.0) Intended use and Users:

Intended use of communication interventionb– no. (%) Lifestyle/Behavior modification 16 (39.0) Symptom reporting 19 (46.3) Care planning 2 (4.9) Other/Not specified 4 (9.8) Type of healthcare provider intended to use tool with patients/caregivers – no. (%) Nurse 12 (29.3) Physician 8 (19.5) One of several professions (i.e. physician or nurse 8 (19.5) or social worker) Case manager/social worker 3 (7.3) Psychologist 3 (7.3) Therapist/counsellor/dietician 3 (7.3) Not specified 4 (9.8) Other: Compensation to healthcare providers– no. (%) Did not provide compensation 39 (95.1) Did provide compensation 2 (4.9) Uniform Resources Locator (URL) available in article– no. (%) Yes 15 (36.6) No 26 (63.4) aTable classifies variables according to unique tools rather than individual studies as unit of analysis bPurposes are grouped based on descriptions from each paper

Table 3 References by selected tool design and functions Reference Article Medium/ Healthcare Patient- Type of Functions description of format of provider using provider communic in tool communication the tool communi ation addition cation to flow communic ation? 1. Armstrong Online model for Asynchron One-to- et al. follow-up Website-based Physician ous (not Yes one 2015231 management real-time) 2. Riipa et al. Patient- Asynchron 2014232 Physician/ Patient portal Website-based multiple ous (not Yes Riipa et al. Nurse/care team providers real-time) 2014233 3. Lau et al. Patient- Asynchron Physician/ 2014234 Patient portal Website-based multiple ous (not Yes Nurse/care team providers real-time) 4. Ryan et al. Internet-based Interdisciplinar Patient- Asynchron 2013217 suite of Website-based y team of multiple ous (not Yes applications providers providers real-time) 5. Hsiao et al. Secure electronic Patient- Asynchron Physician/ 2011235 messaging Website-based multiple ous (not No Nurse system providers real-time) 6. van der Asynchron Internet-based Website-based One-to- Meer et al. Nurse ous (not Yes self-management tool one 2009236 real-time) 7. Allen et al. Asynchron 2008237 One-to- E-coaching Website-based Nurse ous (not Yes Leveille et one real-time) al. 2009238 8. Nilsson et Information and Hybrid web and Asynchron al. 2006239 Communication One-to- software Nurse ous (not No Technology one application real-time) (ICT) 9. Ross et al. Patient-accessible Asynchron One-to- 2004240 online medical Website-based Nurse ous (not Yes one record real-time) 10. Jones et al. Asynchron One-to- 2015241 Web portal Website-based Psychologist ous (not Yes one real-time) 11. Wayne et al. Smartphone- Hybrid web and Asynchron One-to- 2014242 assisted mobile Nurse ous (not Yes one intervention application real-time) 12. Barberan- Information and Hybrid web and Asynchron Garcia et al. Communication One-to- mobile Psychologist ous (not Yes 2014243 Technology one application real-time) (ICT) 13. Mota Asynchron One-to- Pereira et al. Facebook Website-based Physician ous (not No one 2014244 real-time) 14. Lee et al. Asynchron One-to- 2016245 Facebook Website-based Physician ous (not No one real-time) 15. Nobis et al. Asynchron Web-based One-to- 2013246 Website-based Psychologist ous (not Yes intervention one real-time) 16. Fishman et al. 2013247 Asynchron Harris et al. Shared medical One-to- Website-based Pharmacist ous (not Yes 2009248 record one real-time) Weppner et al. 2010249 17. Zhang et al. Internet of Hybrid web and Asynchron One-to- 2013250 Things software Medical staff ous (not Yes one technology application real-time) 18. Nguyen et Internet-based Asynchron One-to- al. 2013251 collaborative Website-based Nurse ous (not Yes one self-monitoring real-time) 19. Solomon et Asynchron Web-based One-to- al. 2012252 Website-based Unclear ous (not Yes intervention one real-time)

20. Ahmed et al. Asynchron One-to- 2011253 Patient portal Website-based Nurse ous (not Yes one real-time) 21. Brennan et Technology- Asynchron One-to- al. 2010254 enhanced Website-based Nurse ous (not Yes one practice real-time) 22. Sarkar et al. Asynchron One-to- 2010255 Patient portal Website-based Physician ous (not Yes one real-time) 23. Zickmund et Asynchron One-to- al. 2008256 Patient portal Website-based Physician ous (not Yes one real-time) 24. Bond et al. Internet-based One-to- 212 Website-based Nurse Both Yes 2007 self-management one 25. Komives et Asynchron One-to- al. 2005221 Patient portal Website-based Physician ous (not Yes one real-time) 26. Gomez et al. Physician Patient- Asynchron Internet-based 2002257 Website-based Psychologist multiple ous (not Yes self-management Social Worker providers real-time) 27. Gulmans et Web-based al. 2010216 system for Physician Patient- Asynchron patient- Physiotherapist Website-based multiple ous (not Yes professional and School/daycare providers real-time) interprofessional professional communication 28. Oerlemans Cognitive et al. Behaviour Hybrid web and Asynchron Psychologist One-to- 2011258 Therapy with software ous (not Yes one personal digital application real-time) assistant 29. Nes et al. Hybrid web and Asynchron Web-based One-to- 2012259 software Nurse ous (not No diaries one application real-time) 30. Kristjansdot tir et al. 2013260 Kristjansdot tir et al. Asynchron Web-based self- Nurse or One-to- 2013261 Website-based ous (not Yes management physician one Kristjansdot real-time) tir et al. 2011262 Jelin et al. 2012263 31. McMahon et Counsellor Asynchron al. 2005264 Internet-based One-to- Website-based ous (not Yes Fonda et al. care management one Care Manager real-time) 2009265 32. Homko et Internet-based Patient- Asynchron al. 2007266 telemedicine Website-based Unclear multiple ous (not Yes system providers real-time) 33. Ralston et Asynchron Web-based care One-to- al. 2009267 Website-based Care Manager ous (not Yes management one real-time) 34. Tang et al. Asynchron Personal Health One-to- 2013268 Website-based Nurse ous (not Yes Record one real-time) 35. Zutz et al. Nurse/Dietitian/ Synchrono Virtual cardiac One-to- 2007269 Website-based Exercise us (real- Yes rehabilitation one specialist time) 36. Quinn et al. Asynchron Patient web One-to- 2011222 Website-based Counsellor ous (not Yes portal one real-time) 37. Liebreich et Website Asynchron One-to- al. 2009270 counselling Website-based Counsellor ous (not Yes one intervention real-time) 38. Bergmo et Hybrid web and Asynchron Web-based One-to- al. 2009271 software Physician ous (not No consultations one application real-time) 39. Meglic et al. Information and Patient- Asynchron 2010272 Communication Website-based Care Manager multiple ous (not Yes Technology providers real-time)

(ICT)

40. Ruland et al. 2007273 Andersen et al. 2009274 Grimsbo et al. 2012a275 Interactive Asynchron Grimsbo et Health One-to- Website-based Nurse ous (not Yes al. 2012b276 Communication one real-time) Grimsbo et Application al. 2011277 Ruland et al. 2013278 Børøsund et al. 2014279 41. Trautmann Synchrono One-to- et al. Chat Website-based Therapist us (real- Yes one 2008280 time)

Table 4 Evaluation characteristics of unique completed studies (n=51)a Randomized controlled trials (n=25) Is the communication component the primary Primary feature = 20 feature or a supplemental feature? – no. Supplemental feature = 5

Stage of study – no.b Development = 0

Feasibility and piloting = 3

Evaluation = 22

Implementation = 0

Type of result(s) captured in each study– no.c Acceptability = 0

Clinical = 24

Usability = 3

Feasibility = 1

Usage = 6

Sample size– median (IQR;range) 121 (63-167; 15-415) Study length of follow-up in months– median 11 (3-12;1-20) (IQR;range) Non-randomized studies (n=26) Prospective cohort studies (n=9) Is the communication component the primary Primary feature = 7 feature or a supplemental feature? – no. Supplemental feature = 2

Stage of study – no.b Development = 0

Feasibility and piloting = 6

Evaluation = 2

Implementation = 1

Type of result(s) captured in each study– no.c Acceptability = 2

Clinical = 5

Experienced = 3

Feasibility = 3

Usability = 4

Usage = 2

Sample size– median (IQR;range) 24 (15-74;6-222) Study length of follow-up in months – median 6 (5.3-8;1-13) (IQR;range) Retrospective cohort studies (n=4) Is the communication component the primary Primary feature = 1 feature or a supplemental feature? – no. Supplemental feature = 3

Stage of study – no.b Development = 0

Feasibility and piloting = 0

Evaluation = 1

Implementation = 3

Type of result(s) captured in each study– no.c Clinical = 2

Usage = 3

Sample size– median (IQR;range) 2603 (1750.75-5718.5;157- 14102) Study length of follow-up in months – median 13.5 (10.5-17.25;6-24) (IQR;range) Quasi-experimental/non-randomized controlled trials (n=4) Is the communication component the primary Primary feature = 4 feature or a supplemental feature? – no. Supplemental feature = 0

Stage of study – no.b Development = 0

Feasibility and piloting = 1

Evaluation = 3

Implementation = 0

Type of result(s) captured in each study– no.c Acceptability = 1

Clinical = 4

Usage = 1

Sample size– median (IQR;range) 141 (93.25-348.75;46-876) Study length of follow-up in months– median 9 (6-14.5;6-22) (IQR;range) Cross-sectional/Survey (n=1) Is the communication component the primary Primary feature = 1 feature or a supplemental feature? – no. Supplemental feature = 0

Stage of study – no.b Development = 0

Feasibility and piloting = 0

Evaluation = 0

Implementation = 1

Type of result(s) captured in each study– no.c Acceptability = 1

Feasibility = 0

Usability = 0

Sample size– median (IQR;range) 4510 Study length of follow-up in months– median N/A (IQR;range) Cost-effectiveness analysis (n=1) Is the communication component the primary Primary feature = 1 feature or a supplemental feature? – no. Supplemental feature = 0

Stage of study – no.b Development = 0

Feasibility and piloting = 0

Evaluation = 0

Implementation = 1

Type of result(s) captured in each study– no.c Costs/clinical = 1 Sample size– median (IQR;range) 778

Study length of follow-up in months– median 12 months (IQR;range) Qualitative study (n=7) Is the communication component the primary Primary feature = 6 feature or a supplemental feature? – no. Supplemental feature = 1

Stage of study – no.b Development = 0

Feasibility and piloting = 2

Evaluation = 0

Implementation = 5

Type of result(s) captured in each study– no.c Clinical = 2

Experienced = 5 Sample size– median (IQR;range) 39 (8.5-60;2-60) Follow-up (yes)– no. 6 Study length of follow-up in months– median 10 (3.5-15;1-15) (IQR;range) aRefers to unique studies, counting studies resulting in multiple publications. Excludes protocols and editorials/commentaries bDefinitions according to 2008 MRC Framework for Evaluation of Complex Interventions. See coding framework for elaboration cAll types of results (outcomes) in a study are counted so that multiple outcomes may be counted from individual studies dThree studies captured qualitative results as secondary outcomes. Three studies were standalone qualitative studies

Table 5 Tools identified from internet search (n=63) Organization Type– no. (%) Healthcare Institution (i.e. hospitals, care 52 (82.5) networks) Business (i.e. tool developers) 11 (17.5) Health record integration – no. (%) Yes 59 (93.7) No 3 (4.8) Unclear 1 (1.6) Target population– no. (%) Outpatients 47 (74.6) Inpatients 0 (0) Both 8 (12.7) Not specified/Unclear 6 (9.5) Healthcare provider intended to use tool with patients/caregivers as described (excluding business tools) – no. (%) “Members of the healthcare team” 11 (17.5) “Doctor's office” 18 (28.6) “Physician” 5 (7.9) “Nurse” 2 (3.2) “Provider” 11 (17.5) Unclear 4 (6.3) Asynchronous tools– no. (%) Asynchronous 60 (95.2) Of asynchronous tools, time-limited (response 8 (12.7) from provider within a specified time window) Unclear 3 (4.8) Synchronous 0 (0) Patient-provider communication flow– no. (%) One-many– no. (%) 2 (3.2) Communication with own provider – no. (%) 0 (0) One-one– no. (%) 53 (84.1) Communication with own provider – no. (%) 11 (17.5) Unclear– no. (%) 8 (12.7) Product names of healthcare institution tools (n=52) – no. (%) Athena Health 8 (15.3) Beth Israel Deaconess Medical Center 1 (1.9) Carolinas Healthcare 1 (1.9) Cerner IQ Health 4 (7.7) eClinicalWorks 6 (11.5) FollowMyHealth 10 (19.2)

IASIS Healthcare 1 (1.9) Intermountain Healthcare 1 (1.9) MedFusion- Greenway Health 1 (1.9) MyChart Epic Systems 8 (15.4) NextGen Healthcare Information Systems LLC 5 (9.6) Partners HealthCare 1 (1.9) RelayHealth 2 (3.8) University of Wisconsin- Madison 1 (1.9)

CHAPTER 3: FEASIBILITY TRIAL

Title: Feasibility Randomized Controlled Trial of a Web-based Communication Tool for Collaborative Care in Patients with Advanced Cancer

Authors: T Voruganti, E Grunfeld, T Jamieson, A M Kurahashi, B Lokuge, M K Krzyzanowska, M Mamdani, R Moineddin, and A Husain on behalf of the Loop Team

A version of this article has been published: Voruganti T, Grunfeld E, Jamieson T, Kurahashi AM, Lokuge B, Krzyzanowska MK, Mamdani M, Moineddin R, Husain A. My Team of Care Study: A Pilot Randomized Controlled Trial of a Web-Based Communication Tool for Collaborative Care in Patients With Advanced Cancer J Med Internet Res 2017;19(7):e219

Key Words: Team-based care Secure messaging Clinical collaboration eHealth evaluation

MeSH Headings: Internet Professional-Patient Relations Interdisciplinary Communication Neoplasms Adult Chronic disease Continuity of Patient Care Patient Care Team Communication Outcome Assessment (Health Care)

ABSTRACT

Background: The management of patients with complex care needs requires the expertise of

healthcare providers from multiple settings and specialties, and as such there is a need for cross-

setting, cross-disciplinary solutions that address deficits in communication and continuity of

care. We have developed a web-based tool for clinical collaboration, called Loop, which

assembles the patient and care team in a virtual space for the purpose of facilitating

communication around care management.

Objective: The objectives of this study were to evaluate the feasibility of integrating a tool like

Loop into current care processes and to capture preliminary measures of the effect of Loop on

continuity of care, quality of care, symptom distress, and healthcare utilization.

Methods: We conducted an open-label cluster randomized controlled feasibility trial allocating

patients with advanced cancer (defined as stage III or IV disease) with ≥3 months prognosis,

their participating healthcare team and caregivers to receive either the Loop intervention or usual

care. Outcome data was collected from patients on a monthly basis for three months. Trial

feasibility was measured with rate of uptake, as well as recruitment and system usage. The

Picker Continuity of Care subscale, Palliative care Outcomes Scale (POS), Edmonton Symptom

Assessment Scale (ESAS), and Ambulatory and Home Care Record (AHCR) were patient self- reported measures of continuity of care, quality of care, symptom distress and health services utilization, respectively. We conducted a content analysis of messages posted on Loop to understand how the system was used.

Results: Nineteen physicians (oncologists or palliative care physicians) were randomized to the intervention or control arms. One hundred twenty-seven of their patients with advanced cancer were approached and 48 patients enrolled. Of 24 patients in the intervention arm, 20 (83.3%) registered onto Loop. A mean of 1.2 (range: 0 to 4) additional healthcare providers with an average total of 3 healthcare providers participated per team. An unadjusted between-arm increase of +11.4 was observed on the Picker scale in favor of the intervention arm at 3 months.

Other measures showed negligible changes. Loop was primarily used for medical care management, symptom reporting, and appointment coordination.

Conclusions: The results of this study show that implementation of Loop was feasible and provides useful information for planning future studies further examining effectiveness and team collaboration. Numerically higher scores were observed for the Loop arm relative to the control group with respect to continuity of care. Future work is required to understand the incentives and barriers to participation so that the implementation of tools like Loop can be optimized.

ClinicalTrials.gov identifier NCT02372994

BACKGROUND

With advances in medical care enabling people to live longer, patients with chronic

diseases and their families have increasingly complex care needs requiring the expertise of many

healthcare providers from multiple settings and more frequent use of the healthcare system.1,23,281

Important contextual information is not consistently exchanged between healthcare providers,

and coordinated delivery of patient care as a team is lacking.32,41,59,282 As such, there is a need for solutions that are cross-organizational, cross-setting and that improve continuity of care, defined as the extent to which delivery of care by different providers is coherent, connected and timely.4

Organizations such as the National Academy of Medicine (NAM) and Agency for

Healthcare Research and Quality (AHRQ) have called for solutions that build on the growing

momentum of health information technology to address the deficits in continuity of care and

coordinated delivery of care.17-21 With over 80% of the populations of Canada and the United

States having access to the internet and mobile phones13, web and mobile-based communication

are ideally positioned to improve the sharing of knowledge, expertise and decision-making

between providers (“collaboration”)54, to involve patients, and, by extension, improve continuity

of care.196,283 Solutions have generally been limited to one-to-one secure messaging or email, possibly as additions to information systems such as patient health records.284

Reviews on the impact of tools for patient-provider communication have shown

promising evidence of improvement on such outcomes as patient self-efficacy, satisfaction with

care and on clinical/psychosocial outcomes.135,148 However, few tools exist with the express intent of facilitating secure team-based communication, which can enable sharing of information between different providers, across health events and settings, and promote collaborative care.147

Previous studies examining tools that enable patients to communicate with their healthcare team

89 have been observational in design and focused their examination on implementation in the pediatric,235 general primary care,285 elderly,286 and cerebral palsy287 populations. However, these studies did not consider such outcomes as continuity of care, which is particularly pertinent to the patient population with complex care needs.

In this study, we evaluated a web-based tool for clinical collaboration called “Loop”. The purpose of Loop is to assemble care teams that include patients and caregivers in order to facilitate communication and collaboration.168 We conducted a randomized controlled feasibility trial in a population of patients with advanced cancer, as prototypical of a population with complex care needs.288,289 Our objective was to evaluate the feasibility of integrating a tool like

Loop into current care processes and to capture preliminary measures of the effect of Loop on continuity of care, quality of care, symptom distress, and healthcare utilization.

METHODS

Trial Design

We conducted a 15-month multi-centered, non-blinded, pragmatic cluster-randomized controlled feasibility trial (cRCT), called the My Team of Care study, allocating participants to receive access to Loop as the intervention arm or usual care, as the control arm. The unit of randomization was at the level of the physician, the unit of analysis was at the level of the individual patient.

Setting and Participants

The study took place at the Temmy Latner Center for Palliative Care at Mount Sinai

Hospital and Princess Margaret Cancer Center in Toronto, Ontario, Canada beginning in January

2015 and ending in April 2016. The Temmy Latner Center is the largest home-based palliative

care program in Canada, consisting of 23 palliative care physicians. The Princess Margaret

Cancer Center is a University of Toronto-affiliated research hospital with 46 medical oncologists and 42 radiation oncologists. At both study sites, patients generally access their physician through visits and telephone messages; some healthcare providers are contactable via email.

Participants consisted of eligible patients plus their principal cancer physician (oncologist or palliative care physician), and if interested, their family caregiver (informal, unpaid). For the intervention arm, additional healthcare providers as identified by the patient were also invited to participate as members of the circle of care to use Loop.

Eligible patients were aged 18 or older; had stage IV cancer or stage III cancer with poor prognosis as determined by their oncologist (a survival prognosis of greater than 3 months but less than 2 years); Eastern Cooperative Oncology Group (ECOG) performance status score of 0,

1, or 2, as assessed by their oncologist or palliative care physician at time of enrolment; English literacy and language competency to provide informed consent and complete questionnaires; patients or caregivers had access to a computer and the internet. Exclusion criteria were currently receiving or a candidate for hormone therapy for breast or prostate cancer (given the impact on prognosis); impaired mental status assessed with the Bedside Confusion Scale290 (score of ≥2 suggesting cognitive impairment); participation in another study that precludes participation in this study.

Intervention

Participants randomly allocated to the intervention arm received access to Loop. Loop is a secure online communication tool for team-based clinical collaboration that enables patients and caregivers to communicate asynchronously with multiple members of the healthcare team involved in providing their direct care (i.e. not individuals hired for the purpose of research), as well as for healthcare providers including physicians, nurses, and allied health professionals to communicate with each other.

The development of Loop followed a user-centered design approach291 with substantial end-user and stakeholder involvement (including caregivers, healthcare providers from several specialties and patients with different conditions). As described by Kurahashi et al.,168 this process included initial needs assessments, ethnographic observational studies and affinity diagramming leading to the development of a prototype. This was followed by simulation activities, usability testing in laboratory and real-world settings (i.e. home, clinics, hospitals, offices), and piloting with patients and clinical teams.

Loop was developed with an intuitive interface to ideally allow for use without prior

training. A patient profile and space is created which can be viewed by the patient, healthcare

providers and caregivers on the computer or mobile phone after logging in with an email address

and password (see Figure 1 and 2). Each patient’s Loop is a secure space partitioned from other

Loops and can only be joined if involved in the patient’s care and authenticated by a study administrator. Healthcare providers may be a part of multiple patients’ Loops but patients cannot access the Loops of other patients. On the main page, individuals can write and post text-based

messages. All messages posted by any member of a patient Loop can be read and responded to

by members of that given Loop. All entries remain on the patient space, allowing for previous

posts to be viewed. The messages are threaded in conversations and can be searched using

various filters. In addition to posting messages, users may label posts with user-defined “tags”,

and an “Attention To” feature that specifies individuals to be alerted of a post by a generic email.

No updates to the system were made during the trial.

Recruitment and Study Procedures

In order to ensure that there would be at least one healthcare provider on each team,

medical/radiation oncologists or palliative care physicians were recruited first (“initiating

physician”), randomized, and patients from their practices were then approached in clinic prior to

appointments or over the phone. Physicians at the two study sites were notified of the study

through announcements at educational rounds, and physicians who expressed interest in

participating were followed up with directly.

All participants provided consent and were asked to complete a baseline demographics

form and an 11-item survey on participants’ access, comfort and usage of computers and the

93 internet.292 Initiating physicians and patients in the intervention arm were then invited to register on Loop. Registration involved completion of a form requesting participant name, address, and, in the case of healthcare providers, professional license number. Once registered on the tool, an intervention patient was considered active in the study. Through the tool, patients could invite family caregivers and additional healthcare providers to join their Loop. Study administrators contacted, explained the study, obtained consent from all additional members of a patient Loop prior to registration and posted an introductory message welcoming participants. Study administrators were part of patient Loops only for the purpose of providing assistance during registration and with using the tool, as requested. When a patient was no longer part of the study,

Loops remained open for two weeks to allow for message exchange records to be exported and saved.

Use of the tool and the type of communication that could occur on the tool was not prescribed. The intervention protocol did not specify intent to replace existing care practices or methods of communication; the intervention was additive. As Loop was not meant to be used for urgent communication, this was reinforced during the consent process and in the Loop Terms of

Use. Providers were not provided with compensation for participating in this study.

Recruitment of initiating physicians and their patients was conducted similarly in the control arm.

Usage of Loop

Usage of the intervention was evaluated from message exchange transcripts and audit data from the tool. Data included time to registration on Loop from consent date, number of

94 participants who registered on Loop, number of messages exchanged, number of times additional features (Attention To, Tagging) were used, and number of views and posts by participants.

We conducted a content analysis of each patient’s Loop messages. 293 Two coders independently reviewed messages exchanged in each Loop and assigned categories thematically that emerged from the data (see Appendix 8 for coding framework and definitions). Categories were assigned to messages and any responses or follow-up posts. Categories were assigned only once per Loop and not quantified. If multiple categories were perceived in a single post, then each was included once as a category identified in that particular Loop. Messages posted by administrators to welcome team members were excluded.

Outcomes

The primary feasibility outcomes were participant recruitment rate and implementation fidelity defined as the proportion of participants who were randomized, completed the baseline demographics and computer usage questionnaire, and if in the intervention arm, registered on

Loop, with ≥70% completion indicating feasibility success. This threshold was selected as an adequate threshold to justify further study and has been suggested previously in the literature.294

Secondary outcomes of preliminary measures of effect were measured with standardized instruments to assess the impact of Loop. Mean difference over the course of the study (from baseline to months 1, 2 and 3) for each instrument was calculated. Patient-reported continuity and coordination of care was measured with the 8-item Picker Ambulatory Cancer Care Survey83

(Picker) Continuity and Coordination subscale questionnaire. The Picker scale is scored by summing absolute positive responses, divided by the total number of responses (scores range from 0 to 100, with higher scores being better), and a minimal clinically important difference of

10 points has been found to be significant.83,98 The Palliative Care Outcomes Scale (POS)295 was used to assess patient-reported quality of care and well-being. The POS is a 12-item self- administered questionnaire (total scores range from 0 to 40, with higher scores being worse); a difference of one point on each item is considered clinically meaningful.296-298 The Edmonton

Symptom Assessment Scale299 is a 9-item, patient-reported questionnaire of symptom intensity

(pain, tiredness, nausea, depression, anxiety, drowsiness, appetite, well-being, shortness of breath) with each item rated from 0 (best) to 10 (worst). Individual symptoms are summed for the Total Symptom Distress score (ranging from 0 to 90, with higher scores indicating worse symptom distress).299 Healthcare utilization was measured as number of visits to the emergency

department and number of hospitalizations, and was self-reported at each monthly assessment using the Ambulatory and Home Care Record.300,301

Data was collected monthly for three months from baseline (four time points).

Questionnaires were distributed electronically using online surveys emailed to study participants

via Research Electronic Data Capture (REDCap) version 6.16.7302, a data management system

hosted at the Applied Health Research Center (AHRC) of St. Michael’s Hospital, Toronto,

Ontario. Patients who did not respond within one week were followed up via a reminder email or

telephone call and were considered lost to follow-up if not reachable after four contacts. We piloted outcome assessments and survey administration prior to the study.

Randomization and Blinding

This study was designed as a cRCT with initiating physicians recruited first and randomized in order to minimize contamination between study arms. Participating patients were allocated to the study arm to which their initiating physician had been randomized.

Randomization was done by a statistical team independent of the study using a computer- generated randomization sequence consisting of permuted blocks of varying size, and assigned initiating physicians in a 1:1 ratio to the intervention and control arms. It was not possible to blind patients completely to study arm, but control patients provided consent without being informed of the existence of another arm. This was done to minimize bias of control patients basing their decision to participate on study arm assignment. Control patients were informed that they were taking part in a study on patient-provider communication to improve healthcare delivery and care management. Investigators and initiating physicians were aware of study arm assignment.

Sample Size and Statistical Analysis

A formal sample size calculation was not computed, as this was a pilot study with primary feasibility outcomes. We set a target sample size of 20 to 25 patients per study arm which has been previously justified as sufficient for pilot evaluations.294,303

The primary analysis was intention-to-treat with available cases. We did not make adjustments for missing data but secondarily report comparison of data for complete cases

(participants who completed outcome assessments at all time points). Descriptive statistics were used to describe each study arm. Analysis compared mean change scores and unadjusted differences in mean change scores on the preliminary effectiveness outcomes between study arms. Statistical tests of difference were not conducted since the study was not sufficiently powered to do so.

Ethics

All participants provided written, informed consent to participate. Research Ethics

Boards of the University Health Network, Mount Sinai Hospital, University of Toronto and the

Community Care Access Centers of Toronto, Ontario approved the study.

This trial is registered with ClinicalTrials.gov, identifier NCT02372994.

RESULTS

Ten palliative care physicians and nine medical oncologists were recruited and

sequentially randomized with ten to the intervention arm and nine to the control arm. We

assessed 127 patients for eligibility of which 94 were eligible. Twenty-four patients each were recruited to the intervention and control arms. In each arm, the baseline questionnaire was completed by 21 patients. Figure 3 shows the randomization of clusters (initiating physicians), reasons patients declined to participate in the study and patient follow-up. In addition to patient and healthcare provider participation, 18 family caregivers participated in the intervention and 8 family caregivers participated in the control arm. There were two instances of initiating physicians from the intervention arm serving as additional healthcare providers on other intervention patient Loops.

Between arms, there was minimal difference between patients on demographic characteristics, with some modest discrepancies resulting from small sample size (see Table 1).

There was differential distribution of patients’ primary cancer diagnoses by arm reflecting differences in clinical subspecialties of the participating physicians: lymphoma (6 in intervention vs. 0 in control), breast (1 in intervention vs. 10 in control) and lung (3 in intervention vs. 6 in control). There was minimal difference at baseline in comorbidity and performance status as

98 measured with the ECOG score. Participants were comfortable with using computers and less so internet-enabled devices (tablets and smartphones), as described in the Appendix 9. Initiating physicians in both arms showed similar demographic and practice characteristics (Table 2). All were from academic settings and most had an alternative payment plan fee structure.

Regarding team assembly in the intervention arm, an average of 3 healthcare providers, including the initiating healthcare provider, participated per patient Loop. Patients suggested between 1 to 5 additional healthcare team members to participate on Loop; 22/51 additional providers consented to participate in the study (mean 1.2 per patient [range: 0 to 4]), and 65%

(13/20) of patient Loops had an additional healthcare provider register on the tool (Table 2).

Only half of additional healthcare providers who took part in patient Loops were from different locations than the initiating healthcare provider.

Usage of Loop

In the intervention arm, 83.3% (20/24) of patients who consented, registered on Loop

(see Table 6). In terms of healthcare provider load, the mean number of patient Loops per initiating physician was 1.6 (range: 0 to 7). Registration on Loop required that the baseline questionnaire be completed beforehand. The time from consent to registration on Loop varied considerably, with the mean time to registration being 39 days; some patients experienced disease worsening between consent and registration, and one patient delayed taking the step to register for 156 days due to personal circumstances. Over the study period, the majority (17/20) of Loops had message exchanges, with 13/20 (45%) having more than six messages exchanged.

During the study, there were 358 logins by all participants; 43 were on the mobile version and

315 were on the desktop version. Patients viewed their Loops more often relative to their number

of posts (a difference of 14.3) compared to initiating physicians viewing and posting to their

patients’ Loops (a difference of 3.9).

Content analysis of messages revealed that of Loops with messages exchanged, messages regarding medical care management, reporting of symptoms, and appointment coordination predominated (these categories were identified in 50%, 45% and 45% of Loops, respectively), while only 10% of the Loops had messages that were prescription-related queries (see Figure 4).

No urgent messages were exchanged during the study.

Outcomes

For the primary outcomes, the mean number of patients recruited per initiating physician was similar between study arms (in intervention arm 2.4 [range: 0 to 7] in intervention vs. control arm 2.7 [range: 0 to 7]) (see Table 3). With respect to implementation fidelity, 87.5%

(21/24) of control patients who consented completed the baseline questionnaire and 75% (18/24) of intervention patients completed the baseline questionnaire, along with registering on the tool.

Regarding patient retention, in the intervention arm, three patients withdrew due to declining health, one patient withdrew because they were no longer interested, and one patient died. In the control arm, one patient withdrew due to declining health, and five patients died. Instrument and item completion were approximately proportional to patient retention (of patients completing the baseline outcome assessment, 11/21 in the intervention arm and 11/21 in the control arm completed month 3 outcome assessments).

Results described are based on available cases. Mean change scores and unadjusted

difference in change scores between study arms for preliminary effectiveness outcomes are

presented in Table 4. At month 3, there was an increase in Picker continuity and coordination of

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care scale scores (in intervention arm +10.2 [SD 31.5] vs. control arm -1.1 [SD 30.3]), a

negligible change in POS (in intervention arm +0.8 [SD 4.4] vs. control arm +0.5 [SD 5.4]), and

an increase in ESAS Total Symptom Distress score (in intervention arm +2.3 [SD 10.7] vs. control arm +3.4 [SD 8.7]). The number of patients with ER visits self-reported at baseline was 3

in the intervention arm and 1 in the control arm; at the third month no visits were reported in the

intervention arm and three were reported in the control arm. Similar numbers were observed for

number of patients with hospitalizations. On complete case analysis, the Picker scale showed a

between-arm difference of +18.5 [SD 47.4] in favor of the intervention arm (see Table 5).

DISCUSSION

In this feasibility cRCT evaluating an online communication tool for clinical

collaboration, trial feasibility conditions and implementation goals were met. The study was not

powered to observe changes in outcomes between study arms but we did observe higher

continuity of care scores in the intervention arm at last follow-up, which was maintained on

complete case analysis. Regarding the assembly of teams, though each patient identified at least

one additional healthcare provider, only 65% of patient Loops had an additional healthcare

provider register on the tool. Loop was primarily used for medical care management, symptom-

related discussions, and appointment coordination.

Interpretation

As a population with complex care needs304, the advanced cancer population served as an

exemplar patient population in which to evaluate Loop, but also proved challenging from a

participation standpoint. Although the proportion of eligible patients who consented in this study

101 was slightly higher than two previous studies conducted at the same institution with the same population (38% here vs. 10%)98,305, a number of patients withdrew due to ill health or died over the course of the study. This was expected given the uncertainty in prognosis in this population.

Instrument completion rates reflected patient retention rates, indicating that questionnaire administration was feasible despite the nature of the patient population.

Loop was designed to connect patients and caregivers to their team of healthcare providers in a virtual space where communication might be facilitated outside of appointments and across care settings.168 While we did not assess differences in measures of effect for statistical significance, preliminary Picker scale results appear to support potential for this tool to improve continuity of care in future studies of adequate statistical power. Contextualized with the content of messages, the findings of this study may suggest that there were important needs that could be dealt with between appointments by using the tool contributing to increased perceptions of continuity of care.

The care of patients with complex needs requires a redefining of the relationship between healthcare providers and patients to a team-based model of care which engages the patient.109

These patients often have interdependent issues and thus require collaborative approaches to care

(shared goals and negotiated decision-making between individuals in a synergistic manner) over coordination between providers (alignment of functioning among independent individuals to address common needs).306 Here, the greater use of Loop by patients over healthcare providers and the patient-driven content of messages (ex. Updates, Appointment Coordination), are suggestive that in this study, coordinative tasks were addressed to some extent but collaboration between providers, and with the patient/caregiver, did not occur. Given these results, we

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recognize that Loop in isolation did not produce collaboration, and further consideration into

building relationships among these teams is required.307

We further found that assembling the team was difficult in this study, with few healthcare

providers from outside academic practices, who were identified by the patient, agreeing to join.

Other studies have found that barriers to healthcare provider participation and uptake of studies

of digital health tools include lack of provider compensation and perceived worry about the

burden of patient overuse.308 Although this increased burden has not been observed thus far309,

better strategies to improve integration into clinical workflow need to be examined, especially

for physicians with large patient rosters. Implementation of incentive schemes, akin to what has

been done in the province of Ontario, Canada for electronic consultations310 may also improve

uptake of digital health tools, like Loop into practice.

In this study, Loop was intentionally provided to teams without training. We observed

that participants were able to understand and use the core functionality of Loop, that is, to post

and read messages. We further observed that patients viewed their Loop more often than they

posted compared to healthcare providers, who posted nearly as often as they viewed a Loop. This

could be interpreted as showing that patients were more proactive tool users while healthcare providers are more likely to wait for notifications before logging in.

Comparison with Previous Studies

While many tools for patient-provider communication exist (frequently as secure email or part of patient portals),135,202 few have considered the potential value of team-based

communication which is crucial for complex care scenarios or situations requiring ongoing care.

At least four studies have evaluated variations of tools connecting patients and caregivers with

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multiple healthcare providers. Gulmans et al.287 found that patient groups who used their tool more often tended to have a larger care network (number of professionals registered per patient).

Furthermore, Ralston et al.285, in evaluating secure messaging as part of a portal, found that

messaging increased proportionally with patient morbidity, which reinforces the suggestion that

messaging is of more value in complex care. While our study was too small to examine such

associations, these findings support the increased value that digital health tools for

communication may have as complexity of team and illness increase.

In a study by Hsiao et al.235, as has been noted elsewhere,144,311 participants felt that text-

based communication may diminish the therapeutic relationship gained from in-person visits or unstructured voice-based contact (such as telephone). This suggests that such forms of communication should supplement, but not replace, appointments/calls.

The ZWIP tool, by Robben et al.286, allows for patient-provider and between-provider communication. Evaluation in frail elderly patients found that use by both patients and providers depended on provider use of the tool. Healthcare providers considered implementation strategies

(such as training to use the tool) “very necessary” to make the most use of ZWIP. This finding may reflect the need for guided implementation to facilitate integration into clinical workflow and to improve the use of Loop.

Limitations

The learnings of this study should be interpreted within the context of the study’s strengths and limitations. As a feasibility study, we aimed for a sample size that is adequate to determine feasibility of implementation. However, this sample size limited the ability to test the effectiveness of the intervention. All healthcare providers described themselves as very

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comfortable with computers and worked in fully-computerized practices, however, this may not

be true of every medical practice, limiting study generalizability. Similarly, the complexity of

clinical cases and nature of physician practice may be different elsewhere. While patients with

advanced cancer are a prototypical population of patients with complex care needs and have

involvement of multiple providers, similar results may not be reflected in other populations. The

cRCT design, involving recruitment and randomization of initiating physicians (clusters)

sequentially, and their patients prospectively, may have led to selection bias because of

differential recruitment rates by provider and differences in their clinical subspecialty. We also

observed that more patients died in the control arm than in the intervention arm possibly

indicating unmeasured confounding. As use of the tool was voluntary, there is also a risk of confounding by indication, with patients who have more issues needing to use the tool more often, or functionally-limited patients using the tool less often.

CONCLUSION

In this study, we found that it was feasible to implement Loop in clinical practice and that

the tool may have the potential to improve continuity of care. The results of this study will

inform the next phase of research, which aims a) to understand the conditions that affect tool

adoption and assembly of teams; b) to understand the relationship between use and outcomes

such as continuity and quality of care; c) to examine the contexts and target populations where

the benefits of a tool like Loop may be best realized and where the effort to assemble the care

team is justified; and d) to consider team building strategies and implementation approaches that

facilitate patient and provider online communication. As an ongoing goal of eHealth

development, the integration of the dynamic components of care (communication and

105 collaboration) with the static repositories of medical records would enable a more seamless provision of healthcare. However challenging this may be in the current environment of multiple electronic health records across organizations, studying collaborative tools like Loop advances this goal.

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ACKNOWLEDGMENTS TV, EG, TJ, AK, BL, MK, MM and AH were involved in study conception. TV, EG, AK, BL, MK, MM, RM, and AH were involved in study design. TV wrote the study protocol. TV, AK and BL were involved in acquisition of data. TV and RM were involved in analysis. TV drafted the manuscript and all authors contributed to revisions.

The My Team of Care study would like to acknowledge the Loop Team, consisting of Alyssa Bertam, Joe Cafazzo, Eyal Cohen, Peter Weinstein, Adam Rapoport, Jennifer Stinson, Andrea Bezjak, Wayne Ho, Renee Desjardins and Russell Goldman as well as Melanie Powis, Jodheme Goldhar, Dipti Purbhoo, Vishal Kukreti, Carol Sawka, Denise Guerriere, Rick Skinner, Ken Sutcliffe, Lydia Lee, Daniela Crivianu-Gaita, Andrew Szende and Camilla Zimmermann for their contributions to making this study possible.

T. Voruganti is supported by a Canadian Institutes for Health Research MD/PhD studentship and McLaughlin Foundation fellowship. E. Grunfeld is supported by a clinician-scientist award from the Ontario Institute for Cancer Research (OICR) and the Giblon Professorship at the Department of Family and Community Medicine.

This research was funded by a grant from the Academic Health Science Centre (AHSC) AFP Innovation Fund- Mount Sinai Hospital/University Health Network Academic Medical Organization (AMO) and the Temmy Latner Centre for Palliative Care.

CONFLICTS OF INTEREST: The authors have no conflicts of interest to declare.

ABBREVIATIONS: NAM- National Academy of Medicine AHRQ- Agency for Healthcare Research and Quality cRCT- Cluster Randomized Controlled Trial ECOG- Eastern Cooperative Oncology Group scale POS- Palliative care Outcomes Scale REDCap- Research Electronic Data Capture AHRC- Applied Health Research Center

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Study Tables

Figure 1 Mock screenshot of the Loop interface on desktop computer

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Figure 2 Mock screenshot of the Loop interface on mobile phone

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Figure 3 Participant flow diagram

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Table 1: Baseline patient and family caregiver characteristics by treatment arms Intervention Control arm arm Patients (n=21) (n=21) Age – years, mean ± SD 60 ± 12.8 59.5 ± 13.8 Female sex – no. (%) 13 (61.9) 16 (76.2) Primary cancer site – no. (%) Breast 1 (4.8) 10 (47.6) Colorectal 2 (9.5) 1 (4.8) Lung 3 (14.3) 6 (28.6) Prostate 2 (9.5) 0 Ovarian 0 1 (4.8) Thyroid 2 (9.5) 0 Lymphoma 6 (28.6) 0 Melanoma 0 1 (4.8) Brain 1 (4.8) 0 Other: 4 (19.0) 2 (9.5) Annual household income – no. (%) $0 - $21,999 2 (9.5) 4 (19.1) $22,000 - $49,999 2 (9.5) 2 (9.5) $50,000 - $89,999 7 (33.3) 4 (19.1) > $90,000 4 (19.1) 5 (20.8) Prefer not to disclose 6 (28.6) 6 (28.6) Primary language – no. (%) English 20 (95.2) 20 (95.2) Other 1 (4.8) 1 (4.8) Age-adjusted Charlson Comorbidity Index – mean ± SDa 5.2 (2.5) 5.8 (1.9) Caregiver – no. (%) Yes 4 (19.1) 6 (28.6) No 17 (81.0) 15 (71.4) Highest education attained – no. (%) Primary school - - High school 4 (19.1) 6 (28.6) College/University 8 (38.1) 8 (38.1) Professional/Graduate degree 9 (42.9) 7 (33.3) Eastern Cooperative Oncology Group score – median (IQR)b 1.5 (1 to 2) 1 (1 to 2) Outcome measures (n=39) Picker Continuity and Coordination subscale – mean ± SDc 47.9 (28.5) 62.5 (25.3) Palliative Care Outcomes Scale – mean ± SDd 9.3 (6.8) 9.8 (5.4) Edmonton Symptom Assessment Scale (Total Symptom 21.2 (17.1) 23.4 (12.9) Distress Score) – mean ± SDe Family caregivers of consented patient participants (n=18) (n= 8) Age – years (mean ± SD) 57 (15.9) 54 (14.6) Female sex – no. (%) 9 (60.0) 6 (33.3) Missing – no. (%) 3 (16.7) - Relationship to patient – no. (%)

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Spouse 7 (38.9) 4 (22.2) Immediate family 5 (27.8) 8 (44.4) Other 3 (16.7) - Missing data 3 (16.7) - IQR= interquartile range aAge-adjusted Charlson Comorbidity Index is a measure of comorbidity based on risk of mortality. The score is weighted by age, increasing for each decade over age 40.312 bEastern Cooperative Oncology Group scale is scored from 1 to 5 with 1 being well and 4 indicating complete disability. A value of 5 indicates death. cThe Picker Continuity and Coordination subscale is a proportion of total number of positive responses to total number of responses. Higher scores indicate the higher perceived continuity and coordination of care. dMean summed scores are presented for the Palliative Care Outcomes Scale with a maximum score of 40. Higher scores indicate worse quality of care. eMean summed scores are presented for the Edmonton Symptom Assessment Scale with a maximum score of 90. Higher scores indicate higher symptom distress.

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Table 2: Baseline healthcare provider demographics Intervention Control arm arm Initiating physicians (n=10) (n=9) Age – years (mean ± SD) 44 ± 7.9 43 ± 6.1 Female sex – no. (%) 5 (50.0) 3 (33.3) Years in healthcare – (mean ± SD) 16 ± 8.8 15 ± 6.5 Initiating physician profession – no. (%) Medical oncologist 4 (40.0) 2 (22.2) Radiation oncologist 1 (10.0) 2 (22.2) Palliative care physician 5 (50.0) 5 (55.6) Primary practice setting – no. (%) Hospital-based 6 (60.0) 4 (44.4) Home-based care 4 (40.0) 5 (55.6) Other - - Type of practice – no. (%) Community setting - - Academic setting 10 (100) 9 (100) Practice fee structure – no. (%) Fee-for-service - - Alternate payment plan 8 (80.0) 7 (77.8) Salaried 1 (10.0) 1 (11.1) Other 1 (10.0) 1 (11.1) Provides after-hours care – no. (%) Telehealth - - Phone support 2 (20.0) 4 (44.4) Phone support with visit when needed 6 (60.0) 5 (55.6) Other - - None 2 (20.0) - Additional healthcare providers identified – total no. 51 Additional healthcare providersa (n=22) Profession – no. (%) Family physician 1 (4.5) Nurse 4 (18.2) Case manager 1 (4.5) Palliative care physician 4 (18.2) Medical oncologist 5 (22.7) Naturopath 1 (4.5) Oncology nurse 1 (4.5) Otolaryngologist 1 (4.5) Personal support worker 1 (4.5) Psychiatrist 1 (4.5) Pharmacist 1 (4.5) Physiotherapist 1 (4.5) Number of additional healthcare providers who consented 16 (72.7) and registered on Loop – no. (%)

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Additional healthcare providers identified per patient – 2.4 (1 to 5) mean (range) aRecruited as part of the intervention arm and who provided consent

Table 3: Feasibility outcomes by treatment arm Intervention arm Control arm (n=24) (n=24) Number of patients from oncology practices 18 13 Number of patients from palliative care practices 6 11 Number of initiating physicians 10 9 Number of consenting initiating physicians 9 7 approached who provided at least one patient Patients who complete baseline and, if in the 18 (75%) 21 (87.5%) intervention arm, registered on Loop – no. (%) Patients recruited per initiating physician – 2.4 ± 2.2 2.7 ± 2.6 mean ± SD Number of patients with a family caregiver who 18 8 participated in study Number of teams with an additional healthcare 13 - provider

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Table 4: Preliminary measures of effectiveness by treatment arm, Available case analysis Score at Score at Mean Mean Unadjusted each month each month observed observed difference in the in the change from change from between Intervention Control arm baseline baseline change arm (SD) in the (SD) in the scores (SD) Intervention Control arm arm Picker Continuity and Coordination subscale – mean (SD)a 1 month 58.7 (23.0) 64.4 (23.3) -3.4 (29.6) -6.7 (11.0) 3.3 (31.6) 2 months 66.7 (27.4) 69.8 (24.7) 9.1 (25.1) 4.2 (22.8) 4.9 (33.9) 3 months 63.5 (25.8) 60.2 (24.9) 10.2 (31.5) -1.1 (30.3) 11.4 (43.8) Palliative Care Outcomes Scale – mean (SD)b 1 month 7.5 (5.1) 8.3 (5.3) -1.3 (4.0) -1.0 (3.4) -0.3 (5.2) 2 months 7.2 (4.5) 9.2 (6.0) 0.0 (3.2) -0.6 (4.0) 0.6 (5.1) 3 months 8.2 (4.8) 10.3 (6.5) 0.8 (4.4) 0.5 (5.4) 0.4 (7.0) Edmonton Symptom Assessment Scale (Total Symptom Distress Score) – mean (SD)c 1 month 14.6 (11.8) 24.7 (15.2) -3.0 (9.0) 1.4 (12.2) -4.4 (15.2) 2 months 15.2 (12.1) 21.1 (11.7) -1.6 (9.4) 1.1 (8.0) -2.7 (12.4) 3 months 19.2 (9.3) 23.3 (17.0) 2.3 (10.7) 3.4 (8.7) -1.1 (13.8) Number of patients with an emergency room visit in the previous four weeks Baseline 3 1 - - - 1 month 1 2 2 months 0 2 3 months 0 3 Number of patients with a hospitalization in the previous four weeks Baseline 3 0 - - - 1 month 1 1 2 months 0 0 3 months 0 3 aThe Picker Continuity and Coordination subscale is a proportion of total number of positive responses to total number of responses. Higher scores indicate the higher perceived continuity and coordination of care. bMean summed scores are presented for the Palliative Care Outcomes Scale with a maximum score of 40. Higher scores indicate worse quality of care. cMean summed scores are presented for the Edmonton Symptom Assessment Scale with a maximum score of 90. Higher scores indicate higher symptom distress.

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Table 5: Complete case analysis preliminary measures of effectiveness by treatment arm Score at each Score at each Mean Mean Unadjusted month in the month in the observed observed difference Intervention Control arm change from change from between arm baseline (SD) baseline (SD) change in the in the scores (SD) Intervention Control arm arm Picker Continuity and Coordination subscale – mean (SD)a Baseline 57.8 (27.5) 76.8 (21.0) ‒ ‒ ‒ 1 month 51.6 (20.5) 73.2 (28.3) -6.3 (34.7) -3.6 (11.9) -2.7 (36.7) 2 months 62.5 (25.0) 76.8 (24.4) 4.7 (26.7) 0.0 (21.7) 4.7 (34.4) 3 months 65.6 (60.0) 66.1 (29.5) 7.8 (36.6) -10.7 (30.1) 18.5 (47.4) Palliative Care Outcomes Scale – mean (SD)b Baseline 8.0 (6.0) 8.0 (6.2) ‒ ‒ ‒ 1 month 6.5 (3.7) 6.0 (5.9) -1.5 (4.4) -2.0 (3.0) 0.5 (5.3) 2 months 8.3 (3.5) 7.1 (5.1) 0.3 (3.8) -0.9 (2.0) 1.1 (4.3) 3 months 8.3 (3.1) 8.4 (7.6) 0.3 (4.7) 0.4 (6.0) -0.2 (7.6) Edmonton Symptom Assessment Scale (Total Symptom Distress Score) – mean (SD)c Baseline 16.8 (10.3) 16.8 (12.8) ‒ ‒ ‒ 1 month 11.7 (8.0) 19.4 (13.2) -5.1 (9.7) 2.5 (7.4) -7.7 (12.2) 2 months 14.3 (8.3) 20.3 (13.6) -2.5 (11.0) 3.5 (7.4) -6.8 (13.3) 3 months 18.9 (8.4) 21.3 (21.4) 2.1 (11.6) 4.4 (10.3) -2.4 (15.5) Number of patients with an emergency room visit in the previous four weeks Baseline 2 1 - - - 1 month 1 1 2 months 0 0 3 months 0 2 Number of patients with a hospitalization in the previous four weeks Baseline 2 0 - - - 1 month 1 0 2 months 0 0 3 months 0 3 aThe Picker Continuity and Coordination subscale is a proportion of total number of positive responses to total number of responses. Higher scores indicate the higher perceived continuity of care. bMean summed scores are presented for the Palliative Care Outcomes Scale with a maximum score of 40. Higher scores indicate worse quality of care. cMean summed scores are presented for the Edmonton Symptom Assessment Scale with a maximum score of 90. Higher scores indicate higher symptom distress.

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Table 6: Usage of Loop (Intervention arm participants, n=24) Loop compositiona Number of patients who registered on Loop (regardless of baseline 20 (83%) questionnaire completion) – no. (%) Number of initiating physicians (intervention arm) (n=10) who: Registered on Loop – no. (%) 9 (90%) Used the tool (posted at least 1 message or viewed a patient Loop) – no. (%) 7 (70%) Number of healthcare providers (including initiating physician) per patient 3 (0 to 5) Loop – mean (range) Number of additional healthcare providers suggested by each patient – mean 2.4 (1 to 5) (range) Number of additional healthcare providers per patient Loop – mean (range) 1.25 (0 to 4) Number of patient Loops healthcare provider is a part of – mean (range) 1.6 (0 to 7) Number of family caregivers per patient Loop – mean (range) 0.5 (0 to 1) Frequency of use of the tool Frequency of use (no.) No. of Loops Number of messages exchanged per Loop (n=20) by registered patients, caregivers, providers 0 3 1-2 5 3-5 3 6 -10 6 >10 3 Number of views of a patient’s own Loop by the patient or caregiver (n=20) 0 0 1-2 3 3-5 4 6-10 5 >10 8 Number of posts to a patient’s own Loop by the patient or caregiver (n=20) 0 6 1-2 5 3-5 3 6-10 4 >10 2 Number of views of a patient Loop by an initiating physician (n=9) 0 2 1-2 1 3-5 2 6-10 4 >10 0 Average number of posts to all their patient Loops by an initiating physician (n=9) 0 3 1-2 5 3-5 1

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6-10 0 >10 0 Use of additional features Time from consent to registration on Loop (days) – mean (range) 39 (2 to 156) Number of times an issue was tagged – mean (range) 1 (1) Number of times Attention To feature was used by a patient or caregiver– 3 (0 to 14) mean (range) Number of times Attention To feature was used by a healthcare provider 0.6 (0 to 3) per Loop– mean (range) aA “Loop” is an aggregation of a patient and/or caregiver and at least the initiating physician allocated to the intervention arm, and registered on the intervention tool

Figure 4 Categories of messages on Loops with messages exchanged- See Appendix 8 for description of coding strategy

Message categories on Loops (n=17)

Updates Medical Care Management Prescription Renewal Prescription of Medication

Medication Information/Changes

Administrative/System Set-Up Appointment Coordination Symptoms

0 2 4 6 8 10 12

# of Loops in which categories appeared

CHAPTER 4: QUALITATIVE STUDY

Title: Disruption or Innovation? A Qualitative Descriptive Study on Electronic Patient-Physician Communication in Patients with Advanced Cancer

Author(s): Teja Voruganti, Amna Husain, Eva Grunfeld, and Fiona Webster

A version of this article has been submitted for publication.

Key Words: Team-based care Secure messaging Clinical collaboration eHealth evaluation

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ABSTRACT

Background: Clinical management of patients with advanced cancer is complex, involving specialized treatment and multiple healthcare providers in different settings. In this context, care coordination and sharing of contextual information is often inadequate, leading to suboptimal continuity of care. Electronic communication has the potential to address these gaps and engage patients in their own care. We studied the effect of a web-based tool which assembles the patient, their caregivers and their healthcare providers in a virtual space for team-based communication.

We sought to understand participant perceptions on electronic communication in general, and the added value of the new web-based tool in particular.

Methods: We conducted a qualitative descriptive study with participants (patients, caregivers and cancer physicians) who participated in a 3-month feasibility trial for evaluating a patient- provider team-based communication tool. Stratified purposive sampling of monthly interviews with intervention arm participants was done. Interviews were thematically analyzed until saturation was reached and source triangulation was used to relate perspectives from patients, caregivers and cancer physicians. Forty-one interviews from six patients, five of their caregivers, four oncologists and three palliative care physicians were analyzed.

Results: We identified five themes relating participants’ perspectives on web-based patient- provider communication to their experience of care: 1) apparent gaps in care; 2) uncertainty in defining the circle of care; 3) relational aspects of communication; 4) incongruence between technology and social norms of patient-physician communication; and 5) appreciation but

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apprehension about the role of the patient-provider team-based communication tool for improving the experience of care. Patients felt that electronic communication in general may be

positive because of the opportunity to seek clarification between appointments. Regarding the team-based communication tool, we found that participants were appreciative of the tool’s

intention to promote connectedness among the healthcare team. However, patients viewed the

role of web-based communication tools as supplemental to traditional face-to-face interactions

with their providers out of apprehension that they could affect the therapeutic relationship.

Conclusions: The potential of tools for web-based communication to bring together a team of

healthcare providers with the patient and caregivers is significant but may pose new challenges

to interpersonal dynamics, understanding of team composition, and distinguishing roles on the

team. Approaches to implementation which build the relationship between the patient and

provider, and integrate the team as a whole, can positively position web-based communication as

a means to enhance the team-based care process.

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BACKGROUND

For patients with advanced cancer, this period of illness is often characterized by

uncertainty and anxiety, compounded by complexities related to care management.49-51

Specialized treatment regimens and follow-up necessitate involvement of multiple healthcare

providers from different settings.59,313 However, research increasingly shows that information

transfer between providers is inconsistent, leading to wasted healthcare resources, risks to safety,

and leaving patients and caregivers to shoulder the burden of care coordination.52,314

Multidisciplinary, team-based management is therefore essential in the context of chronic

conditions56 to overcome fragmentation and improve continuity of care. Continuity of care is

defined as the extent to which the delivery of care by different providers is coherent, connected

and timely.75

In an appeal to address such gaps, the National Academy of Medicine (NAM) issued

reports on patient safety21 and quality improvement20 advocating for system redesign predicated

on patient-centered care delivery that is “respectful of and responsive to individual patient

preferences, needs, and values, and ensuring that patient values guide all clinical decisions”.20

The NAM and organizations such as the Agency for Healthcare Research and Quality17,18 have

called for solutions that leverage the potential of electronic communication to facilitate the

exchange of clinical data and contextual information between healthcare providers and with

patients. Such an endeavor aims to empower patients through greater access to their clinical

information and the opportunity to communicate with their providers.196,315,316

We conducted a qualitative study with advanced cancer patients, their caregivers and cancer physicians who took part in a randomized controlled feasibility trial evaluating a web- based tool for patient-provider team-based communication called Loop.168 The tool connects a

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patient, the healthcare providers who they view as being involved in their direct care and their

caregivers in a secure virtual space for text-based communication about non-urgent matters. The

intended purpose of the tool is to facilitate interprofessional collaboration in goal-setting and

arriving at plans of care. We wanted to explore participant perceptions of the tool with the

overarching goal of understanding the value of an electronic communication tool in this care

context.

METHODS

Study Design

We conducted a qualitative descriptive study182 with participants of a non-blinded,

pragmatic cluster randomized controlled feasibility trial evaluating the tool compared to usual

care (ClinicalTrials.gov identifier: NCT02372994). This concurrent nested study177 was conducted to provide insight into perceptions of electronic communication alongside the trial that had the objective of evaluating feasibility of implementation and effect of Loop. In the trial, oncologists and palliative care physicians (initiating cancer physicians) were the unit of randomization. Initiating physicians were recruited from two university-affiliated hospitals in

Toronto, Ontario, Canada. Patients and their caregivers were recruited prospectively from physicians’ practices such that an initiating physician could have multiple patients enrolled in the study. Participants were adults with a prognosis of ≥3 months, stage IV cancer or stage III with poor prognosis who had access to a computer/internet and who could complete outcome assessments. The duration of the study was three months. Initiating physicians and their patients who were randomized to the intervention arm received access to the tool for the study duration; use of the intervention was not prescribed. Once randomized, patients could then suggest other

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healthcare providers involved in their direct care (ex. nurses, family physicians, allied health

professionals) to use the tool with them. The quantitative outcomes of the study were trial

feasibility, and preliminary measures of patient-perceived continuity of care, quality of care,

symptom distress and healthcare utilization, and were measured on a monthly basis for 3 months.

The results of the study showed that implementation of the tool was feasible and there was an

increase in patient-perceived continuity of care in the intervention arm compared to the control

arm.

Data Collection

Interviews were conducted individually by telephone or in-person with patients,

physicians and caregivers. The use of telephone and face-to-face interviews in the same study is supported in the literature.317 Interviews were conducted on a monthly basis by the lead author

(TV) or a research assistant using a semi-structured interview guide (see Table 1 for sample guide). The interview guide was developed upon discussion with the study authors, and guided by usability testing methods318 and the Technology Acceptance Model.183,184 The model suggests

that use of a new technology is predicted by its acceptance by users (“intention to use”), which is

in turn predicted by attitude, perceived usefulness (“value”) and ease of use.184 The questions in

the interview guide are informed by these constructs. The interview guide was piloted for length

and flow before commencing the study and revised as thematic patterns emerged. Given the

uncertain nature of prognosis in the study population, not all participants were expected to

remain in the study for follow-up at all assessments, but we wanted at least one follow-up

interview to allow for reflection on experiences once they had access to the Loop tool. Stratified

sampling319 of monthly interviews was done of sequential intervention arm patients, their

124 caregivers and initiating cancer physicians, restricting data analysis to interviews from those who completed an interview at baseline and at least one month of follow-up. The baseline guide did not inquire about use of the Loop tool but at follow-up, interviews reflected a focus on the tool.

Field notes and memos were made during and after interviews, and during analysis to document reflections and thoughts.

Data Analysis

Interviews were digitally recorded and transcribed verbatim. Transcripts were imported into NVivo (Version 10),320 a software for organizing qualitative data. The lead and senior authors (TV and FW, respectively) independently coded an initial subset of interview transcripts and developed a coding framework. Subsequent interviews were analyzed using thematic analysis, as described by Braun and Clarke178, by the lead author who met regularly with the senior author to discuss interpretations and revisions to the coding framework. We adopted a critical theoretical lens155 relating participant perspectives to the concept of patient-centered care.

This study followed a constructivist approach which asserts that reality is socially constructed, influenced by social and historical context and experiences.321 Codes were assigned to portions of text representing units of meaning and were grouped into categories based on similarities.322

As the relationships between categories were iteratively constructed and interpreted by the authors, themes emerged relating categories to central ideas. While developing the coding framework, we noted that interviews from patients, caregivers and physicians were reflecting connected concepts, so source triangulation (between patients, caregivers and physicians) was done at the stage of theme assignment.323 Given similar emerging coding schemes at the final stage, codes and corresponding quotes from patient, caregiver and physician interviews were

125 merged as themes were assigned. This suited the joint nature of communication between patients, caregivers and providers; many perceptions appeared to be shared or were facets of the same theme. As described under Data Collection, sequential interviews were conducted with the each participant, and analyzed together without making a distinction between time points because the nature of responses nonetheless differed between baseline and follow-up, from focusing on team structure and existing communication practices to a focus on the patient- provider team-based communication tool. Transcripts were analyzed until categorical saturation was achieved.324,325 Informed consent was obtained from all participants. Research ethics board approval was received from the University of Toronto, University Health Network and Mount

Sinai Hospital of Toronto, ON.

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Table 1 Example of questions in the semi-structured interview guide For all participants, 1. Can you describe all of the members of your/[the patient’s] health care team? * 2. How connected do you feel to the healthcare team? 3. How would you describe your involvement on the healthcare team? 4. How has the team changed from when you/[the patient] were first diagnosed? 5. How do you communicate with healthcare providers/[patients] when there are questions about care from day to day? What methods do you use to communicate with them? 6. What considerations would you have when deciding to use electronic communication? * 7. Would you hesitate to use electronic communication with your/[the patient’s] healthcare team? * 8. Has use of the tool affected your interaction with your/[the patient’s] healthcare team? ** 9. What did you like or dislike about the tool? ** 10. How did you use the tool? ** 11. Can you describe situations where using the tool was useful? Not useful? ** Specifically for physicians at baseline, 1. In what contexts do you communicate with patients and caregivers? * Specifically for patients and caregivers at baseline, 1. Can you tell me a little bit about your healthcare condition? * Prompt: Do you have any healthcare needs currently? What role do your providers have in addressing those needs? 2. Can you tell me about the individuals who are involved in your care? * 3. What are some aspects about communication with your team that you like right now? Are there things you do not like? * Questions specific to baseline only ** Questions specific to follow-up only

RESULTS

In this study, of the 24 patients, 18 caregivers, and 10 initiating cancer physicians (5 oncologists and 5 palliative care physicians) who took part in the intervention arm of the trial, we analyzed monthly interviews (n=41) for six patients, five of their caregivers, four oncologists and three palliative care physicians (see Table 2). We identified themes from monthly interviews

(M0 for baseline, M1, M2, M3) with participants who were able to complete at least one monthly follow-up interview over the course of the study reflecting opinions on the value of electronic communication, and the tool specifically, in the context of their care, the patient-physician relationship and team membership. We categorized these inter-related themes as: 1) apparent

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gaps in care; 2) uncertainty in defining the circle of care; 3) relational aspects of communication;

4) incongruence between technology and social norms of patient-physician communication; and

5) appreciation but apprehension about the role of the web-based communication tool for

improving the experience of care.

Table 2 Description of the participants

Participant demographics Patients (n=6) Age – years; mean (SD) 60 (15) Female 50.0% Caregivers (n=5) Age– years; mean (SD) 60 (14) Female 80.0% Healthcare providers (n=7) Age – years; mean (SD) 44 (9) Female 57.1%

Apparent gaps in care

Both patients and physicians in our study spoke about the complexities of care

management in advanced cancer, noting that “the challenge is actually when there’s

multidisciplinary care across institutions” (Radiation Oncologist, M0). With all patients in the

study having multiple physicians and allied health professionals involved in their care,

participants described issues with care coordination and communication that resulted in

“…opportunities for miscommunication so the broken telephone syndrome” (Medical

Oncologist, M0). Poor communication was described as involving redundancies or lack of

transmission of information between physicians, repeating information over multiple visits to

different family members, and not adapting to the preferred modes of communication (e.g.

telephone, appointments etc.) of different physicians. We found that many patients felt that they

128 were the common thread of information between their physicians as different healthcare providers had “information in different places, filed in different places, some texts, some emails, some scratched notes on a piece of paper, some in the chart.” (Palliative Care Physician, M0). As one patient felt,

“Without me a lot of them wouldn’t have certain information. Like I keep

the information that they need basically, or my husband, whoever has the

info book.” (Patient, M1)

This reflected a broader theme of confusion over who is in charge of coordinating care and at what point in the care trajectory of diagnosis, treatment and palliative care:

“I think basically, the connector is the patient. So, he gives me updates

about what some of the other providers have recommended. I don’t

really have a lot of direct contact with them otherwise.” (Medical

Oncologist, M2)

On further inquiry, misunderstandings in responsibility for coordination appeared to be related to uncertainty around who is a member of the healthcare team and their roles.

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Uncertainty in defining the circle of care

When we asked about the healthcare team, participants could not easily describe who

makes up the group of individuals involved in a patient’s care, termed by a few participants as

the “circle of care”:

“I make sure that I have the correct information..., because one of the things that

very much lacks in our system is a clear identification of the circle of care.”

(Medical Oncologist, M0)

Participants felt that membership in the circle of care is dependent on stage of illness/treatment, with the “definition of roles and responsibilities even within a shared care model [needing] to be continuously updated because it may ebb and flow at various points in time,” (Medical Oncologist, M0). However, the transitions between stages can affect perceptions of continuity in relationships with physicians:

“I think the way these things happen traditionally is patients use practitioner

X. Practitioner X, who has specialty in X, facilitates that support and then

passes patient back out to practitioner Y, who has specialization in Y. When

you have that sort of system, you lose a little bit of a holistic sense of what’s

going on with a person.” (Caregiver, M2)

Furthermore, when asked about their own involvement, patients did not identify themselves as, “a team member because I see the team as the people who have the knowledge,

130 and the experts, and directing activities” (Patient, M1), with one questioning how “normal [it is] for someone to be very involved in their care, to feel that they have something that they could contribute to it,” (Patient, M2).

Relational aspects of communication

Inquiry into current communication practices revealed that patients and physicians have preferences for communication modality that reflect their information and relationship needs.

While all physicians in the study used email and telephone with other physicians to acquire and convey information, some indicated that they do not use email with their patients because it could be used inappropriately (such as for time-sensitive matters). A few physicians did make themselves available by email to answer questions, which was acknowledged by patients as making them seem more accessible.

However, both patients and physicians were adamant that in-person appointments could not be entirely replaced because of the importance of physical examination and conversation to the relationship and sense of care:

“I think it’s important for the doctors to actually lay eyes on their patients

every couple of months. Especially in my scenario, to see if there is a

weight loss, a change in attitude, or whatnot because with the electronic,

you can hide your depression, and you can hide your loss of weight, or

lack of appetite, or your apathy.” (Patient, M3)

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As an oncologist stated, “I find it’s not usually a simple answer. It usually requires a conversation, and I don’t think emails are the best ways to have conversations.” (Medical

Oncologist, M0) Many patients stressed the therapeutic value of in-person appointments to the relationship they have with their healthcare team:

“I like being face-to-face and seeing the doctor and being able to know

that he’s a person and he has a sense of humour and whatever. It’s nice to

see them sometimes and get that interaction, the human interaction with

someone.” (Patient, M0)

Incongruence between technology and social norms of patient-physician communication

Patients, caregivers and physicians were asked about the use of web-based communication specifically, and emphasized that “electronic communication is good for certain things but not for everything.” (Medical Oncologist, M2) Physicians were concerned that web- based communication would make it difficult to set boundaries around availability to patients, as the following quote exemplifies:

“with some of the novel methods of communication it opens you up to

expectations around 24-hour communication by a particular provider. If

my patient has a question on a Saturday afternoon, I’m not working, but

they can e-mail me. Is the expectation that I answer it then? I think we

have to be very careful that we set expectations properly around when we

communicate about what, and we have mechanisms so people can turn

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off because otherwise I think there are going to be high levels of

burnout.” (Medical Oncologist, M0)

Physicians expressed concern that being continuously connected added burden to their already-busy schedules, but also for how it might redefine how care is provided. As one physician said, “I have concerns about boundaries that we set, on how people contact us, that it’s important to me to maintain that, those boundaries” (Palliative Care Physician, M0); email use could result in the boundaries that contain interaction between patients and physicians to appointments being crossed. From the patient/caregiver perspective, concerns about email also reflected an awareness of how busy providers are, “people don’t seem to read past the first couple of lines…I don’t know if everyone is so overwhelmed that they can’t compute or what,”

(Caregiver, M1).

Furthermore, “so much of the work that I do relies very heavily on cues from either body language or pauses in how they ask questions, or even tone of their voice, that I can’t infer any of that by email.” (Palliative Care Physician, M0)

Appreciation but apprehension about the role of the web-based communication tool for improving the experience of care

In asking about the Loop tool, participants uniformly appreciated the tool’s value for cross-setting communication with the different members of the healthcare team:

“that you have postings from people from different institutions, different

places, and they all appear at the time in the same way and everyone can

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read them if they’ve given access...that’s very helpful.” (Palliative Care

Physician, M1)

Healthcare providers thought the tool reduced patient anxiety of appointments being the

“only opportunity to talk to the doctor…And then, knowing that tool is there, they don’t necessarily ask that question unless it really does become an issue, rather than just asking it for the sake of asking because they’re worried they can’t ask it later.” (Medical Oncologist, M1)

Patients liked that with Loop, questions could receive a more timely answer between appointments, that the asynchronous nature of the tool reduced “telephone tag”, gave time to more carefully formulated questions, and that it allowed the amalgamation of information outside of appointment time. As a caregiver summarized, regarding Loop, “that gives [the patient] a little bit more of a sense that people are working together and looking at the person holistically.” (Caregiver, M2)

However, participants also expressed some apprehensions. Loop’s usefulness might be most apparent at only certain stages of treatment, and this may reflect differences in team member responsibility across stages:

“I think it’s of value for patients undergoing concurrent therapies or

undergoing their radiation or undergoing their chemotherapy. But once

that’s finished, at this stage, the usual follow up would be every three or

six months. And most patients don’t feel the need to communicate.”

(Medical Oncologist, M1)

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“I see doctors every couple of weeks, I have CAT scans, I have blood

work done so frequently, I'm not exactly sure how [the oncologist] would

fit in to my care at this point.” (Patient, M2)

Physicians expressed unease that introducing a new tool for communication may affect existing workflow, and patients acknowledged that they would not want use of the tool to add to their physician’s workload:

“I’m just one patient so hopefully the doctors, if they have 100 patients on

this, they don’t get inundated because then what’s going to happen is

they’ll start having to wait until the end of their shifts, just like they go

through all their messages.” (Patient, M3)

Participants echoed that Loop, as with electronic communication technologies in general,

should not replace in-person visits, because of the importance of such contact to their

personalized connection with their physician. This is despite the tool being introduced as

additional to, not replacing, usual care:

“I think there was, probably … there is a secondary therapeutic benefit

that comes from voice-to-voice contact that I think we have not yet been

able to replicate in other forms. I think my sister really valued that. I

wonder if that is, maybe, part of the barrier for specialists in fully jumping

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on board with these kinds of systems because they must be aware of that

therapeutic alliance piece, as well.” (Caregiver, M1)

DISCUSSION

Participants’ accounts reinforced existing evidence that poor continuity and coordination

are prevailing issues in the context of advanced cancer care. The intervention was intended to

connect patients and healthcare providers across settings and disciplines and, through

communication, facilitate patient participation in care management and decision-making. We

believe that the premise of inquiry on the value of a web-based tool for team-based

communication revealed tensions among patients, caregivers and physicians about the concepts

of team definition and patient-centeredness.

Participants recognized that the challenge around care coordination is due in part to changes in the physician most responsible for treatment varying along the course of illness. This may be aggravated by the absence of interoperability of electronic medical records between

different institutions, and in this context, augments care discontinuity between providers at the

cancer centers and those in the community. The difficulty that participants described in

identifying the members of their healthcare team appeared to be reflective of this issue.

Participants found that the time- and place-agnostic aspects of Loop were useful for allowing

providers to contribute accumulated knowledge and specialty-specific insight to ongoing care.

From a practical standpoint, its value may be seen as virtualizing the connection amongst the team to overcome the limitations of a constantly changing team, and thereby facilitating the assembly of a holistic picture of a patient’s health.

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While participants agreed that the tool serves such a purpose in principle, some anxieties

were expressed about how web-based communication is integrated into the patient-physician

relationship. Physicians worried that electronic communication, in general, might blur the

boundaries of contact from the confines of an appointment. Patients and caregivers expressed

that face-to-face appointments were central to their sense of feeling cared for. This was

something neither group wanted technology to supplant, and has been noted elsewhere about the

introduction of new interventions overall.326 A potential reason for these feelings, especially in

the advanced cancer context, is that appointments are important settings for empathic interaction

and social support.115 As a central function of clinical practice, empathy is linked to improved

emotional and medical outcomes.327-329 Defined as “the ability to understand and share the

feelings of another”330, the process of conveying empathy involves both expressing reactive

emotions, like concern, and reflecting warmth and compassion through body language and

nonverbal behavior331, which cannot be observed through text-based communication mediums.

In its reports about improving the quality and safety of care, the NAM stated that improving continuity of care through patient-centered, team-based delivery was needed. The report outlines ten rules for healthcare system redesign, among which is that “the patient is the source of control” over their healthcare decisions.20 In a 2009 article, Berwick332 commented that this rule reflects a consumerism approach to care and comes into conflict with the concept of a profession. Citing sociologist Eliot L. Freidson, he notes that expertise, along with altruism and self-regulation, are tenets for why society grants authority to professions. Some patients in our study made the distinction that team members are those with the expertise to direct care activities and therefore felt that they did not identify themselves as part of the team. Our findings seem to suggest that the reassurance which patients expect from their provider often needs to be received

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from an individual they view as having expertise/authority, such as a physician. While electronic

communication may provide a new opportunity to democratize decision-making by facilitating

greater information exchange with patients, patient-driven care, which some may interpret is

encouraged by communication tools, may be misaligned with the expected therapeutic role of

physicians.

Much research into team-based care confirms the complexity of collaboration and its impact on perceptions of patient-centeredness and decision-making. Several critiques of interprofessional team-based care have revealed gaps between its conceptualization and implementation in practice, some of which are made particularly visible by the introduction of

the web-based tool for team-based communication that takes the presence of established

collaboration as its starting assumption.333,334 These may include lack of established roles, shared

goals, leadership etc.307 Studies of patient-centered decision-making stress approaches that involve partnership and support without overshooting on patient control; patients who appear to resist involvement in decision-making may rather want their choices to be validated first by the opinions of experts.335-337 Interpreted in the context of our study, we recommend that introducing

a new technology cannot be done in a technology-centric fashion. Implementation recommendations often emphasize end-user engagement as central to technology uptake,338,339

however, we further contend that implementation requires cognizance of the dynamics that

already exist in the relationship between patients and physicians at the individual and

interprofessional levels. Future work might consider implementation that entails facilitated

discussion between the patient/caregivers and healthcare providers (especially the team) around

expectations of use to meaningfully integrate novel innovations into communication practices.

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Limitations

This study has several limitations. We conducted this study in the context of an ongoing clinical trial; while the trial design was pragmatic with little instruction as to how the intervention was to be used, the artificial nature of randomization and positivist approach of trials may limit the participant sample and thus variability in perspectives.340 Our analysis was limited to participants in the intervention arm who registered to use the intervention and we have not explored the opinions of those who chose not to participate. However, analysis of intervention participant interviews that had at least a baseline and at least one monthly follow-up interview was conducted until categorical saturation, suggesting that further analysis would be redundant. Interviews were not conducted with additional providers of the healthcare team due to feasibility constraints. However, such perspectives may be valuable in understanding role perceptions by those providers less immediately involved in care. Our study was conducted at two academic hospitals in an urban area in the Canadian province of Ontario and our findings may not transfer to settings where specialist care resources or access to the internet differ. Lastly,

Ontario has a universal health insurance program and this may influence the expectations of participants regarding connectedness of physician services between institutions within this province.

CONCLUSION

In this study, we explored the perspectives of patients, their caregivers and cancer physicians on the value of a web-based tool for team-based communication. In an era where innovation in eHealth is implemented faster than it can be studied, our findings suggest that the introduction of technologies must take into account the potential perceptions of disruption to the

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patient-physician bond, even when a new tool is not intended to replace face-to-face meetings. It

also highlights the sometimes opaque understandings held by both patients and providers of what

constitutes team-based care, including confusion regarding who is a team member, and at what

time points. This confusion can be exacerbated by the fluid nature of care needs throughout the

cancer journey. Our findings seem to suggest that introduction of the tool alone cannot broaden

communication opportunities between patients and the team without negotiating the

undercurrents of the relationship, existing care practices, and patient preferences. However,

through facilitated implementation entailing discussion about expectations of use, the tool can

present an opportunity to realign the goals and expectations of the patient-physician relationship.

As such, electronic team-based communication may be a way to redefine patient- physician/whole team relationships and to make care more patient-centered.

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ACKNOWLEDGMENTS TV, EG, AH and FW were involved in study conception. TV, EG and FW were involved in study design. TV wrote the study protocol. TV and a research assistant were involved in acquisition of data. TV and FW were involved in analysis. TV drafted the manuscript and all authors contributed to revisions.

T. Voruganti is supported by a Canadian Institutes for Health Research MD/PhD studentship and McLaughlin Foundation fellowship. E. Grunfeld is supported by a clinician-scientist award from the Ontario Institute for Cancer Research (OICR) and the Giblon Professorship at the Department of Family and Community Medicine. F. Webster is funded by a Canadian Institute of Health Research New Investigator Award.

The MyTOC trial was funded by a grant from the Academic Health Science Centre Alternative Funding Plan Innovation Fund- Mount Sinai Hospital/University Health Network Academic Medical Organization and the Temmy Latner Centre for Palliative Care.

CONFLICTS OF INTEREST: The authors have no conflicts of interest to disclose.

ABBREVIATIONS: NAM- National Academy of Medicine AHRQ- Agency for Healthcare Research and Quality

CHAPTER 5: DISCUSSION AND SYNTHESIS

5.1 Summary of Results

The purpose of this dissertation was to examine digital health tools for patient-provider team-based communication, their feasibility in practice, and role in improving continuity of care.

Three studies were conducted on tools for enhancing team communication in the care of patients with chronic conditions.

In the first paper, a scoping review was conducted of web-based tools for text-based

communication between patients and providers in the chronic disease setting. A number of

studies that evaluated communication tools were identified in the published literature. The

majority of tools were multidimensional, having features and functions in addition to

communication such as access to an electronic medical record. Only 8 tools from the published literature search were described as patient-provider tools with team-based communication functionality (it was unclear in 7 cases whether these followed one-to-many or many-to-many paradigms); two tools from the internet search were described as allowing the patient to communicate with the team (the paradigm was also unclear). The majority of tools were studied in diabetes and chronic respiratory conditions for purposes of patient self-management, including lifestyle modification/behavior change and symptom reporting. One was evaluated in the cancer care setting.

In the second paper, the feasibility trial, a new web-based tool for team-based communication, called Loop, was evaluated in a population of advanced cancer patients. The

Loop tool was used for purposes of medical care management, symptom reporting, and appointment coordination. Results showed that the feasibility goals were met and a numerically- higher score was observed on the continuity of care measure comparing mean change scores

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between the intervention and control arms. Negligible changes were observed on the quality of

care and symptom distress scores.

In the third paper, the qualitative descriptive study explored trial participant perspectives

on the value of patient-physician communication via electronic mediums in general and the Loop

tool specifically. Participants valued the ability to use Loop to communicate with the team,

appreciated that such communication tools enable greater access to healthcare providers, and for

the opportunity to communicate between appointments. However, patients and physicians

expressed that appointments were crucial to the therapeutic relationship, asserting that they should not be supplanted by web-based communication tools. Findings suggested that introduction of a new technology, especially one involving interpersonal interaction, such as a patient-provider communication tool, should consider existing relationship dynamics during implementation.

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5.2 Interpretation

In Chapter 1, the eHealth Enhanced Chronic Care Model (eCCM) was introduced

(Chapter 1, Figure 2, pg. 34).153 It builds on Wagner’s original model, which was arranged around the community and health system. The eCCM advocates that chronic disease care should encourage patient self-management supported by productive interaction between an informed, activated patient and a prepared healthcare team.152 Major aspects of the model included delineating the overarching organizational settings (Community, Health Systems, eCommunity, eHealth) and enhancements brought about by health information technologies. Supported by a systematic review,154 it suggests that technologies, such as digital health tools for communication, which complete the communication feedback loop between patient and team, should improve outcomes.

The overall rationale of this dissertation builds from this framework: in the care of patients with complex care needs, the implementation of a web-based tool for patient-provider team-based communication may potentially improve patient outcomes including continuity of care. This is because the tool facilitates a complete communication feedback loop with healthcare providers on their care team across health encounters (see Chapter 1, Figure 3, pg.

37).

Presented below is a discussion of how the studies relate to this overall rationale followed by a discussion of the impact on continuity of care in the feasibility trial and qualitative study, and a discussion of the implementation of web-based communication in the context of team- based care.

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5.2.1 Relation to the rationale

The results of these three studies support the overall rationale in several ways. Firstly, findings affirm the supportive care element in chronic disease care posited by the eCCM framework. The scoping review identified that the main intended uses of patient-provider communication tools were for supported self-management purposes such as symptom reporting and lifestyle/behavior modification. We found that most tools were found in chronic disease contexts with strong self-management components, such as diabetes and chronic respiratory conditions. It was similarly observed in the feasibility trial that the content of messages posted to the Loop tool was mostly related to self-management and supportive care. Secondly, the trial setting represented a typical “connected” organizational setting in which the eCCM framework applies, and thus where the proposed rationale (as described above, and in section 1.5, Figure 3, pg. 37) may occur. That is, participants were comfortable with computers and the internet; physicians were very comfortable and used them frequently. Thirdly, in the qualitative study, patients expressed appreciation for the greater accessibility to healthcare providers offered through the tool which can allow for opportunities to provide updates outside of appointments.

This reinforces the opportunity for productive interaction facilitated through digital health tools.

Use of the tool by both patients and providers suggests that a communication feedback loop did occur. We did not observe changes in the distal outcomes in the feasibility trial. This may be explained by the 3-month duration of follow-up in the trial which may be too short a time for changes in quality of care or healthcare utilization to be observed. It is also possible that other factors influencing such outcomes have not been considered - perhaps a threshold of communication via the tool was needed, or perhaps other associated factors such as healthcare

145 needs or quality of life295 were already sufficiently addressed. Further discussion of how continuity of care was affected is presented below.

5.2.2 Continuity of care

Regarding the expectation of improved study outcomes, the trial and qualitative studies revealed interesting findings regarding continuity of care. Higher scores on the continuity of care measure were observed in the intervention arm compared to the control arm of the feasibility trial. In recognition of potential biases that might affect trial results, this points to the possibility of finding a difference in continuity of care in an adequately-powered study. The result from the qualitative study also reaffirmed this hypothesis, with patients and providers appreciating the tool’s ability to connect them to the team members from different disciplines and settings.

As outlined in section 1.3.4, the Haggerty et al.4 definition of continuity of care is “the delivery of services by different providers in a coherent, logical, and timely fashion,” which the authors have further deconstructed into three dimensions of informational, management and relational continuity. Considering the proposed rationale (Chapter 1, Figure 3, pg. 37), a tool which allows for team-based communication and facilitates the feedback loop suggested by the eCCM, should theoretically improve informational (sharing of information across events and over time), management (cross-disciplinary communication of care plans), and relational

(ongoing therapeutic relationship between patient and providers) continuity.

In the trial, content analysis of messages could suggest that informational continuity and management continuity were supported by the tool (e.g. message categories of Updates, Medical

Care Management and Appointment Coordination). However, in the qualitative study, participants’ statements that electronic communication should not replace in-person

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appointments (despite the tool being explicitly described as supplemental to appointments)

emphasized the perceived importance of face-to-face appointments to the therapeutic relationship, and by extension, relational continuity. These findings could suggest that web-based

communication may threaten this domain of relational continuity of care without careful

consideration of the existing interpersonal dynamics between patients and physicians. However,

these notions warrant further study to draw firm conclusions. While an ongoing relationship is maintained on web-based communication tools, the therapeutic value of the relationship may be impacted depending on whether the relationship is founded on medical information provision vs. social support (or other purposes).

Drawing on different sources of data, in these studies, the informational and management components of continuity of care may be interpreted as potentially being helped by the tool, but further consideration of how these communication tools can be used to promote relational continuity is needed. Further comparison with other similar studies is presented below in section

5.3.2.

5.2.3 Team-based care

The three studies also revealed important findings regarding team-based communication.

The scoping review identified 8 tools from published articles that claimed to allow patients and multiple healthcare providers to communicate with each other, though descriptions of the communication paradigm (i.e. one-to-many, many-to-many) were vague. In a few studies,217,266 it

was stated that patients could send messages which would be relayed by a nurse or research

assistant to other members of the care team; that is, communication with each individual member

of the care team was not simultaneous. Only one study287 made explicit reference to allowing for

147 patient-provider and interprofessional communication (many-to-many), indicating that in the field of healthcare, web-based, asynchronous communication among teams is still rare.

In the trial, assembling care teams to use the tool proved to be challenging. Only half of the additional healthcare providers suggested by patients participated, and community-based specialties were not well-represented. Only half of additional healthcare providers who took part in patient Loops were from practice locations different than the patient’s cancer physician

(“initiating healthcare provider”). Additional providers who were contacted but did not participate either did not respond to requests to participate or they indicated that they were too busy to participate. The difficulties in recruiting additional providers and assembling the team may be multifactorial. As described in our qualitative study, burdening busy providers, integration into clinical workflow, and appropriateness at various points in care were raised by participants as concerns around using the tool. In the cancer context, where provider responsibilities are dependent on stage of disease and phase of treatment, lack of involvement in direct care may have been a mitigating factor to provider participation in the trial that could not be overcome by the provision of the tool. This may be reflective of unclear roles for additional providers at different points in the cancer care trajectory. This may suggest that for the tool to be optimally-used, the implementation context should be one in which multiple providers already function as a team or implementation must make use of the tool as a component of the team building process in order to facilitate participation by all team members.

In an effort to examine the patterns of communication in this study, Jamieson (2017; unpublished)169,341 performed a social network analysis of communication within the Loops from this trial, examining such dimensions as who participants communicated with, how frequently, and in what direction communication flowed. This analysis can be used to shed light on the

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extent and nature of collaboration. It was observed that patients and caregivers (analyzed

together as a unit), who as focal points of interaction (“hubs”), were central to information

transfer (“brokers”) and their participation was important to teams being less fragmented. This

suggests that collaboration occurred via patients/caregivers, who were thus integral to teams in

this study. Therefore, it was not apparent that provider-level team functioning (multiple professionals “[collaborating] to accomplish shared goals across settings to achieve coordinated, high quality care”12) was affected by the tool with the implementation approach taken in the trial.

In the qualitative study, a major theme was “uncertainty in defining the circle of care.”

Some patients hesitated to identify themselves as members of the team, distinguishing providers

as those with expertise. In section 1.4.3, the confluence of patient-centered care, evidence-based

medicine and health information technologies, was posited as reorienting the traditional provider

role from being arbiters of healthcare to partnership with patients in a role of information

integrator.130 The findings of the qualitative study and the patterns of use in the trial (and social

network analysis) revealed a contradiction whereby patients’ expressed discomfort in being a member of the team, but were integral to provider communication on the tool. This may support a conceptualization of patient-centered care that likens patients themselves as having an integrator role supported by providers, but not as authorities of their own care.

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5.3 Comparison to the Literature

5.3.1 Web-based tools for patient-provider communication

As outlined in the first chapter, tools to support team functioning are not novel outside of

healthcare. However, the scoping review revealed few digital health tools for team-based

communication in the care of chronic conditions. One tool, by Gulmans et al.,287 was identified which shows some similarities to the Loop tool. Evaluated in the pediatric care setting of cerebral palsy, the tool was described as “an asynchronous secure web-based system for parent- professional and interprofessional communication.” The tool aimed to improve provider to

provider contact between disciplines previously less involved in care, keep every provider up to

date between visits, and allow the parents of patients to communicate with all providers in the

network through multiple threads. In a six-month pilot observational study, parents felt that the tool improved accessibility, timeliness of information exchange and “sufficiency of contact” with providers. However, participation varied greatly, with only 2/3 of parents using the system.

Parents indicated that the system did not improve consistency of information between providers.

At the end of the study, more than a third of parents who used the system felt they still acted as

the coordinator of information between professionals. The description of study enrollment of the

healthcare provider network was not clear, but the authors indicated that allied health

professionals (e.g. rehabilitation specialists and physiotherapists) responded to participant

questions more frequently (90% of questions) than other professions. In comparing the Gulmans

et al. study to the feasibility trial here, it is evident that such tools can improve patient access to

the healthcare provider team outside of appointments. However, as both these studies indicate,

clear challenges remain in getting the full team of providers involved to use the tool, which may

be necessary to reduce the burden of care coordination on patients/caregivers.

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Varsi et al.342,343 conducted a study on barriers to use of an internet-based patient- provider communication tool in a cohort of patients discharged from hospital who required outpatient follow-up. They identified that workplace culture and readiness for change were barriers to implementation. Sufficiency of current information and preference for other communication modalities were reasons for non-use. As corroborated by our findings, the introduction of communication tools in clinic practice is not a static process. Implementation strategies recognizing workflow, communication preferences and culture are critical to promote both uptake and sustained use. In our study, the pragmatic approach to implementation entailed minimal instruction both reflective of the intuitive design of the Loop tool and the belief that each team may adopt the tool according to their contextual needs. However, with communication tools, unlike most other health information technologies, existing communication dynamics and etiquette possibly point to a need to consider implementation tailored to the individual patient- provider/whole team level, beyond consideration of broad patterns of clinic workflow or typical patterns of care.

5.3.2 Continuity of care in relation to the existing literature

In the scoping review, none of the identified articles on web-based tools for patient- provider, text-based communication examined continuity of care as an outcome; most studies either focused on impact on medical outcomes (like HbA1C control) or development and implementation outcomes (like feasibility, usability etc.). However, as a concept representing the coherent experience of care and connectedness at the information, management and relational levels, it is an important outcome to be considering in patients with chronic conditions, especially in patients with complex care needs.

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In the feasibility trial and qualitative study, coordination of care appeared to be impacted

but more consideration of how relational continuity could be affected by electronic

communication tools is necessary; further study is needed to establish evidence of association.

The expectation of such tools is that having an additional channel of communication with

healthcare providers should improve the patient-provider relationship because of increased accessibility to providers.168,344,345 In a study by Lyles et al.,346 on patient portal use for patient-

physician communication, it was found that patients emphasized that in-person provider

interaction was important to the therapeutic relationship, even when tool use was not meant to

replace appointments. These findings, much like ours, suggest that patients place a high value on

appointments as a means to receive care. In some cases, the need may be more from a supportive

care perspective instead of direct treatment. As discussed in section 1.3.5 on Communication in

healthcare, face-to-face patient-provider interaction is an important element of social support and

exchanging empathy. In the advanced cancer context, appointments are crucial facets of coping

with illness and are themselves therapeutic.115 From an implementation standpoint, it also

suggests that guarantees from researchers during the consent process that electronic

communication will not replace appointments may be insufficient, and that reassurance from

providers themselves is needed.

Relational continuity is experienced as sustained contact with provider(s) across

disconnected events, and seeing the same provider(s) at different visits (“provider

consistency”).74 For patients, this denotes security, predictability and confidence about future care, and is built on empathy and trust developed over time.75 However as a result, relational

continuity is most often focused on the care received by a single provider, with some research

suggesting that team-based care models may disrupt relational continuity.347,348 This may be

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because of the difficulties inherent in maintaining a close relationship with multiple providers

concurrently. Furthermore, in the cancer context, care responsibility by providers is transient

based on treatment modality, thus it may not be reasonable to expect relational continuity to be

sustained over the course of care. While informational and management continuity entail

provider- and team-level connectedness, these are less easily discernable with relational

continuity. This may suggest that further distinction within the dimension of relational continuity

between patient-provider and patient-team relationships are needed to acknowledge the different

quality/nature of interaction and closeness at these two levels. Measurement tools, like that by

Haggerty et al.,85 are first steps towards establishing this as an accepted aspect of team-based

interaction.

5.3.3 Team-based care in relation to the existing literature

Research into teams from healthcare and broader contexts can provide insight into the

patterns of use and extent of collaboration in the evaluation of Loop. As described in section

1.3.2, Boon et al.57 outlined a conceptual framework for team-based care that spanned team

structures from working in parallel, as independent units within a “formally-defined scope of

practice,” to integrative practice, with “interdisciplinary, non-hierarchical blending.” In the middle of the spectrum were coordinated (sharing of information among a team who

“intentionally gathered to provide treatment for a disease”) and multidisciplinary (team managed by a leader who integrates decisions produced independently by members) designs. We observed in the trial that patients posted and viewed content in their Loop more than physicians, that the

content of the messages tended towards patient-driven coordination topics (e.g. Updates,

Symptoms, Appointment Coordination), and, as the social network analysis by Jamieson

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(2017)169,341 showed, patients/caregivers drove use of the tool. Within the limitations to

interpretation (given the variability with which additional providers participated, and the limits

of a patient’s medical knowledge to lead care decisions), it appears that patients functioned as the

integrator and initiator of information exchange in the feasibility trial. Applying the terminology

from Boon et al., this positioned teams in our study between coordinated and multidisciplinary

on the spectrum, where the patient is the integrator. However, as discussed in section 1.3.1 on

Complex Care Needs, the notion of patients as shouldering the burden of care coordination was

the initial issue to be addressed.

This does not indicate a failure of the tool’s immediate objective or the endeavour of

electronic communication tools in general: communication did occur, it occurred between

appointments and the tool did appear to improve accessibility to the healthcare team. However,

in the complex patient population, where interrelated issues require shared decision-making to be

best addressed, collaboration among providers is needed. As suggested by Denise (2012),349

“collaborations are interpersonally rather than structurally determined,” implying that perhaps a

functional rather than structural lens is needed by which to consider teams (structural referring to

team structure and functional referring to the activities of teams). A horizontal integration

continuum has been used to describe team function from fragmented to fully connected.334 It

delineates the extent of connectedness from cooperation to coordination to collaboration (the

“3Cs”); individuals working in teams are not collaborative, initially.306

Reflective of the principles of team-based healthcare highlighted in the NAM discussion

paper described in section 1.3.2, the important components of effective teams are known, but

arriving at effective team functioning is often a context-dependent development process. At first, team assembly involves developing a shared identity, outlining clear roles and responsibilities,

154 fostering a non-competitive culture, and agreement on leadership.333 These efforts establish common ground – the shared beliefs, knowledge or language between individuals necessary to negotiate decisions.307 Collaboration can develop with ongoing interaction built on trust and commitment toward a mutual goal. The inference is that past experience of working together as a team may facilitate future productive collaboration. Indeed, in examining patient-physician communication with text-messaging, email, or mobile phones, a recent study showed that benefit was most likely where patients already had a relationship with their healthcare providers.350 In the context of the feasibility trial, it was expected that team functioning could be improved with a team-based communication tool. However, the tool itself only provides a channel for communication; prior team development may be needed to optimize how a tool like Loop can be used to facilitate collaborative care. Furthermore, involving the patient as a component of collaboration compounded by their dual role as the subject of investigation/treatment may further affect (either in a supportive or detrimental way) the development of strong collaboration.

In considering team-based communication as a means to improve coordination and care integration amongst the team of healthcare providers, literature from outside of healthcare can also provide insights into how these ideas may be considered. In particular, the concept of relational coordination, first develop by Gittell et al.351 based on work in the aviation industry, endeavours to connect aspects of “a network of communication and relationship ties among workgroups engaged in a common work process.”352 According to Gittell’s relational coordination theory, the communication dimension is considered in terms of frequency of communication, timeliness of communication, accuracy of communication, and extent of

“problem-solving communication”; the relationship dimension is considered from an individual’s perspective of how others in the group are performing in terms of helpfulness,

155 having shared goals, shared knowledge, and mutual respect.353 Relational coordination is thus defined by Gittell et al. as “a mutually reinforcing process of communicating and relating for the purpose of task integration.”354 The validity of this theory was assessed in the aviation industry, and Gittell found that airlines with higher relational coordination among different workgroups

(gate attendants, baggage handlers, ticket counter clerks etc.) were more efficient, had higher job satisfaction among workers, higher customer satisfaction, and ultimately, higher quality of performance.351 Relational coordination could be applied in this context: Loop itself may serve as a venue for making communication more frequent, accurate, timely and (possibly) more collaborative. Such communication may therefore enable sharing goals and knowledge, and reinforce mutual respect among providers. Measurement of relational coordination may also serve as a means to gauge effectiveness of teamwork. However, as stated earlier, implementation efforts to encourage use of the tool are a necessary first step towards making use of it to improve team functioning.

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5.4 Strengths and Limitations

The limitations of each study are presented in their respective sections. However, there are a number of considerations pertaining to this dissertation as a whole warranting discussion.

The overall purpose of the dissertation was to examine tools for patient-provider team-based

communication, their feasibility in practice and role in improving continuity of care.

In the scoping review, the focus was on web-based tools for text-based communication

between a patient and their provider(s) in the chronic disease context. From the perspective of this dissertation, the scoping review found that tools similar to the Loop tool are rare, and that

there are few such tools in the contexts of cardiovascular disease and cancer. It is possible that

barriers to use/implementation have prevented such tools from being adopted (or evaluated and

published) in these contexts, and thus were not captured here.

The second study employed a pragmatic RCT design to assess feasibility of the Loop

tool. The pragmatic approach to implementation reflected the intuitive usability of the tool and

the intention for it to be used by teams, as needed. The benefit of the pragmatic design is that the

study findings are likely generalizable to other contexts. However, the minimalistic approach to

introducing the tool, which involved explaining and setting up accounts on Loop at the time of

consent, may not have appropriately recognized components in the implementation context, such

as existing communication dynamics, which may influence how participants would use Loop.

We could not adequately measure communication which occurred between participants outside

of Loop (i.e. if emails were being exchanged). The intervention required involvement from

providers as well as patients. As a result, recruitment of patients was restricted to those whose

providers were willing to participate, which limits generalizability of results to all patients and

providers. The prospective sequential approach to recruiting patients may have contributed to

157 selection bias as not all eligible patients of participating providers were invited to participate.

This was determined to be the most feasible approach to recruitment given study resources and the anticipated small sample size of the study. The duration of follow-up (3 months) was selected to reflect the approximate prognosis of advanced cancer patients seen at the study centers.

However, it is possible that this was not long enough for participants in the intervention arm of the study to become comfortable with the tool and build a protocol for communication (i.e. expectations and convention of contact over the tool). It is also possible that with a longer period of follow-up, the content and pattern of interaction would have changed. In this trial, it was assumed that the providers identified by patients were involved in the patient’s care in some capacity, and that connecting these individuals would enable collaboration among a team with variable overlap in communication. However, we did not assess the extent of team functioning prior to the trial because healthcare providers were first identified by patients during the trial enrolment process. As team members were identified by patients, it was also unclear whether providers viewed themselves as functioning as a team. These may be important metrics to capture at baseline for the purpose of comparing improvement in collaboration with use of a tool like Loop in future studies with such a goal. Similarly, implementation measures such as patient- level readiness and perceived need would have been useful for gauging change over the course of the study and to explain patterns of uptake. Finally, a global measure of coordination and continuity of care was used. The Picker scale, though validated in the cancer population, was primarily designed as a hospital/health system quality evaluation instrument, and thus may not reflect the full breadth or patient-oriented perspective of the continuity of care concept as defined by Haggerty et al.4 Newer instruments to measure continuity of care84,85 also include measurement at the team-level but have not been validated in the advanced cancer population.

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Assessment with these instruments may provide greater continuity of care component-specific

insight into perceptions of continuity of care, including patient understandings of relational

continuity among the team.

Lastly, the qualitative study was conducted concurrently with the feasibility trial as a

multimethod design, which enabled data collection to occur while participants were actively

using the Loop tool. However, trial constraints on data collection limited the methodological

approaches that could have been adopted. Approaches such as grounded theory,355 for example,

would have been appropriate if the objective was to gather further depth on perceptions related to

continuity of care and the connection to patterns of tool use. This is because attributes such as

theoretical sampling of participants enabled by simultaneous data collection and analysis

(“constant comparison”) are conducive to theory generation. In contrast, mixed methods designs,

in which different methods are used to answer a shared study question,177 have been used in

clinical trials to fulfill exploratory or confirmatory purposes.340 A mixed methods design might

have been useful to support further understanding of the role of patient-provider team-based

communication tools on continuity of care but would have been challenging to ask about directly

to study participants, given the multifaceted nature of continuity of care356 and the desire to begin with an understanding of the value of such digital health tools.

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5.5 Summary of Implications

The findings and their implications to the feasibility of team-based communication tools

and their role in improving continuity of care are discussed.

First, the scoping review found that tools for team-based communication are rare and few

have been studied. Only one identified tool was described in similar conceptual terms, as

intended with the Loop tool, of concurrent asynchronous, text-based communication with multiple providers as a means to promote team-based care. Most patient-provider communication tools with one-to-one communication flow were intended to facilitate provider-supported self- management. However, in the care of patients with complex conditions, tools for team-based communication have utility beyond this, aiming to integrate information and management across providers to make care more connected and coherent. Few tools were identified in the CVD and cancer contexts, and none were found in these disease contexts for team-based communication.

As these are chronic conditions which typically involve multiple providers, we have potentially

identified a gap in the research literature.

Second, as an early trial of a web-based tool for team-based communication, it was found

that web-based communication between a patient and their healthcare providers is a viable

means to connect participating team members. Compared to the alternative methods of

communication, which are driven by provider motivation over patient need and typically entail

each provider on a team using one-to-one paradigms of connecting, these feasibility results are an intrinsically important step to improving communication among teams. We also observed higher patient-reported continuity of care scores in the intervention arm relative to the control

arm at 3 months follow-up. These findings do not constitute statistically-supported evidence of association but do warrant proceeding to a sufficiently-powered study to draw firm conclusions

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about the relationship between the intervention and outcomes. We also found in the qualitative

study that participants felt the tool’s value may be greater at certain points in care, that patients

were aware of (and possibly apprehensive about disrupting) providers busy schedules, and some

felt a need to maintain appointments for secondary supportive benefits. These findings suggest

that agreement between patients and providers is needed around expectations of use.

Third, the tool was used as a medium for communication among multiple providers but

itself did not appear to change how care-based interactions as a team were carried out. Findings

seem to imply that team functioning was not affected by the tool, and simply making the tool

available for use may be an insufficient strategy to improve team functioning. Efforts to build

collaboration among providers so as to promote team functioning may need to happen in parallel

to effectively impact clinical outcomes in patients with complex care needs.

Finally, a crucial learning from these studies is that success is predicated on an effective

approach to implementation. In the trial, assembling the team was found to be challenging

because of difficulty in recruiting team members identified by patients. Along with findings

about team functioning, this suggests that team-centered introduction of the tool is needed to

foster collaboration on the tool, which can itself facilitate, but not stimulate, collaborative care.

As found in the qualitative study, and in the literature,357 barriers to implementation of these

tools include, among others: provider busyness, workplace culture, clinical workflow, clinical

need and sufficiency of existing modes of communication. However, our findings further suggest that implementation must also be patient-centered, reflecting the variable interpersonal dynamics of communication between various patients and physicians.

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5.6 Knowledge Translation and Future Research

A critical aspect of clinical research is the uptake and use of generated knowledge.

Knowledge translation “includes the synthesis, dissemination, exchange and ethically sound

application of knowledge to improve health,…” and, “is a move beyond the simple

dissemination of knowledge into actual use of knowledge.”358 Straus et al. (2009)358 presented a

model called the Knowledge-to-Action cycle which distinguishes between knowledge creation

and action phases. In addition to publication in peer-reviewed journals and presentation at

academic conferences, making knowledge actionable involves engaging with stakeholders

(including policymakers, funding bodies, clinicians etc.) who will make use of high-quality

knowledge. The Loop initiative has involved stakeholders throughout the development and

evaluation phases. However, much of this work falls within the knowledge creation phase of the

cycle and is supportive of future research, as detailed below.

The scoping review was a necessary step in summarizing the current landscape of web- based tools for patient-provider, text-based communication. Without this understanding, what efforts have already been made to understand these types of communication tools could not have been known. The realist review framework is another approach to synthesizing the literature with

“an explanatory rather than judgmental focus.”359 Capturing context, mechanism, and outcome, a realist review approach might take a further step of understanding how intended uses of patient-

provider communication tools map onto study outcomes, and contribute to a better understanding

of optimal implementation.

The feasibility trial suggested that implementation of the tool was feasible and further

study to establish its effectiveness is warranted. The design of the trial had appropriately mapped

onto the next expected phase of evaluation from previous work168 according to the MRC

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Framework for the Evaluation of Complex Interventions.161 However, the field of eHealth evaluation has evolved in its philosophy towards the sequential approach to evaluation with

RCTs (Phase I to Phase IV) over the last decade. It is argued that traditional RCTs cannot adequately capture the complexity of digital health interventions, given the influence of context, users, readiness, competing/alternative/existing interventions, social and organizational culture etc.155,174,206 Newer evaluation frameworks contend that explaining and revising are, “essential in a multifaceted program whose goals are contested and whose baseline is continually shifting.”155

For example, Mohr et al. (2015)360 articulate that typical clinical trial frameworks are restrictive by virtue of their originating from pharmaceutical evaluation. While pharmacological interventions are expected to function in a physiologically similar manner from patient to patient, efforts to impose comparable rigor in complex intervention evaluations (psychological/ behavioral programs etc.), in order to maximize internal validity, force constraints on adjustments to the intervention. In the case of digital health interventions, improvements to keep up with the technology or a changing study context are not allowed. The authors argue that over a long study duration, or if issues with the intervention are discovered during the trial, this restriction limits the value of the RCT by the time the study is completed. Instead, the authors propose that trials of complex interventions should evaluate the principle or mechanism of action of the intervention (termed Trial of Intervention Principles (TIP)) instead of the intervention as a whole. So long as the clinical aims and behavioural strategies that compose the principle of the intervention are maintained, minor changes to the usability or characteristics of the intervention

(“instantiation components”) are allowed. Unlike adaptive trials361 which aim to adjust the study design (allocation ratio, intervention dose, duration of follow-up etc.) by discretized quantities

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that can be adjusted for, adjusting the intervention must be carefully planned (and reported) if

causation is still to be inferred.

Pagliari (2007)362 proposed a model combining phases of development and evaluation,

drawing on methodological approaches from health services research and software design. The

model uniquely envisions evaluation as a series of cycles continuous with one another,

oscillating between concept and prototype evaluation, evaluation of impact, and pragmatic

evaluation. Inherent in each cycle is refinement of the intervention, assessing impact and

considering implementation. The author suggests that the evaluation of digital health

interventions should therefore involve transdisciplinary expertise to inform the intertwining of

these steps. The reason for new evaluation approaches and main arguments118,363,364 against traditional RCTs relate to their focus on establishing efficacy to the exclusion of understanding context, process, and reason for effect. Thus multi-method approaches are recommended to capture both quantitative and qualitative data.

However, beyond RCTs, few other methods can control for both known and unknown confounders. Furthermore, stakeholders (which, in eHealth, are responsible for substantial investments towards design/development) demand demonstration of effectiveness to justify broad implementation. In this dissertation, the difficulties with team assembly and variable use

of the tool by different teams suggest the need for further investigation into both effectiveness

and implementation. Curran et al.228 have proposed hybrid trial designs which pursue simultaneous effectiveness and process evaluations to inform principle and practice. These study types fall between the effectiveness and implementation segments of the efficacy-effectiveness- implementation pipeline.228 Beyond what was done in this trial, which entailed capture of both

quantitative and qualitative data around the clinical intervention itself, a co-primary aim of

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hybrid trials is to field implementation strategies of the intervention. Pursuing such a design for

future study of the Loop tool would enable further investigation into the issues with

implementation observed in the feasibility trial.

Furthermore, in considering the intervention itself, the tool has received positive

feedback conceptually and from the perspective of design/interface.168 As suggested in section

5.5, the bottleneck to realizing team-based communication as a means to reduce the burden of

coordination from the patient was in assembling the team on the tool. Implementation efforts

focusing on team assembly and collaboration which use the tool as a facilitating medium may

better tailor tool use to the needs of the team. As described in section 1.3.2, checklists,65

education,66 team-building workshops63 have been effectively demonstrated to improve team functioning. Factorial designs would allow for the assessment of impact of the tool vs. tool +

implementation approach vs. control.364

In the eHealth development literature, it is common to perform clinical workflow

evaluations as part of ethnographic study or prototype testing. These assess a clinician’s

activities, roles, and utilization of health information technologies with the aim of optimizing

design and implementation around the workflow of an individual.365 Alternatively, it has been

proposed that such analyses should shift the focus from clinician to patient, suggesting that

patient-oriented workflow models, which view care delivery with the patient as the reference

point, may provide a more comprehensive look at the sequences of activities by multiple

providers and their temporal contributions to care.366 Taking a similar perspective to tailoring

tool use to the relationship between the patient and their team may minimize perceptions of

interference.

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Implementation frameworks, such as the Consolidated Framework for Implementation

Research (CFIR),339 outline factors for consideration to guide implementation approaches,

although how each factor pertains to the study at hand specifically needs to be considered.

Regarding immediate future evaluations of Loop, some considerations based on CFIR might

include: a) training for participants, b) consideration of the degree of healthcare needs of

patients, as a study inclusion criterion, based on stage of illness or phase of treatment, and c)

involving local champions/leaders to assist in tool promotion at an organizational level. Long-

term development may consider system integration and interoperability with electronic medical

records, as a means to combine information storage with the communication. Strategies to

incorporate financial incentive/compensation to support provider time for using this new

modality of engaging with patients may also be needed.

Future evaluations might also consider different study contexts, as the Loop tool was not

designed exclusively for use in the advanced cancer population; some patients suggested that

having access to the tool when they were first diagnosed with cancer might have allowed for conversations on Loop to chronicle their experience for their team of providers. Further understanding is needed on how asynchronous, team-based communication tools can be used in scenarios where “distance-monitoring” is required, such as for patients live who far away from the cancer center wanting to remain connected to providers for non-urgent, ongoing monitoring and management. As the studies here suggest, further qualitative investigation is needed to understand how to encourage healthcare providers to participate, and explore the incongruence between how patients identify their team and how providers define the patient’s care team.

CHAPTER 6: CONCLUSION

The burden of chronic diseases is forcing changes in the practices and protocols of healthcare delivery, and increased reliance on information technology is seen as one of the solutions. Our research has shown that team-based communication tools may be eminently- suited to fulfill the complex needs of advanced cancer patients receiving interdisciplinary care, and there is an urgent need to explore their potential in improving communication and continuity of care. Web-based communication tools offer the promise of greater democratization of healthcare through empowering patients and families, and decisively moving clinical practice towards patient-centered care. Team-based communication tools do not simply add yet another option for communication but could rewrite the script for healthcare.

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REFERENCES 1. Hickam DH, Weiss JW, Guise JM, et al. Defining Complex Care Needs. Rockville, MD: Agency for Healthcare Research and Quality,;2013.

2. Rich E, Lipson D, Libersky J, Parchman M. Coordinating Care for Adults With Complex Care Needs in the Patient-Centered Medical Home: Challenges and Solutions. Rockville, MD.Agency for Healthcare Research and Quality; 2012.

3. Eysenbach G. Consumer health informatics. BMJ. 2000;320(7251):1713-1716.

4. Haggerty JL, Reid RJ, Freeman GK, Starfield BH, Adair CE, McKendry R. Continuity of care: a multidisciplinary review. BMJ. 2003;327(7425):1219-1221.

5. Canada Health Infoway. What Is Digital Health 2017; https://www.infoway- inforoute.ca/en/what-we-do/digital-health-and-you/what-is-digital-health.

6. U.S. Food and Drug Administration. Digital Health. 2017; https://www.fda.gov/MedicalDevices/DigitalHealth/.

7. Eysenbach G. What is e-health? J Med Internet Res. 2001;3(2):E20.

8. Kelsey S, St. Amant K, eds. Handbook of research on computer mediated communication. Hershey, PA: Information Science Reference; 2008.

9. Web 2.0 At Work - Simple And Social Collaboration Between Coworkers 2008.

10. Hanlon P, Daines L, Campbell C, McKinstry B, Weller D, Pinnock H. Telehealth Interventions to Support Self-Management of Long-Term Conditions: A Systematic Metareview of Diabetes, Heart Failure, Asthma, Chronic Obstructive Pulmonary Disease, and Cancer. J Med Internet Res. 2017;19(5).

11. Lorig KR, Holman H. Self-management education: history, definition, outcomes, and mechanisms. Ann Behav Med. 2003;26(1):1-7.

12. Mitchell P, Wynia M, Golden R, et al. Core Principles & Values of Effective Team-Based Health Care. Institute of Medicine; 2012.

13. Internet Users (per 100) Worldwide. The World Bank;2015.

14. American Medical Association. Digital Health Study: Physicians' motivations and requirements for adopting digital clinical tools. 2016.

15. Canadian Medical Association. Physician Guidelines for Online Communication with Patients. 2005.

16. Canadian Medical Association. How can Canada achieve enhanced use of electronic medical records? 2014.

167

168

17. Carayon P, Hoonakker P, Cartmill R, Hassol A. Using Health Information Technology (IT) in Practice Redesign: Impact of Health IT on Workflow. Patient-Reported Health Information Technology and Workflow. Rockville, MD. Agency for Healthcare Research and Quality; 2015.

18. Cipriano PF, Bowles K, Dailey M, Dykes P, Lamb G, Naylor M. The importance of health information technology in care coordination and transitional care. Nursing Outlook. 2013;61(6):475-489.

19. Canada Health Infoway. Opportunities for Action: A Pan-Canadian Digital Health Strategic Plan. In: Canada Health Infoway, 2013.

20. Institute of Medicine (U.S.) Committee on Quality of Health Care in America. Crossing the quality chasm : a new health system for the 21st century. Washington, D.C.National Academy Press; 2001; 337 p.

21. Institute of Medicine. IOM report: patient safety--achieving a new standard for care. Acad Emerg Med. 2005;12(10):1011-1012.

22. Coleman EA, Boult C. Improving the quality of transitional care for persons with complex care needs. J Am Geriatr Soc. 2003;51(4):556-557.

23. Betancourt MT, Roberts KC, Bennett T-L, Driscoll ER, Jayaraman G, Pelletier L. Chronic Diseases and Injuries in Canada In: Chronic Disease Surveillance Division, Public Health Agency Canada, 2011.

24. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross- sectional study. Lancet. 2012;380(9836):37-43.

25. Seniors and the Health Care System: What Is the Impact of Multiple Chronic Conditions? Health Canada. Canadian Institute for Health Information; 2011.

26. Pham HH, Schrag D, O'Malley AS, Wu B, Bach PB. Care patterns in Medicare and their implications for pay for performance. N Engl J Med. 2007;356(11):1130-1139.

27. Starfield B. Threads and yarns: weaving the tapestry of comorbidity. Ann Fam Med. 2006;4(2):101-103.

28. Tinetti ME, Bogardus ST, Jr., Agostini JV. Potential pitfalls of disease-specific guidelines for patients with multiple conditions. N Engl J Med. 2004;351(27):2870-2874.

29. Easley J, Miedema B, Carroll JC, et al. Coordination of cancer care between family physicians and cancer specialists: Importance of communication. Canadian Family Physician. 2016;62.

30. Dossett LA, Hudson JN, Morris AM, et al. The primary care provider (PCP)-cancer specialist relationship: A systematic review and mixed-methods meta-synthesis. CA Cancer J Clin. 2016.

169

31. Gandhi TK, Sittig DF, Franklin M, Sussman AJ, Fairchild DG, Bates DW. Communication breakdown in the outpatient referral process. J Gen Intern Med. 2000;15(9):626-631.

32. van Walraven C, Taljaard M, Bell CM, et al. Information exchange among physicians caring for the same patient in the community. CMAJ. 2008;179(10):1013-1018.

33. Schoen C, Osborn R, Huynh PT, et al. Primary care and health system performance: adults' experiences in five countries. Health Affairs. 2004;Suppl Web Exclusives:W4-487-503.

34. Kripalani S, LeFevre F, Phillips CO, Williams MV, Basaviah P, Baker DW. Deficits in communication and information transfer between hospital-based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831-841.

35. van Walraven C, Mamdani M, Fang J, Austin PC. Continuity of care and patient outcomes after hospital discharge. J Gen Intern Med. 2004;19(6):624-631.

36. Snow V, Beck D, Budnitz T, et al. Transitions of Care Consensus Policy Statement American College of Physicians-Society of General Internal Medicine-Society of Hospital Medicine- American Geriatrics Society-American College of Emergency Physicians-Society of Academic Emergency Medicine. J Gen Intern Med. 2009;24(8):971-976.

37. McDonald K, Sundaram V, Bravata D, et al. Closing the Quality Gap: A Critical Analysis of Quality Improvement Strategies (Vol. 7: Care Coordination). In: Agency for Healthcare Research and Quality, Rockville, MD. 2007.

38. Sambamoorthi U, Tan X, Deb A. Multiple chronic conditions and healthcare costs among adults. Expert Rev Pharmacoecon Outcomes Res. 2015;15(5):823-832.

39. Skinner HG, Coffey R, Jones J, Heslin KC, Moy E. The effects of multiple chronic conditions on hospitalization costs and utilization for ambulatory care sensitive conditions in the United States: a nationally representative cross-sectional study. BMC Health Serv Res. 2016;16:77.

40. Makary MA, Daniel M. Medical error—the third leading cause of death in the US. BMJ. 2016;353(2139).

41. Sutcliffe KM, Lewton E, Rosenthal MM. Communication failures: an insidious contributor to medical mishaps. Acad Med. 2004;79(2):186-194.

42. Berwick DM, Hackbarth AD. Eliminating waste in US health care. JAMA. 2012;307(14):1513-1516.

43. Schwappach DL. Risk factors for patient-reported medical errors in eleven countries. Health Expect. 2014;17(3):321-331.

44. Bodenheimer T. Coordinating care--a perilous journey through the health care system. N Engl J Med. 2008;358(10):1064-1071.

170

45. eHealth Ontario. EHR Connectivity Strategy. 2016.

46. Canadian Cancer Society's Advisory Committee on Cancer Statistics. Canadian Cancer Statistics. Toronto, ON.Canadian Cancer Society; 2016.

47. Edwards BK, Noone AM, Mariotto AB, et al. Annual Report to the Nation on the status of cancer, 1975-2010, featuring prevalence of comorbidity and impact on survival among persons with lung, colorectal, breast, or prostate cancer. Cancer. 2014;120(9):1290-1314.

48. Roth AJ, Massie MJ. Anxiety and its management in advanced cancer. Curr Opin Support Palliat Care. 2007;1(1):50-56.

49. Teunissen SC, de Graeff A, Voest EE, de Haes JC. Are anxiety and depressed mood related to physical symptom burden? A study in hospitalized advanced cancer patients. Palliat Med. 2007;21(4):341-346.

50. Osse BH, Vernooij-Dassen MJ, Schade E, Grol RP. The problems experienced by patients with cancer and their needs for palliative care. Supportive Care in Cancer. 2005;13(9):722-732.

51. Rainbird K, Perkins J, Sanson-Fisher R, Rolfe I, Anseline P. The needs of patients with advanced, incurable cancer. Br J Cancer. 2009;101(5):759-764.

52. Detmar SB, Muller MJ, Wever LD, Schornagel JH, Aaronson NK. The patient-physician relationship. Patient-physician communication during outpatient palliative treatment visits: an observational study. JAMA. 2001;285(10):1351-1357.

53. Naylor MD, Coburn KD, Kurtzman ET, et al. Inter-professional team-based primary care for chronically ill adults: State of the science. In: Foundation American Board of Internal Medicine. Philadelphia, PA. American Board of Internal Medicine. 2010.

54. Curran V. Collaborative Care. In: Health Canada, 2007.

55. Katzenbach JR. The Wisdom of Teams: Creating the High Performance Organization. 2nd ed: Harper Business; 2003.

56. Wagner EH. The role of patient care teams in chronic disease management. BMJ. 2000;320(7234):569-572.

57. Boon H, Verhoef M, O'Hara D, Findlay B. From parallel practice to integrative health care: a conceptual framework. BMC Health Serv Res. 2004;4(1):15.

58. Henry E, Silva A, Tarlov E, et al. Delivering Coordinated Cancer Care by Building Transactive Memory in a Team of Teams. J Oncol Pract. 2016.

59. Lee SJ, Clark MA, Cox JV, Needles BM, Seigel C, Balasubramanian BA. Achieving Coordinated Care for Patients With Complex Cases of Cancer: A Multiteam System Approach. J Oncol Pract. 2016.

171

60. Tomasone JR, Brouwers MC, Vukmirovic M, et al. Interventions to improve care coordination between primary healthcare and oncology care providers: a systematic review. ESMO Open. 2016;1(5):e000077.

61. Braun KL, Kagawa-Singer M, Holden AE, et al. Cancer patient navigator tasks across the cancer care continuum. J Health Care Poor Underserved. 2012;23(1):398-413.

62. Grumbach K, Bodenheimer T. Can health care teams improve primary care practice? JAMA. 2004;291(10):1246-1251.

63. Young HM, Siegel EO, McCormick WC, Fulmer T, Harootyan LK, Dorr DA. Interdisciplinary collaboration in geriatrics: advancing health for older adults. Nursing Outlook. 2011;59(4):243-250.

64. Martin HA, Ciurzynski SM. Situation, Background, Assessment, and Recommendation- Guided Huddles Improve Communication and Teamwork in the Emergency Department. J Emerg Nurs. 2015;41(6):484-488.

65. Arriaga AF, Bader AM, Wong JM, et al. Simulation-based trial of surgical-crisis checklists. N Engl J Med. 2013;368(3):246-253.

66. Page JS, Lederman L, Kelly J, Barry MM, James TA. Teams and Teamwork in Cancer Care Delivery: Shared Mental Models to Improve Planning for Discharge and Coordination of Follow-Up Care. J Oncol Pract. 2016;12(11).

67. Rudin RS, Bates DW. Let the left hand know what the right is doing: a vision for care coordination and electronic health records. J Am Med Inform Assoc. 2014;21(1):13-16.

68. Wagner EH, Austin BT, Davis C, Hindmarsh M, Schaefer J, Bonomi A. Improving chronic illness care: translating evidence into action. Health Affairs. 2001;20(6):64-78.

69. Levit LA, Balogh EP, Nass SJ, Ganz PA. Delivering High-Quality Cancer Care. Washington D. C.: National Academy of Medicine. 2013.

70. Shojania KG, United States. Agency for Healthcare Research and Quality. Closing the quality gap : a critical analysis of quality improvement strategies. Rockville, MD: Agency for Healthcare Research and Quality, 2004.

71. Vose JM. 2016 ASCO Presidential Address: "Collective Wisdom: The Future of Patient- Centered Care and Research". J Clin Oncol. 2016.

72. Cancer Care Ontario. Ontario Cancer Plan 2015-2019. In: Cancer Care Ontario, ed. 2016.

73. Epstein RM, Street RL, Jr. The values and value of patient-centered care. Ann Fam Med. 2011;9(2):100-103.

74. Reid RJ, Haggerty JL, McKendry R. Defusing the confusion: concept and measures of continuity of healthcare. In: Canadian Health Services Research Foundation. 2002.

172

75. Haggerty JL, Roberge D, Freeman GK, Beaulieu C. Experienced continuity of care when patients see multiple clinicians: a qualitative metasummary. Ann Fam Med. 2013;11(3):262-271.

76. Uijen AA, Schers HJ, Schellevis FG, van den Bosch WJ. How unique is continuity of care? A review of continuity and related concepts. Fam Pract. 2012;29(3):264-271.

77. Flocke SA. Measuring attributes of primary care: development of a new instrument. J Fam Pract. 1997;45(1):64-74.

78. Farrell TW, Tomoaia-Cotisel A, Scammon DL, Day J, Day RL, Magill MK. Care Management: Implications for Medical Practice, Health Policy, and Health Services Research. Rockville, MD.Agency for Healthcare Research and Quality; 2015.

79. Center for Health Care Strategies Inc. Care Management Definition and Framework. 2007.

80. Fragmentation or integration? Lancet. 1951;2(6693):1071.

81. Tepper J. Experiencing Integrated Care: Ontarians' views of health care coordination and communication. Health Quality Ontario,;2014.

82. Singer SJ, Burgers J, Friedberg M, Rosenthal MB, Leape L, Schneider E. Defining and measuring integrated patient care: promoting the next frontier in health care delivery. Med Care Res Rev. 2011;68(1):112-127.

83. National Research Corporation. Development and Validation of the Picker Ambulatory Oncology Survey Instrument in Canada. In: Ontario Hospital Association, ed. Lincoln, NE2003.

84. Uijen AA, Schellevis FG, van den Bosch WJ, Mokkink HG, van Weel C, Schers HJ. Nijmegen Continuity Questionnaire: development and testing of a questionnaire that measures continuity of care. J Clin Epidemiol. 2011;64(12):1391-1399.

85. Haggerty JL, Roberge D, Freeman GK, Beaulieu C, Breton M. Validation of a generic measure of continuity of care: when patients encounter several clinicians. Ann Fam Med. 2012;10(5):443-451.

86. McDonald K, Schultz E, Albin L, et al. Chapter 3. Care Coordination Measurement Framework. Rockville, MD: Agency for Healthcare Research and Quality,;2014.

87. Scholle SH, Vuong O, Ding L, et al. Development of and field test results for the CAHPS PCMH Survey. Med Care. 2012;50 Suppl:S2-10.

88. Baggs JG. Development of an instrument to measure collaboration and satisfaction about care decisions. Journal of advanced nursing. 1994;20(1):176-182.

89. Jenkinson C, Coulter A, Reeves R, Bruster S, Richards N. Properties of the Picker Patient Experience questionnaire in a randomized controlled trial of long versus short form survey instruments. Journal of public health medicine. 2003;25(3):197-201.

173

90. Rittenhouse DR, Casalino LP, Gillies RR, Shortell SM, Lau B. Measuring the medical home infrastructure in large medical groups. Health affairs. 2008;27(5):1246-1258.

91. Schultz EM, Pineda N, Lonhart J, Davies SM, McDonald KM. A systematic review of the care coordination measurement landscape. BMC Health Serv Res. 2013;13:119.

92. Bautista MA, Nurjono M, Lim YW, Dessers E, Vrijhoef HJ. Instruments Measuring Integrated Care: A Systematic Review of Measurement Properties. Milbank Q. 2016;94(4):862- 917.

93. Dobrow MJ, Paszat L, Golden B, et al. Measuring Integration of Cancer Services to Support Performance Improvement: The CSI Survey. Healthc Policy. 2009;5(1):35-53.

94. Singer SJ, Friedberg MW, Kiang MV, Dunn T, Kuhn DM. Development and preliminary validation of the Patient Perceptions of Integrated Care survey. Med Care Res Rev. 2013;70(2):143-164.

95. Uijen AA, Heinst CW, Schellevis FG, et al. Measurement properties of questionnaires measuring continuity of care: a systematic review. PLoS One. 2012;7(7):e42256.

96. McDonald K, Sundaram V, Bravata D, et al. Care Coordination. A Critical Analysis of Quality Improvement Strategies. Technical Review 9. Vol 7. Rockville, MD: Agency for Healthcare Research and Quality. 2007.

97. Cabana MD, Jee SH. Does continuity of care improve patient outcomes? J Fam Pract. 2004;53(12):974-980.

98. Husain A, Barbera L, Howell D, Moineddin R, Bezjak A, Sussman J. Advanced lung cancer patients' experience with continuity of care and supportive care needs. Support Care Cancer. 2013;21(5):1351-1358.

99. Parchman ML, Pugh JA, Noel PH, Larme AC. Continuity of care, self-management behaviors, and glucose control in patients with type 2 diabetes. Med Care. 2002;40(2):137-144.

100. Barker I, Steventon A, Deeny SR. Association between continuity of care in general practice and hospital admissions for ambulatory care sensitive conditions: cross sectional study of routinely collected, person level data. BMJ. 2017;356:j84.

101. Arnold LD, McGilvray MM, Kyle Cooper J, James AS. Inadequate Cancer Screening: Lack of Provider Continuity is a Greater Obstacle than Medical Mistrust. J Health Care Poor Underserved. 2017;28(1):362-377.

102. Pollack CE, Hussey PS, Rudin RS, Fox DS, Lai J, Schneider EC. Measuring Care Continuity: A Comparison of Claims-based Methods. Med Care. 2016;54(5):e30-34.

103. Bice TW, Boxerman SB. A quantitative measure of continuity of care. Med Care. 1977;15(4):347-349.

174

104. Breslau N, Haug MR. Service Delivery Structure and Continuity of Care - Case-Study of a Pediatric Practice in Process of Reorganization. Journal of Health and Social Behavior. 1976;17(4):339-352.

105. Waibel S, Henao D, Aller MB, Vargas I, Vazquez ML. What do we know about patients' perceptions of continuity of care? A meta-synthesis of qualitative studies. International Journal for Quality in Health Care. 2012;24(1):39-48.

106. Aubin M, Vezina L, Verreault R, et al. Patient, primary care physician and specialist expectations of primary care physician involvement in cancer care. J Gen Intern Med. 2012;27(1):8-15.

107. Aubin M, Giguere A, Martin M, et al. Interventions to improve continuity of care in the follow-up of patients with cancer. Cochrane Database Syst Rev. 2012;7:CD007672.

108. Communication. Merriam-Webster Dictionary. 2017.

109. Weiner SJ, Barnet B, Cheng TL, Daaleman TP. Processes for effective communication in primary care. Ann Intern Med. 2005;142(8):709-714.

110. O'Daniel M, Rosenstein AH. Professional Communication and Team Collaboration. In: Hughes RG. Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Rockville, MD: Agency for Healthcare Research and Quality. 2008.

111. Luhmann N. Familiarity, Confidence, Trust: Problems and Alternatives. In: Gambetta D, ed. Trust: Making and Breaking Cooperative Relations,. Cambridge, MA: Basil Blackwell; 1988:95.

112. Paget L, Han PK, Nedza S, et al. Patient-Clinician Communication: Basic Principles and Expectations. Institute of Medicine. 2011.

113. Simpson M, Buckman R, Stewart M, et al. Doctor-patient communication: the Toronto consensus statement. BMJ. 1991;303(6814):1385-1387.

114. Epstein RM, Hundert EM. Defining and assessing professional competence. JAMA. 2002;287(2):226-235.

115. Epstein R, Street RL. Patient-centered communication in cancer care : promoting healing and reducing suffering. Bethsda, MD: U.S. Dept. of Health and Human Services, National Institutes of Health, National Cancer Institute. 2007.

116. Institute of Medicine. Dying in America: Improving Quality and Honoring Individual Preferences Near the End of Life. Washington, D. C.2015.

117. Elkin EB, Kim SH, Casper ES, Kissane DW, Schrag D. Desire for information and involvement in treatment decisions: elderly cancer patients' preferences and their physicians' perceptions. J Clin Oncol. 2007;25(33):5275-5280.

175

118. van Gemert-Pijnen JE, Nijland N, van Limburg M, et al. A holistic framework to improve the uptake and impact of eHealth technologies. J Med Internet Res. 2011;13(4):e111.

119. Schwartz M, Kleinrock L. An Early History of the Internet. IEEE Commun Magazine. 2010;48(8):26-36.

120. Statistics Canada. Table 358-0153 - Canadian Internet use survey, Internet use, by age group, Internet activity, sex, level of education and household income, occasional (percent). In: CANSIM, ed. 2012.

121. Statistics Canada. CANSIM Table 358-0008. 2007.

122. Pagliari C, Sloan D, Gregor P, et al. What is eHealth (4): a scoping exercise to map the field. J Med Internet Res. 2005;7(1):e9.

123. Finkelstein J, Knight A, Marinopoulos S, et al. Enabling Patient-Centered Care Through Health Information Technology. In: The Johns Hopkins University Evidence-based Practice Center. Rockville.Agency for Healthcare Research and Quality. 2012.

124. Black AD, Car J, Pagliari C, et al. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med. 2011;8(1):e1000387.

125. Liddy C, Drosinis P, Deri Armstrong C, McKellips F, Afkham A, Keely E. What are the cost savings associated with providing access to specialist care through the Champlain BASE eConsult service? A costing evaluation. BMJ Open. 2016;6(6):e010920.

126. Gray CS, Mercer S, Palen T, McKinstry B, Hendry A. eHealth Advances in Support of People with Complex Care Needs: Case Examples from Canada, Scotland and the US. Healthc Q. 2016;19(2):29-37.

127. Fox S, Purcell K. Chronic Disease and the Internet. Washington, D.C.Pew Internet and American Life Project. 2010.

128. Hibbard JH, Mahoney E. Toward a theory of patient and consumer activation. Patient Educ Couns. 2010;78(3):377-381.

129. Holman H, Lorig K. Patients as partners in managing chronic disease. Partnership is a prerequisite for effective and efficient health care. BMJ. 2000;320(7234):526-527.

130. Eysenbach G, Diepgen TL. The role of e-health and consumer health informatics for evidence-based patient choice in the 21st century. Clin Dermatol. 2001;19(1):11-17.

131. Robinson TN, Patrick K, Eng TR, Gustafson D. An evidence-based approach to interactive health communication: a challenge to medicine in the information age. Science Panel on Interactive Communication and Health. JAMA. 1998;280(14):1264-1269.

132. Anderson RM, Funnell MM. Patient empowerment: myths and misconceptions. Patient Educ Couns. 2010;79(3):277-282.

176

133. Coulter A, Entwistle VA, Eccles A, Ryan S, Shepperd S, Perera R. Personalised care planning for adults with chronic or long-term health conditions. Cochrane Database Syst Rev. 2015(3):CD010523.

134. Patient Safety Network. The Role of the Patient in Safety.Agency for Healthcare Research and Quality. 2016.

135. de Jong CC, Ros WJ, Schrijvers G. The effects on health behavior and health outcomes of Internet-based asynchronous communication between health providers and patients with a chronic condition: a systematic review. J Med Internet Res. 2014;16(1):e19.

136. Green MD, Miers I. Forward Secure Asynchronous Messaging from Puncturable Encryption. P Ieee S Secur Priv. 2015:305-320.

137. Wakefield DS, Mehr D, Keplinger L, et al. Issues and questions to consider in implementing secure electronic patient-provider web portal communications systems. Int J Med Inform. 2010;79(7):469-477.

138. Baron NS. See you online - Gender issues in college student use of instant messaging. J Lang Soc Psychol. 2004;23(4):397-423.

139. Bafoutsou G, Mentzas G. Review and functional classification of collaborative systems. Int J Inform Manage. 2002;22(4):281-305.

140. Ye J, Rust G, Fry-Johnson Y, Strothers H. E-mail in patient-provider communication: a systematic review. Patient Educ Couns. 2010;80(2):266-273.

141. Atherton H, Sawmynaden P, Sheikh A, Majeed A, Car J. Email for clinical communication between patients/caregivers and healthcare professionals. Cochrane Database Syst Rev. 2012;11:CD007978.

142. Kummervold PE, Trondsen M, Andreassen H, Gammon D, Hjortdahl P. [Patient-physician interaction over the internet]. Tidsskr Nor Laegeforen. 2004;124(20):2633-2636.

143. Bergmo TS, Kummervold PE, Gammon D, Dahl LB. Electronic patient-provider communication: will it offset office visits and telephone consultations in primary care? Int J Med Inform. 2005;74(9):705-710.

144. Katz SJ, Moyer CA, Cox DT, Stern DT. Effect of a triage-based E-mail system on clinic resource use and patient and physician satisfaction in primary care: a randomized controlled trial. J Gen Intern Med. 2003;18(9):736-744.

145. Pappas Y, Atherton H, Sawmynaden P, Car J. Email for clinical communication between healthcare professionals. Cochrane Database Syst Rev. 2012;9:CD007979.

146. Feldstein A, Elmer PJ, Smith DH, et al. Electronic medical record reminder improves osteoporosis management after a fracture: a randomized, controlled trial. J Am Geriatr Soc. 2006;54(3):450-457.

177

147. Walsh C, Siegler EL, Cheston E, et al. Provider-to-provider electronic communication in the era of meaningful use: a review of the evidence. J Hosp Med. 2013;8(10):589-597.

148. Kruse CS, Bolton K, Freriks G. The effect of patient portals on quality outcomes and its implications to meaningful use: a systematic review. J Med Internet Res. 2015;17(2):e44.

149. Rittenhouse DR, Ramsay PP, Casalino LP, McClellan S, Kandel ZK, Shortell SM. Increased Health Information Technology Adoption and Use Among Small Primary Care Physician Practices Over Time: A National Cohort Study. Ann Fam Med. 2017;15(1):56-62.

150. Househ MS, Lau FY. Collaborative technology use by healthcare teams. J Med Syst. 2005;29(5):449-461.

151. Sarker S, Sahay S. Understanding virtual team development: An interpretive study. J Assoc Inform Syst. 2002;3:247-285.

152. Wagner EH. Chronic disease management: what will it take to improve care for chronic illness? Effective Clinical Practice. 1998;1(1):2-4.

153. Gee PM, Greenwood DA, Paterniti DA, Ward D, Miller LM. The eHealth Enhanced Chronic Care Model: a theory derivation approach. J Med Internet Res. 2015;17(4):e86.

154. Jimison HB, Oregon Health & Science University. Evidence-based Practice Center., United States. Agency for Healthcare Research and Quality. Barriers and drivers of health information technology use for the elderly, chronically ill, and underserved. Rockville, MD. United States Agency for Healthcare Research and Quality. 2008.

155. Greenhalgh T, Russell J. Why do evaluations of eHealth programs fail? An alternative set of guiding principles. PLoS Med. 2010;7(11):e1000360.

156. Nilsen P. Making sense of implementation theories, models and frameworks. Implement Sci. 2015;10:53.

157. Bergeson SC, Dean JD. A systems approach to patient-centered care. JAMA. 2006;296(23):2848-2851.

158. Dudgeon DJ, Harlos M, Clinch JJ. The Edmonton Symptom Assessment Scale (ESAS) as an audit tool. J Palliat Care. 1999;15(3):14-19.

159. Mularski RA, Dy SM, Shugarman LR, et al. A systematic review of measures of end-of-life care and its outcomes. Health Serv Res. 2007;42(5):1848-1870.

160. Barbera L, Seow H, Howell D, et al. Symptom burden and performance status in a population-based cohort of ambulatory cancer patients. Cancer. 2010;116(24):5767-5776.

161. A Framework for Development and Evaluation of RCTs for Complex Interventions to Improve Health. MRC Health Services and Public Health Research Board. 2000.

178

162. Catwell L, Sheikh A. Evaluating eHealth interventions: the need for continuous systemic evaluation. PLoS Med. 2009;6(8):e1000126.

163. Cresswell KM, Sheikh A. Undertaking sociotechnical evaluations of health information technologies. Inform Prim Care. 2014;21(2):78-83.

164. Creswell J. Designing and Conducting Mixed Methods Research. 2nd ed: Sage Publications. 2010.

165. Arksey H, O'Malley L. Scoping studies: towards a methodological framework. International Journal of Social Research Methodology. 2005;8(1).

166. Mays N, Roberts E, Popay J. Synthesizing research evidence. In: Fulop N, ed. Studying the organisation and delivery of health services : research methods. London ; New York: Routledge; 2001:xi, 228 p.

167. Pham MT, Rajic A, Greig JD, Sargeant JM, Papadopoulos A, McEwen SA. A scoping review of scoping reviews: advancing the approach and enhancing the consistency. Res Synth Methods. 2014;5(4):371-385.

168. Kurahashi AM, Weinstein PB, Jamieson T, et al. In the Loop: The Organization of Team- Based Communication in a Patient-Centered Clinical Collaboration System. JMIR Hum Factors. 2016;3(1):e12.

169. Jamieson T. Using social network analysis to analyze the function of collaborative care teams in an online social networking tool. Portland, OR: Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Sciences University. 2015.

170. Campbell M, Fitzpatrick R, Haines A, et al. Framework for design and evaluation of complex interventions to improve health. BMJ. 2000;321(7262):694-696.

171. Craig P, Dieppe P, Macintyre S, et al. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008;337:a1655.

172. Altman DG, Schulz KF, Moher D, et al. The revised CONSORT statement for reporting randomized trials: explanation and elaboration. Ann Intern Med. 2001;134(8):663-694.

173. Tierney WM, Overhage JM, Mcdonald CJ. A Plea for Controlled Trials in Medical Informatics. J Am Med Inform Assn. 1994;1(4):353-355.

174. Heathfield HA, Buchan IE. Current evaluations of information technology in health care are often inadequate. BMJ. 1996;313(7063):1008.

175. Schwartz D, Lellouch J. Explanatory and pragmatic attitudes in therapeutical trials. J Clin Epidemiol. 2009;62(5):499-505.

179

176. Thorpe KE, Zwarenstein M, Oxman AD, et al. A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers. J Clin Epidemiol. 2009;62(5):464- 475.

177. Tashakkori AM, Teddlie CB. Mixed Methodology: Combining Qualitative and Quantitative Approaches. 1st ed: SAGE Publications; 1998.

178. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res in Psych. 2006;3(2):77-101.

179. Sandelowski M. Whatever happened to qualitative description? Res Nurs Health. 2000;23(4):334-340.

180. Sandelowski M. Qualitative analysis: what it is and how to begin. Res Nurs Health. 1995;18(4):371-375.

181. Creswell J. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. London, UK. Sage Publications. 2009.

182. Sandelowski M. What's in a name? Qualitative description revisited. Res Nurs Health. 2010;33(1):77-84.

183. Davis D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 1989;13(3):318-340.

184. Holden RJ, Karsh BT. The Technology Acceptance Model: its past and its future in health care. J Biom Informatics. 2010;43(1).

185. Ward BW, Schiller JS, Goodman RA. Multiple Chronic Conditions Among US Adults: A 2012 Update. Prev Chronic Dis. 2014;11.

186. Wagner EH, Groves T. Care for chronic diseases. BMJ. 2002;325(7370):913-914.

187. Glasgow RE, Funnell MM, Bonomi AE, Davis C, Beckham V, Wagner EH. Self- management aspects of the improving chronic illness care breakthrough series: implementation with diabetes and heart failure teams. Ann Behav Med. 2002;24(2):80-87.

188. O'Malley AS, Cunningham PJ. Patient experiences with coordination of care: the benefit of continuity and primary care physician as referral source. J Gen Intern Med. 2009;24(2):170-177.

189. Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA. 2002;288(19):2469-2475.

190. Epstein R, Street RLJ. Patient-centered Communication in Cancer Care. Bethesda, MD. US Department of Health and Human Services. 2007.

180

191. Pandor A, Gomersall T, Stevens JW, et al. Remote monitoring after recent hospital discharge in patients with heart failure: a systematic review and network meta-analysis. Heart. 2013;99(23):1717-1726.

192. Hamines S, Gerth-Guyette E, Faulx D, Green BB, Ginsburg AS. Impact of mHealth Chronic Disease Management on Treatment Adherence and Patient Outcomes: A Systematic Review. J Med Internet Res. 2015;17(2).

193. Cook N, Maganti M, Dobriyal A, et al. E-Mail Communication Practices and Preferences Among Patients and Providers in a Large Comprehensive Cancer Center. J Oncol Pract. 2016;12(7).

194. Siopis G, Chey T, Allman-Farinelli M. A systematic review and meta-analysis of interventions for weight management using text messaging. J Hum Nutr Diet. 2015;28 Suppl 2:1-15.

195. Newhouse N, Lupianez-Villanueva F, Codagnone C, Atherton H. Patient Use of Email for Health Care Communication Purposes Across 14 European Countries: An Analysis of Users According to Demographic and Health-Related Factors. J Med Internet Res. 2015;17(3).

196. Bates DW. Health Information Technology and Care Coordination: The Next Big Opportunity for Informatics? Yearb Med Inform. 2015;10(1).

197. Stille CJ, Jerant A, Bell D, Meltzer D, Elmore JG. Coordinating care across diseases, settings, and clinicians: a key role for the generalist in practice. Ann Intern Med. 2005;142(8):700-708.

198. Health Quality Ontario. Electronic tools for health information exchange: an evidence- based analysis. Ont Health Technol Assess Ser. 2013;13(11):1-76.

199. Wu RC, Tran K, Lo V, et al. Effects of clinical communication interventions in hospitals: a systematic review of information and communication technology adoptions for improved communication between clinicians. Int J Med Inform. 2012;81(11):723-732.

200. Gentles SJ, Lokker C, McKibbon KA. Health information technology to facilitate communication involving health care providers, caregivers, and pediatric patients: a scoping review. J Med Internet Res. 2010;12(2):e22.

201. Kuijpers W, Groen WG, Aaronson NK, van Harten WH. A systematic review of web-based interventions for patient empowerment and physical activity in chronic diseases: relevance for cancer survivors. J Med Internet Res. 2013;15(2):e37.

202. Wildevuur SE, Simonse LW. Information and communication technology-enabled person- centered care for the "big five" chronic conditions: scoping review. J Med Internet Res. 2015;17(3):e77.

203. Ammenwerth E, Schnell-Inderst P, Hoerbst A. The impact of electronic patient portals on patient care: a systematic review of controlled trials. J Med Internet Res. 2012;14(6):e162.

181

204. Goldzweig CL, Orshansky G, Paige NM, et al. Electronic patient portals: evidence on health outcomes, satisfaction, efficiency, and attitudes: a systematic review. Ann Intern Med. 2013;159(10):677-687.

205. Flodgren G, Rachas A, Farmer AJ, Inzitari M, Shepperd S. Interactive telemedicine: effects on professional practice and health care outcomes. Cochrane Database Syst Rev. 2015(9):CD002098.

206. Lilford RJ, Foster J, Pringle M. Evaluating eHealth: how to make evaluation more methodologically robust. PLoS Med. 2009;6(11):e1000186.

207. Bishop TF, Press MJ, Mendelsohn JL, Casalino LP. Electronic communication improves access, but barriers to its widespread adoption remain. Health Affairs. 2013;32(8):1361-1367.

208. Cole-Lewis H, Kershaw T. Text messaging as a tool for behavior change in disease prevention and management. Epidemiol Rev. 2010;32:56-69.

209. Hall AK, Cole-Lewis H, Bernhardt JM. Mobile text messaging for health: a systematic review of reviews. Annu Rev Public Health. 2015;36:393-415.

210. Colquhoun HL, Levac D, O'Brien KK, et al. Scoping reviews: time for clarity in definition, methods, and reporting. J Clin Epidemiol. 2014.

211. Huang JS, Terrones L, Tompane T, et al. Preparing adolescents with chronic disease for transition to adult care: a technology program. Pediatrics. 2014;133(6):e1639-1646.

212. Bond GE, Burr R, Wolf FM, Price M, McCurry SM, Teri L. The effects of a web-based intervention on the physical outcomes associated with diabetes among adults age 60 and older: a randomized trial. Diabetes Technol Ther. 2007;9(1):52-59.

213. Jones JB, Weiner JP, Shah NR, Stewart WF. The wired patient: patterns of electronic patient portal use among patients with cardiac disease or diabetes. J Med Internet Res. 2015;17(2):e42.

214. Riippa I, Linna M, Ronkko I. The effect of a patient portal with electronic messaging on patient activation among chronically ill patients: controlled before-and-after study. J Med Internet Res. 2014;16(11):e257.

215. Higgins JPT, Green S. Cochrane Handbook for Systematic Reviews of Interventions The Cochrane Collaboration. 2011.

216. Gulmans J, Vollenbroek-Hutten MM, Visser JJ, Nijeweme-d'Hollosy WO, van Gemert- Pijnen JE, van Harten WH. A web-based communication system for integrated care in cerebral palsy: design features, technical feasibility and usability. J Telemed Telecare. 2010;16(7):389- 393.

182

217. Ryan JG, Schwartz R, Jennings T, Fedders M, Vittoria I. Feasibility of an internet-based intervention for improving diabetes outcomes among low-income patients with a high risk for poor diabetes outcomes followed in a community clinic. Diabetes Educ. 2013;39(3):365-375.

218. Chui M, Manyika J, Bughin J, et al. The social economy: Unlocking value and productivity through social technologies.McKinsey & Company. 2012.

219. Weller J, Boyd M, Cumin D. Teams, tribes and patient safety: overcoming barriers to effective teamwork in healthcare. Postgrad Med J. 2014;90(1061):149-154.

220. Kittler AF, Carlson GL, Harris C, et al. Primary care physician attitudes towards using a secure web-based portal designed to facilitate electronic communication with patients. Informatics in Primary Care. 2004;12(3):129-138.

221. Komives EM. Clinician-patient E-mail communication: challenges for reimbursement. N C Med J. 2005;66(3):238-240.

222. Quinn CC, Shardell MD, Terrin ML, Barr EA, Ballew SH, Gruber-Baldini AL. Cluster- randomized trial of a mobile phone personalized behavioral intervention for blood glucose control. Diabetes Care. 2011;34(9):1934-1942.

223. Funnell MM, Anderson RM. The problem with compliance in diabetes. JAMA. 2000;284(13):1709.

224. National Asthma Education and Prevention Program. Expert panel report III: Guidelines for the diagnosis and management of asthma. In: National Heart LaBI, ed. 2007.

225. Clark RA, Inglis SC, McAlister FA, Cleland JG, Stewart S. Telemonitoring or structured telephone support programmes for patients with chronic heart failure: systematic review and meta-analysis. BMJ. 2007;334(7600):942.

226. Inglis SC, Clark RA, Dierckx R, Prieto-Merino D, Cleland JG. Structured telephone support or non-invasive telemonitoring for patients with heart failure. Heart. 2017;103(4):255-257.

227. Van Poucke S, Thomeer M, Heath J, Vukicevic M. Are Randomized Controlled Trials the (G)old Standard? From Clinical Intelligence to Prescriptive Analytics. J Med Internet Res. 2016;18(7).

228. Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012;50(3):217-226.

229. Guise JM, Chang C, Viswanathan M, et al. Agency for Healthcare Research and Quality Evidence-based Practice Center methods for systematically reviewing complex multicomponent health care interventions. J Clin Epidemiol. 2014;67(11):1181-1191.

183

230. van Limburg M, van Gemert-Pijnen JE, Nijland N, Ossebaard HC, Hendrix RM, Seydel ER. Why business modeling is crucial in the development of eHealth technologies. J Med Internet Res. 2011;13(4):e124.

231. Armstrong AW, Johnson MA, Lin S, Maverakis E, Fazel N, Liu FT. Patient-centered, direct-access online care for management of atopic dermatitis: a randomized clinical trial. JAMA Dermatol. 2015;151(2):154-160.

232. Riippa I, Linna M, Ronkko I. The effect of a patient portal with electronic messaging on patient activation among chronically ill patients: controlled before-and-after study. J Med Internet Res. 2014;16(11):e257.

233. Riippa I, Linna M, Ronkko I, Kroger V. Use of an electronic patient portal among the chronically ill: an observational study. J Med Internet Res. 2014;16(12):e275.

234. Lau M, Campbell H, Tang T, Thompson DJ, Elliott T. Impact of patient use of an online patient portal on diabetes outcomes. Can J Diabetes. 2014;38(1):17-21.

235. Hsiao AL, Bazzy-Asaad A, Tolomeo C, Edmonds D, Belton B, Benin AL. Secure web messaging in a pediatric chronic care clinic: a slow takeoff of "kids' airmail". Pediatrics. 2011;127(2):e406-413.

236. van der Meer V, Bakker MJ, van den Hout WB, et al. Internet-based self-management plus education compared with usual care in asthma: a randomized trial. Ann Intern Med. 2009;151(2):110-120.

237. Allen M, Iezzoni LI, Huang A, Huang L, Leveille SG. Improving patient-clinician communication about chronic conditions: description of an internet-based nurse E-coach intervention. Nurs Res. 2008;57(2):107-112.

238. Leveille SG, Huang A, Tsai SB, Allen M, Weingart SN, Iezzoni LI. Health coaching via an internet portal for primary care patients with chronic conditions: a randomized controlled trial. Med Care. 2009;47(1):41-47.

239. Nilsson C, Ohman M, Soderberg S. Information and communication technology in supporting people with serious chronic illness living at home - an intervention study. J Telemed Telecare. 2006;12(4):198-202.

240. Ross SE, Moore LA, Earnest MA, Wittevrongel L, Lin CT. Providing a web-based online medical record with electronic communication capabilities to patients with congestive heart failure: randomized trial. J Med Internet Res. 2004;6(2):e12.

241. Jones JB, Weiner JP, Shah NR, Stewart WF. The wired patient: patterns of electronic patient portal use among patients with cardiac disease or diabetes. J Med Internet Res. 2015;17(2):e42.

184

242. Wayne N, Ritvo P. Smartphone-enabled health coach intervention for people with diabetes from a modest socioeconomic strata community: single-arm longitudinal feasibility study. J Med Internet Res. 2014;16(6):e149.

243. Barberan-Garcia A, Vogiatzis I, Solberg HS, et al. Effects and barriers to deployment of telehealth wellness programs for chronic patients across 3 European countries. Respir Med. 2014;108(4):628-637.

244. Mota Pereira J. Facebook enhances antidepressant pharmacotherapy effects. ScientificWorldJournal. 2014;2014:892048.

245. Lee JL, Choudhry NK, Wu AW, Matlin OS, Brennan TA, Shrank WH. Patient Use of Email, Facebook, and Physician Websites to Communicate with Physicians: A National Online Survey of Retail Pharmacy Users. J Gen Intern Med. 2016;31(1):45-51.

246. Nobis S, Lehr D, Ebert DD, et al. Efficacy and cost-effectiveness of a web-based intervention with mobile phone support to treat depressive symptoms in adults with diabetes mellitus type 1 and type 2: design of a randomised controlled trial. BMC Psychiatry. 2013;13:306.

247. Fishman PA, Cook AJ, Anderson ML, et al. Improving BP control through electronic communications: an economic evaluation. Am J Manag Care. 2013;19(9):709-716.

248. Harris LT, Haneuse SJ, Martin DP, Ralston JD. Diabetes quality of care and outpatient utilization associated with electronic patient-provider messaging: a cross-sectional analysis. Diabetes Care. 2009;32(7):1182-1187.

249. Weppner WG, Ralston JD, Koepsell TD, et al. Use of a shared medical record with secure messaging by older patients with diabetes. Diabetes Care. 2010;33(11):2314-2319.

250. Zhang J, Song YL, Bai CX. MIOTIC study: a prospective, multicenter, randomized study to evaluate the long-term efficacy of mobile phone-based Internet of Things in the management of patients with stable COPD. Int J Chron Obstruct Pulmon Dis. 2013;8:433-438.

251. Nguyen HQ, Donesky D, Reinke LF, et al. Internet-based dyspnea self-management support for patients with chronic obstructive pulmonary disease. J Pain Symptom Manage. 2013;46(1):43-55.

252. Solomon M, Wagner SL, Goes J. Effects of a Web-based intervention for adults with chronic conditions on patient activation: online randomized controlled trial. J Med Internet Res. 2012;14(1):e32.

253. Ahmed S, Bartlett SJ, Ernst P, et al. Effect of a web-based chronic disease management system on asthma control and health-related quality of life: study protocol for a randomized controlled trial. Trials. 2011;12:260.

185

254. Brennan PF, Casper GR, Burke LJ, et al. Technology-enhanced practice for patients with chronic cardiac disease: home implementation and evaluation. Heart Lung. 2010;39(6 Suppl):S34-46.

255. Sarkar U, Karter AJ, Liu JY, et al. The literacy divide: health literacy and the use of an internet-based patient portal in an integrated health system-results from the diabetes study of northern California (DISTANCE). J Health Commun. 2010;15 Suppl 2:183-196.

256. Zickmund SL, Hess R, Bryce CL, et al. Interest in the use of computerized patient portals: role of the provider-patient relationship. J Gen Intern Med. 2008;23 Suppl 1:20-26.

257. Gomez EJ, Caceres C, Lopez D, Del Pozo F. A web-based self-monitoring system for people living with HIV/AIDS. Comput Methods Programs Biomed. 2002;69(1):75-86.

258. Oerlemans S, van Cranenburgh O, Herremans PJ, Spreeuwenberg P, van Dulmen S. Intervening on cognitions and behavior in irritable bowel syndrome: A feasibility trial using PDAs. J Psychosom Res. 2011;70(3):267-277.

259. Nes AA, van Dulmen S, Eide E, et al. The development and feasibility of a web-based intervention with diaries and situational feedback via smartphone to support self-management in patients with diabetes type 2. Diabetes Res Clin Pract. 2012;97(3):385-393.

260. Kristjansdottir OB, Fors EA, Eide E, et al. A smartphone-based intervention with diaries and therapist feedback to reduce catastrophizing and increase functioning in women with chronic widespread pain. part 2: 11-month follow-up results of a randomized trial. J Med Internet Res. 2013;15(3):e72.

261. Kristjansdottir OB, Fors EA, Eide E, et al. A smartphone-based intervention with diaries and therapist-feedback to reduce catastrophizing and increase functioning in women with chronic widespread pain: randomized controlled trial. J Med Internet Res. 2013;15(1):e5.

262. Kristjansdottir OB, Fors EA, Eide E, et al. Written online situational feedback via mobile phone to support self-management of chronic widespread pain: a usability study of a Web-based intervention. BMC Musculoskelet Disord. 2011;12:51.

263. Jelin E, Granum V, Eide H. Experiences of a web-based nursing intervention--interviews with women with chronic musculoskeletal pain. Pain Manag Nurs. 2012;13(1):2-10.

264. McMahon GT, Gomes HE, Hickson Hohne S, Hu TM, Levine BA, Conlin PR. Web-based care management in patients with poorly controlled diabetes. Diabetes Care. 2005;28(7):1624- 1629.

265. Fonda SJ, McMahon GT, Gomes HE, Hickson S, Conlin PR. Changes in diabetes distress related to participation in an internet-based diabetes care management program and glycemic control. J Diabetes Sci Technol. 2009;3(1):117-124.

186

266. Homko CJ, Santamore WP, Whiteman V, et al. Use of an internet-based telemedicine system to manage underserved women with gestational diabetes mellitus. Diabetes Technol Ther. 2007;9(3):297-306.

267. Ralston JD, Hirsch IB, Hoath J, Mullen M, Cheadle A, Goldberg HI. Web-based collaborative care for type 2 diabetes: a pilot randomized trial. Diabetes Care. 2009;32(2):234- 239.

268. Tang PC, Overhage JM, Chan AS, et al. Online disease management of diabetes: engaging and motivating patients online with enhanced resources-diabetes (EMPOWER-D), a randomized controlled trial. J Am Med Inform Assoc. 2013;20(3):526-534.

269. Zutz A, Ignaszewski A, Bates J, Lear SA. Utilization of the internet to deliver cardiac rehabilitation at a distance: a pilot study. Telemed J E Health. 2007;13(3):323-330.

270. Liebreich T, Plotnikoff RC, Courneya KS, Boule N. Diabetes NetPLAY: A physical activity website and linked email counselling randomized intervention for individuals with type 2 diabetes. Int J Behav Nutr Phys Act. 2009;6:18.

271. Bergmo TS, Wangberg SC, Schopf TR, Solvoll T. Web-based consultations for parents of children with atopic dermatitis: results of a randomized controlled trial. Acta Paediatr. 2009;98(2):316-320.

272. Meglic M, Furlan M, Kuzmanic M, et al. Feasibility of an eHealth service to support collaborative depression care: results of a pilot study. J Med Internet Res. 2010;12(5):e63.

273. Ruland CM, Jeneson A, Andersen T, et al. Designing tailored Internet support to assist cancer patients in illness management. AMIA Annual Symposium proceedings. AMIA Symposium. 2007:635-639.

274. Andersen T, Ruland CM. Cancer patients' questions and concerns expressed in an online nurse-delivered mail service: preliminary results. Stud Health Technol Inform. 2009;146:149- 153.

275. Grimsbo GH, Engelsrud GH, Ruland CM, Finset A. Cancer patients' experiences of using an Interactive Health Communication Application (IHCA). Int J Qual Stud Health Well-being. 2012;7.

276. Grimsbo GH, Ruland CM, Finset A. Cancer patients' expressions of emotional cues and concerns and oncology nurses' responses, in an online patient-nurse communication service. Patient Educ Couns. 2012;88(1):36-43.

277. Grimsbo GH, Finset A, Ruland CM. Left hanging in the air: experiences of living with cancer as expressed through E-mail communications with oncology nurses. Cancer Nurs. 2011;34(2):107-116.

187

278. Ruland CM, Andersen T, Jeneson A, et al. Effects of an internet support system to assist cancer patients in reducing symptom distress: a randomized controlled trial. Cancer Nurs. 2013;36(1):6-17.

279. Borosund E, Cvancarova M, Moore SM, Ekstedt M, Ruland CM. Comparing effects in regular practice of e-communication and Web-based self-management support among breast cancer patients: preliminary results from a randomized controlled trial. J Med Internet Res. 2014;16(12):e295.

280. Trautmann E, Kroner-Herwig B. Internet-based self-help training for children and adolescents with recurrent headache: a pilot study. Behavioural and Cognitive Psychotherapy. 2008;36.

281. Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: implications for understanding health and health services. Ann Fam Med. 2009;7(4):357-363.

282. Smith PC, Araya-Guerra R, Bublitz C, et al. Missing clinical information during primary care visits. JAMA. 2005;293(5):565-571.

283. Baker L, Wagner TH, Singer S, Bundorf MK. Use of the Internet and e-mail for health care information: results from a national survey. JAMA. 2003;289(18):2400-2406.

284. McGeady D, Kujala J, Ilvonen K. The impact of patient-physician web messaging on healthcare service provision. Int J Med Inform. 2008;77(1):17-23.

285. Ralston JD, Rutter CM, Carrell D, Hecht J, Rubanowice D, Simon GE. Patient use of secure electronic messaging within a shared medical record: a cross-sectional study. J Gen Intern Med. 2009;24(3):349-355.

286. Robben SH, Perry M, Huisjes M, et al. Implementation of an innovative web-based conference table for community-dwelling frail older people, their informal caregivers and professionals: a process evaluation. BMC Health Serv Res. 2012;12:251.

287. Gulmans J, Vollenbroek-Hutten M, van Gemert-Pijnen L, van Harten W. A web-based communication system for integrated care in cerebral palsy: experienced contribution to parent- professional communication. Int J Integr Care. 2012;12:e9.

288. Schumacher KL, Stewart BJ, Archbold PG, Dodd MJ, Dibble SL. Family caregiving skill: development of the concept. Res Nurs Health. 2000;23(3):191-203.

289. Payne S, Jarrett N, Jeffs D. The impact of travel on cancer patients' experiences of treatment: a literature review. Eur J Cancer Care. 2000;9(4):197-203.

290. Sarhill N, Walsh D, Nelson KA, LeGrand S, Davis MP. Assessment of delirium in advanced cancer: the use of the bedside confusion scale. Am J Hosp Palliat Care. 2001;18(5):335-341.

188

291. MacKenzie C. The need for a design lexicon: Examining minimalist, performance-centered, and user-centered design. Tech Commun. 2002;49(4):405-410.

292. Stinson JN, McGrath PJ, Hodnett ED, et al. An internet-based self-management program with telephone support for adolescents with arthritis: a pilot randomized controlled trial. J Rheumatol. 2010;37(9):1944-1952.

293. Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qualitative health research. 2005;15(9):1277-1288.

294. Thabane L, Ma J, Chu R, et al. A tutorial on pilot studies: the what, why and how. BMC Med Res Methodol. 2010;10:1.

295. Hearn J, Higginson IJ. Development and validation of a core outcome measure for palliative care: the palliative care outcome scale. Palliative Care Core Audit Project Advisory Group. Quality in health care : QHC. 1999;8(4):219-227.

296. Hughes RA, Sinha A, Aspinal F, Dunckley M, Addington-Hall J, Higginson IJ. What is the potential for the use of clinical outcome measures to be computerised? Findings from a qualitative research study. Int J Health Care Qual Assur Inc Leadersh Health Serv. 2004;17(1):47-52.

297. Pelayo-Alvarez M, Perez-Hoyos S, Agra-Varela Y. Reliability and concurrent validity of the Palliative Outcome Scale, the Rotterdam Symptom Checklist, and the Brief Pain Inventory. Journal of Palliative Medicine. 2013;16(8):867-874.

298. Bajwah S, Ross JR, Wells AU, et al. Palliative care for patients with advanced fibrotic lung disease: a randomised controlled phase II and feasibility trial of a community case conference intervention. Thorax. 2015;70(9):830-839.

299. Bruera E, Kuehn N, Miller MJ, Selmser P, Macmillan K. The Edmonton Symptom Assessment System (ESAS): a simple method for the assessment of palliative care patients. J Palliat Care. 1991;7(2):6-9.

300. Guerriere DN, Coyte PC. The Ambulatory and Home Care Record: A Methodological Framework for Economic Analyses in End-of-Life Care. J Aging Res. 2011;2011:374237.

301. Guerriere DN, Ungar WJ, Corey M, et al. Evaluation of the ambulatory and home care record: Agreement between self-reports and administrative data. Int J Technol Assess Health Care. 2006;22(2):203-210.

302. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377-381.

303. Lancaster GA, Dodd S, Williamson PR. Design and analysis of pilot studies: recommendations for good practice. J Eval Clin Pract. 2004;10(2):307-312.

189

304. Armes J, Crowe M, Colbourne L, et al. Patients' supportive care needs beyond the end of cancer treatment: a prospective, longitudinal survey. J Clin Oncol. 2009;27(36):6172-6179.

305. Zimmermann C, Swami N, Krzyzanowska M, et al. Early palliative care for patients with advanced cancer: a cluster-randomised controlled trial. Lancet. 2014.

306. Keast R, Brown K, Mandell M. Getting The Right Mix: Unpacking Integration Meanings and Strategies. International Public Management Journal. 2007;1(9).

307. Kuziemsky CE, O'Sullivan TL. A model for common ground development to support collaborative health communities. Soc Sci Med. 2015;128:231-238.

308. Crotty BH, Tamrat Y, Mostaghimi A, Safran C, Landon BE. Patient-To-Physician Messaging: Volume Nearly Tripled As More Patients Joined System, But Per Capita Rate Plateaued. Health Affairs. 2014;33(10):1817-1822.

309. Sullivan MG. Patient Portals: Not the Open Floodgates Physicians Fear Dermatology News2008.

310. Ontario Medical Association. OHIP Payments for E-Consultation Services for Referring Physicians (K738). OHIP Schedule of Benefits 2015: OMA Economics, Research & Analytics Department,; 2015.

311. Cartwright M, Hirani SP, Rixon L, et al. Effect of telehealth on quality of life and psychological outcomes over 12 months (Whole Systems Demonstrator telehealth questionnaire study): nested study of patient reported outcomes in a pragmatic, cluster randomised controlled trial. BMJ. 2013;346:f653.

312. Charlson M, Pompei P, Ales K, CR M. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Disease. 1987;40(5):373-383.

313. Dunbrack J. Cancer and Palliative Care: Integration and Continuity of Care.Canadian Parternership Against Cancer; 2009.

314. Price M, Lau FY. Provider connectedness and communication patterns: extending continuity of care in the context of the circle of care. BMC Health Serv Res. 2013;13:309.

315. Gaston CM, Mitchell G. Information giving and decision-making in patients with advanced cancer: a systematic review. Soc Sci Med. 2005;61(10):2252-2264.

316. Weiner JP. Doctor-patient communication in the e-health era. Isr J Health Policy Res. 2012;1(1):33.

317. Holt A. Using the telephone for narrative interviewing: a research note. Qualitative Research. 2010;10(1).

190

318. Kushniruk AW, Patel VL, Cimino JJ. Usability testing in medical informatics: cognitive approaches to evaluation of information systems and user interfaces. Proc AMIA Annu Fall Symp. 1997:218-222.

319. Sandelowski M. Combining qualitative and quantitative sampling, data collection, and analysis techniques in mixed-method studies. Res Nurs Health. 2000;23(3):246-255.

320. NVivo Qualitative Data Analysis Software [computer program]. Version 10: QSR International Pty Ltd.; 2016.

321. Cruickshank J. Positioning positivism, critical realism and social constructionism in the health sciences: a philosophical orientation. Nurs Inq. 2012;19(1):71-82.

322. Saldana J, ed The coding manual for qualitative researchers. Los Angeles. Sage. 2009.

323. Patton MQ. Enhancing the quality and credibility of qualitative analysis. Health Serv Res. 1999;34(5 Pt 2):1189-1208.

324. Draucker CB, Martsolf DS, Ross R, Rusk TB. Theoretical sampling and category development in grounded theory. Qualitative health research. 2007;17(8):1137-1148.

325. Bowen GA. Naturalistic inquiry and the saturation concept: a research note. Qualitative Research. 2008;8(137).

326. Webster F, Christian J, Mansfield E, et al. Capturing the experiences of patients across multiple complex interventions: a meta-qualitative approach. BMJ Open. 2015;5(9):e007664.

327. Hojat M, Louis DZ, Markham FW, Wender R, Rabinowitz C, Gonnella JS. Physicians' empathy and clinical outcomes for diabetic patients. Acad Med. 2011;86(3):359-364.

328. Lelorain S, Bredart A, Dolbeault S, Sultan S. A systematic review of the associations between empathy measures and patient outcomes in cancer care. Psycho-oncology. 2012;21(12):1255-1264.

329. Lobchuk MM, Bokhari SA. Linkages among empathic behaviors, physical symptoms, and psychological distress in patients with ovarian cancer: a pilot study. Oncology nursing forum. 2008;35(5):808-814.

330. Empathy. In: Pearsall J, Oxford Dictionary of English. Oxford, UK. 2003.

331. Larson EB, Yao X. Clinical empathy as emotional labor in the patient-physician relationship. JAMA. 2005;293(9):1100-1106.

332. Berwick DM. What 'patient-centered' should mean: confessions of an extremist. Health Affairs. 2009;28(4):w555-565.

333. Reeves S, Lewin S, Espin S, Zwarenstein M. Interprofessional teamwork for health and social care. Oxford: Blackwell Publishing; 2011.

191

334. Konrad EL. A Multidimensional Framework from Conceptualising Human Services Integration Initiatives. In: Marquart JM, Konrad EL, eds. Evaluating Initiatives to Integrate Human Services, New Directions for Evaluation. San Francisco: Jossey-Bass. 1996.

335. Lavoie M, Blondeau D, Martineau I. The integration of a person-centered approach in palliative care. Palliat Support Care. 2013;11(6):453-464.

336. O'Brien MA, Ellis PM, Whelan TJ, et al. Physician-related facilitators and barriers to patient involvement in treatment decision making in early stage breast cancer: perspectives of physicians and patients. Health Expect. 2013;16(4):373-384.

337. Sinding C, Hudak P, Wiernikowski J, et al. "I like to be an informed person but..." negotiating responsibility for treatment decisions in cancer care. Soc Sci Med. 2010;71(6):1094- 1101.

338. Mair FS, May C, O'Donnell C, Finch T, Sullivan F, Murray E. Factors that promote or inhibit the implementation of e-health systems: an explanatory systematic review. Bulletin of the World Health Organization. 2012;90(5):357-364.

339. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4:50.

340. Lewin S, Glenton C, Oxman AD. Use of qualitative methods alongside randomised controlled trials of complex healthcare interventions: methodological study. BMJ. 2009;339:b3496.

341. Jamieson T, Chiang M, Voruganti T, et al. Using Social Networking Analysis to Understand the Importance of Patients and Caregivers in Online Teams of Care. Paper presented at: American Medical Informatics Association2017; San Francisco.

342. Varsi C, Ekstedt M, Gammon D, Ruland CM. Using the Consolidated Framework for Implementation Research to Identify Barriers and Facilitators for the Implementation of an Internet-Based Patient-Provider Communication Service in Five Settings: A Qualitative Study. J Med Internet Res. 2015;17(11):e262.

343. Varsi C, Gammon D, Wibe T, Ruland CM. Patients' reported reasons for non-use of an internet-based patient-provider communication service: qualitative interview study. J Med Internet Res. 2013;15(11):e246.

344. Haun JN, Patel NR, Lind JD, Antinori N. Large-Scale Survey Findings Inform Patients' Experiences in Using Secure Messaging to Engage in Patient-Provider Communication and Self- Care Management: A Quantitative Assessment. J Med Internet Res. 2015;17(12):e282.

345. Wolcott V, Agarwal R, Nelson DA. Is Provider Secure Messaging Associated With Patient Messaging Behavior? Evidence From the US Army. J Med Internet Res. 2017;19(4):e103.

192

346. Lyles CR, Allen JY, Poole D, Tieu L, Kanter MH, Garrido T. "I Want to Keep the Personal Relationship With My Doctor": Understanding Barriers to Portal Use among African Americans and Latinos. J Med Internet Res. 2016;18(10):e263.

347. Burge F, Haggerty JL, Pineault R, et al. Relational continuity from the patient perspective: comparison of primary healthcare evaluation instruments. Healthc Policy. 2011;7(Spec Issue):124-138.

348. Rodriguez HP, Rogers WH, Marshall RE, Safran DG. Multidisciplinary primary care teams: effects on the quality of clinician-patient interactions and organizational features of care. Med Care. 2007;45(1):19-27.

349. Denise L. Collaboration vs. C-Three (Cooperation, Coordination, and Communication. Innovating. 2012;7(3).

350. Griffiths F, Bryce C, Cave J, et al. Timely Digital Patient-Clinician Communication in Specialist Clinical Services for Young People: A Mixed-Methods Study (The LYNC Study). J Med Internet Res. 2017;19(4).

351. Gittell JH. Organizing work to support relational co-ordination. Int. J. of Human Resource Management. 2000;11(3).

352. Gittell JH, Godfrey M, Thistlethwaite. Interprofessional collaborative practice and relational coordination: Improving healthcare through relationships. J Interprof Care. 2012;27(3).

353. Gittell JH. Relational coordination: coordinating work through relationships ofshared goals,shared knowledge and mutual respect. In: Kyriakidou O, Ozbilgin MF, eds. Relational Perspectives in Organizational Studies: Edward Elgar Pub; 2006.

354. Gittell JH. Relationships between service providers and their impact on customers. J Services Research. 2002;4(4).

355. Corbin J, Strauss A. Grounded Theory Research: Procedures, Canons, and Evaluative Criteria. Qualitative Sociology. 1990;13(1).

356. Easley J, Miedema B, Carroll JC, O'Brien MA, Manca DP, Grunfeld E. Patients’ experiences with continuity of cancer care in Canada: Results from the CanIMPACT study. Canadian Family Physician. 2016;62.

357. Ross J, Stevenson F, Lau R, Murray E. Factors that influence the implementation of e- health: a systematic review of systematic reviews (an update). BMC Implementation Science. 2016;11.

358. Straus SE, Tetroe J, Graham I. Defining knowledge translation. CMAJ. 2009;181(3-4):165- 168.

193

359. Pawson R, Greenhalgh T, Harvey G, Walshe K. Realist review--a new method of systematic review designed for complex policy interventions. J Health Serv Res Policy. 2005;10 Suppl 1:21-34.

360. Mohr DC, Schueller SM, Riley WT, et al. Trials of Intervention Principles: Evaluation Methods for Evolving Behavioral Intervention Technologies. J Med Internet Res. 2015;17(7):e166.

361. Brown CH, Ten Have TR, Jo B, et al. Adaptive designs for randomized trials in public health. Annu Rev Public Health. 2009;30:1-25.

362. Pagliari C. Design and evaluation in eHealth: challenges and implications for an interdisciplinary field. J Med Internet Res. 2007;9(2):e15.

363. Kaplan B. Evaluating informatics applications--some alternative approaches: theory, social interactionism, and call for methodological pluralism. Int J Med Inform. 2001;64(1):39-56.

364. Resnicow K, Strecher V, Couper M, et al. Methodologic and design issues in patient- centered e-health research. Am J Prev Med. 2010;38(1):98-102.

365. Zheng K, Haftel HM, Hirschl RB, O'Reilly M, Hanauer DA. Quantifying the impact of health IT implementations on clinical workflow: a new methodological perspective. J Am Med Inform Assoc. 2010;17(4):454-461.

366. Ozkaynak M, Brennan PF, Hanauer DA, et al. Patient-centered care requires a patient- oriented workflow model. J Am Med Inform Assoc. 2013;20(e1):e14-16.

367. Green BB, Anderson ML, Cook AJ, et al. e-Care for heart wellness: a feasibility trial to decrease blood pressure and cardiovascular risk. Am J Prev Med. 2014;46(4):368-377.

368. Appari A, Johnson E. Information Security and Privacy in Healthcare: Current State of Research. 2008.

369. Smits R, Bryant J, Sanson-Fisher R, et al. Tailored and integrated Web-based tools for improving psychosocial outcomes of cancer patients: the DoTTI development framework. J Med Internet Res. 2014;16(3):e76.

370. Oken MM, Creech RH, Tormey DC, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J of Clin Onc. 1982;5(6):649-655.

Appendix

194

195

APPENDIX 1: Permission to Reproduce eCCM Diagram

______From: Perry Sent: Friday, March 17, 2017 6:18 PM To: Teja Voruganti Subject: Re: eCCM diagram

Yes, you have our permission. We are revising the model again. Sorry we are not done as of yet. Best wishes!

Perry Gee

Sent from my iPhone

On Mar 17, 2017, at 1:05 PM, Teja Voruganti wrote: Dear Dr. Gee, I would like to ask the permission of you and your co-authors to reproduce the eCCM diagram (Figure 2) from your article in JMIR (2015): "The eHealth Enhanced Chronic Care Model: A Theory Derivation Approach" in my PhD thesis conducted at the Institute of Health Policy, Management and Evaluation at the University of Toronto.

I believe the copyright is embedded in the figure but will appropriately provide the citation in the caption of the figure in my thesis as such: Gee PM, Greenwood DA, Paterniti DA, Ward D and Miller LMS. J Med Internet Res 2015;17(4)e86, http://www.jmir.org/2015/4/e86/

Thank you, Teja Voruganti

196

APPENDIX 2: MEDLINE and EMBASE Search Strategy for Scoping Review NOTE: These search strategies were constructed under the guidance of Marina Englesakis, an information specialist at the University of Toronto.

MEDLINE(R) (Ovid Interface) 1946- Week 1 March 2016

1 exp internet/ 2 internet:.mp. 3 exp informatics/ 4 exp computer-assisted instruction/ 5 online.mp. 6 on-line.mp. 7 (virtual not virtual realit:).mp. 8 world wide web:.mp. 9 worldwide web:.mp. 10 www.tw. 11 web.tw,kw. 12 web page:.mp. 13 webpage:.mp. 14 web site:.mp. 15 website:.mp. 16 exp computer communication networks/ (portal? and (internet* or online or on-line or computer* or electronic or web or webbased 17 or telehealth or tele-health)).mp. 18 (portal?? adj3 patient??).mp,kw. 19 ehealth.mp. 20 e-health.mp. 21 semantic web?.mp. 22 blog:.mp. 23 folksonom:.mp. 24 mashup:.mp. 25 pod cast:.mp. 26 podcast:.mp. 27 (social adj2 bookmark:).mp. 28 (social adj2 book-mark:).mp. 29 (social adj2 software:).mp. 30 (sociable adj2 technolog:).mp. 31 (social adj2 technolog:).mp.

197

32 tag cloud:.mp. 33 (virtual adj2 collabor:).mp. 34 web api:.mp. 35 (web adj2 syndicat:).mp. 36 webcast:.mp. 37 web-cast:.mp. 38 web-log:.mp. 39 weblog:.mp. 40 wiki:.mp. 41 social network:.mp. 42 (social adj2 utilit:).mp. 43 chat.mp. 44 chatroom*.mp. 45 chat-room*.mp. 46 chat group*.mp. 47 chatgroup*.mp. 48 chat techno*.mp. 49 meebo.mp. 50 "second life".mp. 51 secondlife.mp. 52 uhealth.mp. 53 (ubiquit* adj2 comput*).mp. 54 "u-comput*".mp. 55 patientslikeme*.mp. 56 "www.patientslikeme.com".mp. 57 (digital adj2 divid*).mp. 58 (digital adj2 inequit*).mp. 59 exp information systems/ 60 exp computer systems/ 61 exp telecommunications/ 62 exp user-computer interface/ 63 exp computer literacy/ 64 exp attitude to computers/ 65 "u-health*".mp. 66 "e-health*".mp. 67 twitter.mp. 68 tweet.mp.

198

69 epatient*.mp. 70 "e-patient*".mp. 71 edoctor*.mp. 72 e-doctor*.mp. 73 ephysician*.mp. 74 "e-physician*".mp. 75 elearn*.mp. 76 "e-learn*".mp. 77 Webcasts/ 78 Webcasts as topic/ 79 microblog*.mp. 80 micro-blog*.mp. 81 facebook*.mp. 82 Social Media/ 83 Social Networking/ 84 "information and communication technolog*".mp. 85 ict.mp. 86 etechnolog*.mp. 87 e-technolog*.mp. 88 "health 2.0".mp. 89 "web 2.0".mp. 90 "academia.edu".mp. 91 bebo.mp. 92 dailystrength*.mp. 93 livestrong*.mp. 94 epernicus*.mp. 95 experienceproject*.mp. 96 carepages*.mp. 97 caringbridge*.mp. 98 flickr*.mp. 99 fuelmyblog*.mp. 100 friendica*.mp. 101 friendster*.mp. 102 googleplus*.mp. 103 google plus.mp. 104 hi5.mp. 105 jaiku*.mp.

199

106 kiwibox*.mp. 107 linkedin*.mp. 108 myopera*.mp. 109 myspace*.mp. 110 netlog*.mp. 111 ning.mp. 112 "ning.com".mp. 113 "www.ning.com".mp. 114 orkut*.mp. 115 pinterest*.mp. 116 researchgate*.mp. 117 sciencestage*.mp. 118 sonico.mp. 119 stumbleupon*.mp. 120 twitter*.mp. 121 wasabi*.mp. 122 "wasabi.com".mp. 123 wellwer*.mp. 124 wooxie*.mp. 125 social awareness*.mp. 126 "aim pages".mp. 127 badoo*.mp. 128 cyworld*.mp. 129 drconnected*.mp. 130 icarecafe*.mp. 131 sanewire*.mp. 132 whoissick*.mp. 133 (social adj2 informatic*).mp. 134 (social adj2 infomatic*).mp. 135 diabetesmine*.mp. 136 "diabetesmine.com".mp. 137 google wave*.mp. 138 "windows live".mp. 139 "live messenger*".mp. 140 "aim messenger*".mp. 141 "yahoo messenger*".mp. 142 "microsoft messenger*".mp.

200

143 compuserv*.mp. 144 "america online".mp. 145 usenet?.mp. 146 (mobile adj1 technolog*).mp. 147 (technolog* adj1 based adj1 intervention*).mp. 148 mcare.tw. 149 "m-care".tw. 150 "connected care".tw. 151 (health* adj1 inform* adj1 techn*).mp. 152 Web Browser/ 153 browser?.mp,kw. 154 (touchscreen* or touch-screen*).tw,kw. 155 (web-bas* or webbas*).mp,kw. 156 Interactive Health Communication.mp. 157 internet communication tool.mp. 158 internet communication.mp. (telemedicine/ or remote consultation/) not teledermatology.mp. not teleradiology.mp. not telepathology.mp. [mp=title, abstract, original title, name of substance word, subject 159 heading word, keyword heading word, protocol supplementary concept word, rare disease supplementary concept word, unique identifier] 160 or/1-159 [MEDLINE Internet Hedge] 161 Chronic Disease/ 162 (chronic* adj2 ill*).mp,kw. 163 (chronic* adj disease*).mp,kw. 164 (chronic* adj2 disease*).mp,kw. 165 polypatholog*.mp,kw. 166 poly-patholog*.mp,kw. 167 multiple comorbid*.mp,kw. 168 multiple co-morbid*.mp,kw. 169 (chronic adj2 patholog*).mp,kw. 170 pluri-patholog*.mp,kw. 171 pluripatholog*.mp,kw. 172 multiple longterm condition?.mp,kw. 173 multiple long-term condition?.mp,kw. 174 multiple chronic condition?.mp,kw. 175 (multi-morbid* adj2 condition?).mp,kw. 176 (chronic* adj2 condition?).mp,kw.

201

177 Comorbidity/ 178 (long term adj2 condition?).mp,kw. 179 (longterm adj2 condition?).mp,kw. 180 (chronic adj2 medical adj2 problem*).mp,kw. 181 multimorbid*.mp,kw. 182 (multi-component? adj2 chronic).mp,kw. 183 (multicomponent? adj2 chronic).mp,kw. 184 comorbid*.mp,kw. 185 co-morbid*.mp,kw. 186 multimorbid*.mp,kw. 187 multi-morbid*.mp,kw. 188 (complex* adj3 condition?).mp,kw. 189 (complex adj2 care?).mp,kw. 190 or/161-189 [Chronic Illness or Polypathology or Multiple Morbidity] 191 exp program evaluation/ 192 exp program development/ 193 exp pilot project/ 194 ((patient?? or inpatient?? or outpatient??) adj1 portal?).mp,kw. 195 platform?.mp,kw. 196 tool?.mp,kw. 197 toolkit??.mp,kw. 198 intervention studies/ 199 intervention?.mp,kw. 200 prototype?.mp,kw. 201 kiosk??.mp,kw. 202 project?.mp,kw. 203 ((patient? or inpatient? or outpatient?) adj2 program?).mp,kw. 204 ((patient? or inpatient? or outpatient?) adj2 programme?).mp,kw. 205 professional-patient relations/ 206 or/191-205 [Intervention or Portal or Tool and related terms] 207 160 and 190 and 206 [Internet and Chronic Illness and Intervention Hedges] 208 limit 207 to (english language and humans) 209 remove duplicates from 208

202

EMBASE (Ovid Interface) 1946- Week 1 March 2016

1 internet:.mp. 2 online.mp. 3 on-line.mp. 4 (virtual not virtual realit:).mp. 5 world wide web:.mp. 6 worldwide web:.mp. 7 www.tw. 8 web.tw,kw. 9 web page:.mp. 10 webpage:.mp. 11 web site:.mp. 12 website:.mp. (portal? and (internet* or online or on-line or computer* or electronic or web or webbased or 13 telehealth or tele-health)).mp. [added March 17 2015] 14 (portal?? adj3 patient??).mp,kw. [added March 17b 2015] 15 ehealth.mp. 16 e-health.mp. 17 semantic web?.mp. 18 blog:.mp. 19 folksonom:.mp. 20 mashup:.mp. 21 (social adj2 bookmark:).mp. 22 (social adj2 book-mark:).mp. 23 (social adj2 software:).mp. 24 (sociable adj2 technolog:).mp. 25 (social adj2 technolog:).mp. 26 tag cloud:.mp. 27 (virtual adj2 collabor:).mp. 28 web api:.mp. 29 (web adj2 syndicat:).mp. 30 webcast:.mp. 31 web-cast:.mp. 32 web-log:.mp. 33 weblog:.mp. 34 wiki:.mp.

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35 social network:.mp. 36 (social adj2 utilit:).mp. 37 chat.mp. 38 chatroom*.mp. 39 chat-room*.mp. 40 chat group*.mp. 41 chatgroup*.mp. 42 chat techno*.mp. 43 meebo.mp. 44 "second life".mp. 45 secondlife.mp. 46 uhealth.mp. 47 (ubiquit* adj2 comput*).mp. 48 "u-comput*".mp. 49 patientslikeme*.mp. 50 "www.patientslikeme.com".mp. 51 (digital adj2 divid*).mp. 52 (digital adj2 inequit*).mp. 53 "u-health*".mp. 54 "e-health*".mp. 55 epatient*.mp. 56 "e-patient*".mp. 57 edoctor*.mp. 58 e-doctor*.mp. 59 ephysician*.mp. 60 "e-physician*".mp. 61 microblog*.mp. 62 micro-blog*.mp. 63 facebook*.mp. 64 "information and communication technolog*".mp. [added May 2 2012] 65 ict.mp. [added May 2 2012] 66 etechnolog*.mp. 67 e-technolog*.mp. 68 "health 2.0".mp. 69 "web 2.0".mp. 70 "academia.edu".mp. 71 bebo.mp.

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72 dailystrength*.mp. 73 livestrong*.mp. 74 epernicus*.mp. 75 experienceproject*.mp. 76 carepages*.mp. 77 caringbridge*.mp. 78 flickr*.mp. 79 fuelmyblog*.mp. 80 friendica*.mp. 81 friendster*.mp. 82 googleplus*.mp. 83 google plus.mp. 84 hi5.mp. 85 jaiku*.mp. 86 kiwibox*.mp. 87 linkedin*.mp. 88 myopera*.mp. 89 myspace*.mp. 90 netlog*.mp. 91 ning.mp. 92 "ning.com".mp. 93 "www.ning.com".mp. 94 orkut*.mp. 95 pinterest*.mp. 96 researchgate*.mp. 97 sciencestage*.mp. 98 sonico.mp. 99 stumbleupon*.mp. 100 wasabi*.mp. 101 "wasabi.com".mp. 102 wellwer*.mp. 103 wooxie*.mp. 104 social awareness*.mp. 105 "aim pages".mp. 106 badoo*.mp. 107 cyworld*.mp. 108 drconnected*.mp.

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109 icarecafe*.mp. 110 sanewire*.mp. 111 whoissick*.mp. 112 (social adj2 informatic*).mp. 113 (social adj2 infomatic*).mp. 114 diabetesmine*.mp. 115 "diabetesmine.com".mp. 116 google wave*.mp. 117 "windows live".mp. 118 "live messenger*".mp. 119 "aim messenger*".mp. 120 "yahoo messenger*".mp. 121 "microsoft messenger*".mp. 122 compuserv*.mp. 123 "america online".mp. 124 (technolog* adj1 based adj1 intervention*).mp. [June 10 2014] 125 mcare.tw. 126 "m-care".tw. 127 "connected care".tw. 128 (web-bas* or webbas*).mp,kw. [added March 18 2015] 129 internet/ 130 exp information science/ 131 telehealth/ 132 information system/ 133 online system/ 134 computer system/ 135 telecommunication/ 136 teleconference/ 137 computer interface/ 138 human computer interaction/ 139 social network/ 140 social media/ 141 (health* adj1 communicat* adj1 techn*).mp. 142 exp computer network/ 143 webcast/ 144 interactive health communication.mp. 145 internet communication tool.mp.

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146 internet communication.mp. telemedicine/ not teledermatology.mp. not teleradiology.mp. not telepathology.mp. 147 [mp=title, abstract, heading word, drug trade name, original title, device manufacturer, drug manufacturer, device trade name, keyword] 148 or/1-147 [EMBASE Internet Hedge] 149 Chronic Disease/ 150 (chronic* adj2 ill*).mp,kw. 151 (chronic* adj disease*).mp,kw. 152 (chronic* adj2 disease*).mp,kw. 153 polypatholog*.mp,kw. 154 poly-patholog*.mp,kw. 155 multiple comorbid*.mp,kw. 156 multiple co-morbid*.mp,kw. 157 (chronic adj2 patholog*).mp,kw. 158 pluri-patholog*.mp,kw. 159 multiple longterm condition?.mp,kw. 160 multiple long-term condition?.mp,kw. 161 (multi-morbid* adj2 condition?).mp,kw. 162 (chronic* adj2 condition?).mp,kw. 163 Comorbidity/ 164 (long term adj2 condition?).mp,kw. 165 (longterm adj2 condition?).mp,kw. 166 (chronic adj2 medical adj2 problem*).mp,kw. 167 multimorbid*.mp,kw. 168 (multi-component? adj2 chronic).mp,kw. 169 (multicomponent? adj2 chronic).mp,kw. 170 comorbid*.mp,kw. 171 co-morbid*.mp,kw. 172 multimorbid*.mp,kw. 173 multi-morbid*.mp,kw. 174 (complex* adj3 condition?).mp,kw. 175 (complex adj2 care?).mp,kw. 176 or/149-175 [EMBASE Chronic Illness or Polypathology or Multiple Morbidity] 177 exp program evaluation/ 178 exp program development/ 179 exp pilot project/ 180 ((patient?? or inpatient?? or outpatient??) adj1 portal?).mp,kw.

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181 platform?.mp,kw. 182 tool?.mp,kw. 183 toolkit??.mp,kw. 184 intervention studies/ 185 intervention?.mp,kw. 186 prototype?.mp,kw. 187 kiosk??.mp,kw. 188 project?.mp,kw. 189 ((patient? or inpatient? or outpatient?) adj2 program?).mp,kw. 190 ((patient? or inpatient? or outpatient?) adj2 programme?).mp,kw. 191 or/177-190 [Intervention or Portal or Tool & related terms] 192 148 and 176 and 191 [EMBASE Internet and Chronic Illness and Intervention Hedges] 193 limit 192 to (human and english language) 194 remove duplicates from 193

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APPENDIX 3: Google Search Strategy for Scoping Review

• the first 100 hits of the following strings were examined for electronic communication tools that meet the specified inclusion and exclusion criteria

Key Terms

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APPENDIX 4: Data Extraction Form for Published Articles for Scoping Review

Reviewer response (not more than 1 sentence) 1. Citation First Author: Title: Journal: Year: 2. What type of publication  original research study (observational study, randomized is this paper? controlled trial etc.)  editorial/commentary/news and views  review/meta-analysis  protocol  RCT  Review  other:______

3. Is there a communication  Yes component to the tool?  No If no, do not continue. 4. Is the communication  Primary component the primary  Supplemental feature or a supplemental feature? 5. What is the primary  Unstructured (Patient-provider free-form communication) functioning of the  Structured (Guided feedback) communication component of the tool? 6. Is the tool findable  URL: (website url etc.)?  No, further information about the tool could not be found

7. What is the country of Please specify: origin? 8. At what stage of study is  Development the tool?  Feasibility and piloting  Evaluation  Implementation  Other: ______

9. In what context or setting  Healthcare is the tool used?  Non-healthcare  Other, please specify: ______If non-healthcare tools, exclude

Further description, if needed:

10. What clinical/disease area  Cardiovascular disease

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is the tool focused on?  Cancer  Stroke  Chronic respiratory diseases  Diabetes  Mental health  Non-specific  Other: ______

11. What is the primary  Patient-healthcare provider communication purpose of the tool?  Communication that is not between patients and healthcare providers  Health information storage, such as an EHR  Other: ______

12. List all other functions of Description: the tool beyond that mentioned in 6.

13. Have any published  Yes studies been conducted  What study design?: which evaluated this tool?  Randomized controlled trial  Observational study  Cohort  Case-control study  Non-randomized controlled trial  Controlled before and after study  Qualitative study  Cross-sectional study 14. If observational study, is it  Prospective prospective or  Retrospective retrospective? 15. Is this study a randomized  Yes controlled trial?  If it was evaluated with the Medical Research Council Framework for Complex Interventions, check phase:  Phase I  Phase II  Phase III  Phase IV

 No

Description: 16. If answered yes to 8, what Description: outcomes were measured?

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17. What was the study Description: sample size? 18. What is the length of Description: follow-up?  N/A 19. What medium does it use?  Web-based application  Hybrid web and software application  Other: ______

20. Is this tool a component of  Yes another system/platforms  If yes, how: ______(i.e. EHR, care plan)??  No  If no, are there future plans for connectivity:  Yes, how: ______ No

21. What credentials are used  Email address for logging in?  Password  Username  Banking credentials  Other: ______22. What form of  Synchronous communication communication does the  Asynchronous communication (end-users do not have to use tool work by? the tool in real-time)  Other: ______

23. If asynchronous  Yes communication, is it time-  No limited? 24. Does the tool engage  Select all that apply patients and/or caregivers?  Adult patients (default)  Children  Family Caregivers  Parents  Paid Caregivers 25. What type of health care  Nurse provider is intended to use  Physician the tool?  Physician Assistant  Pharmacist  Allied Health Professional (Physiotherapist, Dietician, Social Worker, Psychologist etc.)

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 Other: ______

26. What is the study  Academic context/setting of use?  Business (i.e. CVS, Walmart)  Primary care  Tertiary care outpatient clinics  Inpatient hospital units  Other: ______

27. What area of clinical Describe: specialty is/are the end- users? 28. Does the tool allow for  Yes team-based  No communication (more  Unclear than a single health care provider can communicate)? 29. Does the patient  Yes communicate with their  No own healthcare provider?  Unclear 30. How is the tool made  Freely available available? (select all that  Registration required to use apply)  Payment required  User pays  Organizational license  Other form of monetary revenue: ______

31. What is the name of the Description: tool?

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APPENDIX 5: Data Extraction Form for Internet Search Results for Scoping Review

Reviewer response (not more than 1 sentence) 1. URL 2. Type of website  Business  Healthcare  Other: ______

3. Name of the organization 4. Name of the tool 5. Tool developer 6. Terminology for the platform 7. Linked to health record?  Yes  No  Unclear 8. Payment/compensation  Yes for healthcare providers?  If yes, please specify: ______ No  Unclear 9. Target population 10. Does this tool engage  Yes patients and/or caregivers?  No  Unclear

11. What type of provider is  Doctor intended to use this tool  Nurse with the patient?  Other:______

12. What form of  Synchronous communication communication does the  Asynchronous communication (end-users do not have to use tool work by? the tool in real-time)  Other: ______

13. If asynchronous  Yes communication, is it time-  No limited?  Unclear

14. Does the tool allow for  Yes team-based  No communication (more  Unclear than a single health care provider can communicate)? 15. Does this tool allow the  Yes patient to communicate  No

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with their own healthcare  Unclear provider? 16. Can patients self-register  Yes to use the tool?  No (prior verification is required)  Unclear 17. Has the tool been  Yes identified through the  No published literature? 18. Country of origin: 19. Year last updated:

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APPENDIX 6: Coding Framework for Scoping Review Coding Framework

Article Characteristics Setting Tertiary care- the intervention is evaluated in a tertiary care setting, may be outpatient care (i.e. healthcare provider is a specialist or works in a specialty clinic) Primary care- the intervention is evaluated in a primary care/community setting (i.e. healthcare provider is in primary care or general practice) Academic- the intervention is evaluated through an academic setting (i.e. healthcare provider is based out of a university department, such as Behavioral Sciences) Business- intervention is evaluated in a business context (i.e. through CVS Pharmacy, Walmart) Tool Characteristics Medium of communication Website- URL accessible via an internet browser (whether mobile or computer-based) Hybrid website/software application- an intervention which uses a software application and uploads information to the internet, which may have a web-based interface as well Functionality Asynchronous- non-concurrent communication between patient and healthcare provider Synchronous- patient and healthcare provider(s) must use the tool at the same time (ie telephone) Type of communication Unstructured communication (patient-provider free-form)- two-way unstructured text-based dialogue Structured communication- structured responses or recommendations by a trained end-user (healthcare provider/therapist/research assistant) to information input from the patient Intended use Lifestyle/behavior modification- altering habits or behaviors to improve patient management of illness Symptom management- reporting, monitoring or medical treatment related to the care of specific symptoms Care planning- developing and adherence to protocol for administration and receipt of care and medical procedures Medication adherence- adherence to prescribed medications Evaluation Study designa Randomized controlled trial- an experimental study in which people are randomly allocated to different interventions Cohort study- a study in which a defined group of people (the cohort) is followed over time, to examine associations between different interventions received and subsequent outcomes. A ‘prospective’ cohort study recruits participants before any intervention and follows them into the future. A ‘retrospective’ cohort study identifies subjects from past records describing the interventions received and follows them from the time of those records Case-control study- a study that compares people with a specific outcome of interest (‘cases’)

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with people from the same source population but without that outcome (‘controls’), to examine the association between the outcome and prior exposure. Quasi-experimental/Non-randomized controlled trial- an experimental study in which people are allocated to different interventions using methods that are not random. Cross-sectional study- a study that collects information on interventions (past or present) and current health outcomes, i.e. restricted to health states, for a group of people at a particular point in time, to examine associations between the outcomes and exposure to interventions Cost-effectiveness analysis- a study evaluating costs, especially relative to effect or utility of an intervention Qualitative study- involving a method of data collection comprising interviews and focus groups; data is narrative in nature. Approaches include grounded theory, ethnography, phenomenology Stage of evaluationb Development- identifying evidence base, identifying or developing theory, modelling processes and outcomes Feasibility/piloting- testing procedures, estimating recruitment and retention, determining sample size Evaluation- assessing effectiveness, understanding change processes, assessing cost- effectiveness Implementation- dissemination, surveillance and monitoring, long-term follow-up Outcomes Health outcomes- clinical data, quality of life or care, healthcare utilization, illness knowledge Usability318- ease of use related outcomes Usage- how the tool was used, e.g. frequency of use Costs- medical costs, costs related to implementation or use Acceptability/Feasibility (collected via questionnaire)318- described as feasibility or acceptability measure including satisfaction with implementation, interest, willingness-to- use, attitudes Experience (open-ended/unstructured responses)- focused on perceptions around the intervention Clinical- clinical data, quality of life or care, healthcare utilization, knowledge aAdapted from the Cochrane Handbook for Systematic Reviews215 bBased on the MRC 2008 Framework for the Evaluation of Complex Interventions171

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APPENDIX 7: Study conclusions on primary outcome by article (protocols excluded)a

Tool Reference Interventio Disease Primary Samp Follow- Outcome Conclusion # n context or Co- le up description interven Size tion Randomized controlled trials (RCTs) 1 Armstrong Online Atopic Primary 156 12 Atopic No difference et al. model for dermatitis months dermatitis on follow-up 2015231 follow-up disease management severity 6 van der Internet- Asthma Co- 200 12 Asthma- Significant Meer et al. based self- interventi months related improvement 2009236 management on quality of in quality of life life 7 Allen et al. E-coaching 1. Pain Primary 121 1 month Use One third of 2008237 2. participants Depression used the 3. Mobility email component of the program. Most patients were interested in further e- coaching. 7 Leveille et E-coaching 1. Pain Primary 142 3 Number of No difference al. 2009238 2. months days in poor between Depression health groups 3. Mobility 9 Ross et al. Patient- CVD Co- 107 12 Self-efficacy No 2004240 accessible interventi months significant online on difference in medical self-efficacy record 12 Mota Facebook Mental Primary 60 3 Depression Significant Pereira et al. health months symptoms reduction in 2014244 depressive symptoms 16 Nguyen et Internet- COPD Primary 125 12 Level of No al. 2013251 based months dyspnea significant collaborative with difference in self- physical dyspnea with monitoring activity physical activity 17 Solomon et Web-based 1. Asthma Primary 201 3 Patient Significant al. 2012252 intervention 2. months activation difference in Hypertensi patient on activation 3. Diabetes between groups 19 Brennan et Technology- CVD Primary 282 6 Physical and Significant al. 2010254 enhanced months mental difference in practice functional physical and clinical mental status functional

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clinical status between groups 22 Bond et al. Internet- Diabetes Primary 62 6 1. HbA1C Significant 2007212 based self- months 2. Weight reductions in management 3. HbA1C, Cholesterol weight, 4. HDL cholesterol; significant improvement in HDL 26 Oerlemans Cognitive Irritable Primary 75 3 1. 1. et al. Behaviour bowel months Feasibility Intervention 2011258 Therapy syndrome 2. is feasible with Dysfunction 2. No personal al cognitions significant digital reduction in assistant dysfunctional cognitions 28 Kristjansdot Web-based Chronic Primary 140 5 Catastrophiz Significantly tir et al. self- pain months ing thoughts fewer 2013260 management catastrophizin g thoughts 28 Kristjansdot Web-based Chronic Primary 140 11 Catastrophiz No tir et al. self- pain months ing thoughts significant 2013261 management difference 29 McMahon et Internet- Diabetes Primary 104 12 1. Glucose Significant al. 2005264 based care months control reductions in management 2. Blood HbA1C and pressure systolic blood control pressure 29 Fonda et al. Internet- Diabetes Primary 104 12 Diabetes Significant 2009265 based care months distress reduction in management diabetes distress 30 Homko et Internet- Diabetes Primary 63 20 1. System System was al. 2007266 based months use used by the telemedicine 2. Maternal majority of system feeling of participants. diabetes Significant self-efficacy improvement in self- efficacy between groups at follow-up 31 Ralston et Web-based Diabetes Primary 83 12 HbA1C Significant al. 2009267 care months levels reduction in management HbA1C 32 Tang et al. Personal Diabetes Co- 415 12 HbA1C No 2013268 Health interventi months levels significant Record on reduction in HbA1C 33 Zutz et al. Virtual CVD Co- 15 3 1. Use of the 2007269 cardiac interventi months Feasibility tool was

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rehabilitatio on 2. HDL feasible and n cholesterol safe 3. Significant Triglyceride improvement s in cholesterol, 4. Total triglycerides, cholesterol exercise to HDL capacity, cholesterol weekly rate ratio of physical 5. Exercise activity, and capacity exercise- 6. Weekly specific self- physical efficacy Activity 7. Exercise- specific self- efficacy 34 Quinn et al. Patient web Diabetes Co- 163 12 HbA1C Significant 2011222 portal interventi months levels reduction in on HbA1C 35 Liebreich et Website and Diabetes Primary 49 3 1. Significant al. 2009270 email-linked months Feasibility between- counselling 2. Physical group intervention activity difference in moderate to vigorous physical activity at follow-up 36 Bergmo et Web-based Atopic Primary 98 12 1. Self- Significant al. 2009271 consultations dermatitis months management reduction in 2. Eczema number of severity skin care 3. treatments Healthcare per week, and resource use overall healthcare visits 38 Green et al. Web-based Cardiovasc Primary 101 6 1. Weight Significant 2014367 dietician-led ular disease months 2. Blood reduction in team care pressure weight, BP intervention 3. and CVD risk Framingham in the 10-year risk intervention score group compared to the usual care group 39 Ruland et al. Interactive Breast and Primary 325 12 1. Symptom Significant 2013278 Health prostate months distress reduction in Communicat cancer 2. global ion Depression symptom Application 3. Self- distress efficacy between 4. Health- groups

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related quality of life 5. Social support 39 Børøsund et Interactive Breast and Primary 167 6 1. No difference al. 2014279 Health prostate months Comorbidity between Communicat cancer 2. Symptom groups ion distress Application 3. Anxiety and depression 4. Self- efficacy 5. System use 40 Barberan- Information 1. COPD Primary 55 12 Long-term No Garcia et al. and 2. CHF months sustainabilit significant 2014243 Communicat 3. Stroke y of difference in ion training- aerobic Technology induced capacity (ICT) enhancemen t of aerobic capacity 41 Trautmann Chat Chronic Primary 18 1 month Duration, No difference et al. migraines frequency, between 2008280 intensity of groups headache Non-randomized studies Prospective cohort studies 2 Riipa et al. Patient Non- Primary 222 6 months 1. 1. Reduction 2014232 portal specific Healthcare in visits to utilization nurses among 2. Patient tool users activation 2. No difference in patient activation 4 Ryan et al. Internet- Diabetes Co- 24 13 1. 1. 2013217 based suite interventi months Feasibility Intervention of on 2. HbA1C was feasible. applications 3. LDL 2. Significant cholesterol decrease in 4. HDL HbA1C, LDL cholesterol cholesterol, 5. Triglycerides, Triglycerid Total es cholesterol 6. Total cholesterol 5 Hsiao et al. Secure Chronic Primary 127 8 months Use of Participants 2011235 electronic respiratory messaging did not use messaging disease service messaging system service because it

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was too technically cumbersome, lacked “personal touch”, was inconvenient 11 Wayne et al. Smartphone- Diabetes Primary 21 6 months HbA1C Significant 2014242 assisted levels reduction in intervention HbA1C at follow-up 23 Komives et Patient Non- Primary 3688 12 1.Satisfacti Patients were al. 2005221 portal specific months on satisfied with 2. Monthly the tool. costs Office visit costs were reduced by $1.92 (USD) per month 24 Gomez et al. Internet- HIV/AIDS Co- 10 Not Feasibility Tool was 2002257 based self- interventi specified feasible to management on use 25 Gulmans et Web-based Cerebral Primary 30 6 months 1. 1. Tool was al. 2010216 system for Palsy Feasibility technically patient- 2. robust and professional Communic reliable and ation 2. Produced interprofessi frequency improvement onal in frequency communicati of patient- on provider communicati on 27 Nes et al. Web-based Diabetes Primary 15 3 months Feasibility Tool was 2012259 diaries feasible to use 28 Kristjansdot Web-based Chronic Primary 6 1 month Feasibility The tir et al. self- pain intervention 2011262 management was rated as supportive, meaningful and user- friendly by the majority of participants 39 Ruland et al. Interactive Breast and Primary 74 8 months Content The 2007273 Health prostate analysis intervention Communicat cancer was received ion positively by Application participants Retrospective cohort studies 3 Lau et al. Patient Diabetes Co- 157 up to 2 HbA1C Significant 2014234 portal interventi years level reduction in on HbAIC levels

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10 Jones et al. Web portal 1. CVD Co- 2282 12 Types of Identified 2015241 2. Diabetes interventi months users eight distinct on user groups based on cluster analysis of usage data 20 Sarkar et al. Patient Diabetes Co- 14102 6 months Association Health 2010255 portal interventi of use with literacy was on health negatively literacy associated with use of the patient portal 14 Harris et al. Shared Diabetes Primary 2924 15 1. HbA1C Using 2009248 medical months 2. Blood electronic record pressure secure 3. LDL messaging cholesterol was 4. associated Outpatient with better visits glycemic control and increased health services utilization 14 Weppner et Shared Diabetes Co- 6185 48 Initial and One third of al. 2010249 medical interventi months subsequent elderly users record on use of the continued to shared use the shared medical medical record record at follow-up Quasi-experimental/non-randomized studies 2 Riipa et al. Patient Non- Primary 876 6 months Patient No difference 2014233 portal specific activation in patient activation 37 Meglic et al. Information Depression Primary 46 6 months 1. A significant 2010272 and Medication association Communicat adherence between ion 2. medication Technology Depression adherence (ICT) symptoms and portal use and difference on depression symptoms between groups at follow-up 40 Barberan- Information COPD Primary 173 22 Long-term Significant Garcia et al. and months sustainabili difference 2014243 Communicat ty of between ion training- groups on the

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Technology induced 6-minute (ICT) enhanceme walk test at nt of follow-up aerobic capacity 40 Barberan- Information 1. COPD Primary 109 12 Long-term No Garcia et al. and 2. CHF months sustainabili significant 2014243 Communicat 3. Stroke ty of difference ion training- between Technology induced groups at (ICT) enhanceme follow-up nt of aerobic capacity Cross-sectional/survey 12 Lee et al. Facebook Non- Primary 4510 N/A Patient use 37% of 2016245 specific (Survey) of email patients and contacted Facebook their to contact physicians physicians via email; 18% via Facebook in the previous six months Cost-effectiveness studies 14 Fishman et Shared Hypertensi Primary 778 12 Cost- 1% al. 2013247 medical on months effectiveness improvement record in number of patients with controlled blood pressure costs $16.65 Qualitative studies 8 Nilsson et Information Non- Primary 2 5 Experiences Communicati al. 2006239 and specific months on was Communicat improved ion because of Technology increased (ICT) accessibility 21 Zickmund et Patient Diabetes Co- 39 N/A Impact on Patients al. 2008256 portal interventi patient- expressed on provider dissatisfactio relationship n with on using the provider web-based communicati portal on/ responsivenes s, the inability to obtain medical information because of

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the portal 28 Jelin et al. Web-based Fibromyalg Primary 7 1 month Experiences Participants 2012263 self- ia experienced management the follow-up program as motivating and supportive 39 Andersen et Interactive Breast and Primary 60 15 Experiences An online al. 2009274 Health prostate months application to Communicat cancer address ion patient needs Application for information may improve quality of care 39 Grimsbø et Interactive Breast and Primary 10 3 Experiences The online al. 2012275 Health prostate months application is Communicat cancer effective at ion providing Application support but may also remind patients of uncertainty related to their disease 39 Grimsbø et Interactive Breast and Primary 60 15 Experiences The al. 2011277 Health prostate months application is Communicat cancer an important ion service to Application address unmet needs to help manage their illness 39 Grimsbø et Interactive Breast and Primary 60 15 Experiences E- al. 2012276 Health prostate months communicati Communicat cancer on is feasible ion to relieve Application patients' emotional distress aIncludes multiple studies done on the same tool (as designated by tool number). Tools only described in protocols are excluded from this table. bAbbreviations: COPD- chronic obstructive pulmonary disease, CVD- cardiovascular disease, CHF- congestive heart failure, HbA1C- glycosylated hemoglobin, HDL- high-density lipoprotein, LDL- low-density lipoproteins

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Conclusions • 18/27 RCTs where the tool was evaluated as a primary intervention showed a significant improvement on the primary outcome due to the intervention. Of these studies evaluated in the diabetes context, all but two studies showed significant improvements on diabetes outcomes (4 showed significant reductions in HbA1C). 3/5 RCTs where the tool was evaluated as a co-intervention showed a significant improvement on outcomes • 6/7 prospective cohort studies which evaluated a tool as a primary intervention found the intervention feasible to implement in practice. One study evaluated a tool in the diabetes context, finding a significant reduction in HbA1C at follow-up. Both studies evaluating the tool as a co-intervention found the tool to be feasible. • One study retrospective cohort study examined the tool as a primary intervention, finding that patients who used a shared medical record had better glycemic control but increased health services utilization. 4/5 studies evaluated the tool as a co-intervention in the diabetes context. One found a reduction in HbA1C levels. • All quasi-experimental studies evaluated tools as primary interventions. Three showed improvements on study outcomes (improvement on aerobic capacity in COPD patients; better medication adherence in patients with depression). One showed no improvements on primary outcomes. • One survey study showed that just over 1/3 of patients actually contacted their physician via email (non-specific chronic conditions context). • One cost-effectiveness study showed that using a shared medical record was cost- effective (another cohort study evaluating costs, showed that the tool reduced costs due to provider appointments per month) • All seven qualitative studies showed that patients felt positively about using a communication tool. One qualitative study where the tool was a co-intervention found that patients were dissatisfied by the impact that the tool had on the patient-physician relationship (replacing appointments), and on provider responsiveness over the tool.

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APPENDIX 8: Coding Framework for Loop Usage for Pilot Trial

Coding Framework for Loop Usage Method of coding categories: The message exchange on each Loop was independently reviewed by two coders (TV and AB) for text that reflected any of the categories described below, at least once. Categories were assigned to messages and any responses or follow-up posts. Categories were not quantified but assigned only once per Loop because of the challenge in defining the beginning and conclusion of an exchange. If multiple categories were perceived in a single post, then each was included as identified in the Loop. Introductions posted by administrators were not counted.

Category definitions and sample quotations reflecting the label Abbreviations Pt- patient HCP- healthcare provider

1. Introductions- messages that introduce team participants on the tool 1) “Got it! Welcome to Loop [pt]! I'm glad to see that you and [HCP] have a handle of the Attention To function; in this way, you can direct messages to individuals which will alert them through their email. There is also a Tag Issue feature (in the compose message box), where you can label conversations around a particular issue, for example, a symptom. Messages can be filtered (on the left side of the screen) as well.”

2. Symptoms- messages that relate new or updates to symptoms 1) “I've had an increase in hoarseness and swallowing difficulties as well as episodes of tetany to my left hand mostly affect [HCP]. I feel the [test 1] and [test 2] are needed especially due to the recent changes in symptoms, location of my cancer and its metastatic routes.”

3. Appointment coordination- messages related to scheduling and booking appointments. 1) “Dear Dr [HCP1] and Dr [HCP2] Sorry if you receive this twice but I think my previous message got deleted. My next appointment with you is [date].”

2) “Dr. [HCP1]; Sorry to inform you that I messed up the schedule for my CT Scan and your appointment. I missed taking the premedication this morning and have a rescheduled scan on the [date 1]. The earliest appointment the clinic could reschedule with you is [date 2].”

4. Administrative/tool set-up- related to assembling Loop team members, technical issues and usage instructions 1) “Hi [pt], yes as of right now those are the team members who have activated their loops. Dr. [HCP1] and Dr. [HCP2] invitations are pending. Best, [study administrator]”

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5. Medication information/changes- related to providing information (but not prescription or administration of medication) of medication, dosage etc. 1) “Hi [pt], I hope that you are doing well since our last meeting. Remember the medication ritalin (other name - methylphenidate) is there if you need it for fatigue. Feel free to post any issues or concerns. talk soon! [HCP]”

6. Prescription renewal- messages related to renewal of medication 1) “I would really appreciate it if you can send a prescription ( prefrebly for two months)for [drug] to the pharmacy. I have only x pills left. Fax: 12345789 Thank you [pt]”

7. Prescription of new medication- messages related to new prescription of medications 1) From patient: "Hello, I was wondering if you can kindly send a prescription for Imodium to the pharmacy. I want to give it a new shot and see if I can get reimbersment from my insurance co. Thank you"

From HCP: “Hi [pt] That's fine, I've sent a script for 280 tablets (and one repeat) for you to try. The generic name is Loperamide, it's exactly the same as Immodium, which is one of the brand names. With thanks [HCP]"

8. Medical care updates- messages related to updating either the physician or the patient on status 1) From patient: “Sugars for the first 15 days were from 7 - 13 with many double digit counts. Things have settled down some so that since the first of July the range has been 4.8 to 9.1 with none of the low counts I was experiencing before the embolization.”

9. Medical care management- related to direction, management and provision of care, including ordering tests and administration of medication. 1) “Hi [HCP1] and [HCP2], Dr. [HCP3] said you need a nurse to administer an injection next month. Do you know which MD I need to call to get the order? Thanks,”

2) “Good Morning I left on a message with Dr [HCP’s] office regarding this issue but I figured this would also be a good idea. I returned from [location 1] on Friday and went through 6 weeks of mail. I found my [hospital name] appointment letter and I'm concerned that the CTs that are ordered are chest abdo and pelvis. Can you please add head and neck? …I feel the head and neck are needed especially due to the recent changes in symptoms, location of my cancer and its metastic routes. Also, the bloodwork does not have ECG added to it and this presents me with difficulty with the ECG tech as I have to talk her/him into doing the ECG without an online order. Thank you for your time.”

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APPENDIX 9: Responses to Computer Usage Questionnaires by User Group for Trial

Intervention arm Control arm Patients (n=21) (n=21) Computer usage – no. (%) At work 6 (28.6) 6 (28.6) At home 17 (81.0) 19 (90.5) Internet access 17 (81.0) 19 (90.5) Any use of other devices – no. (%) Tablet 7 (33.3) 12 (57.1) Smartphone 14 (66.7) 14 (66.7) None 2 (9.5) 1 (4.8) Daily use of computers or related devices – no. (%) Not at all 4 (19.1) 1 (4.8) ≤2 hr 6 (28.6) 13 (61.9) 3-7 hrs 8 (38.1) 6 (28.6) >7 hrs 3 (14.3) 1 (4.8) Daily internet use – no. (%) Not at all 4 (19.1) 1 (4.8) ≤2 hr 10 (47.6) 13 (61.9) 3-7 hrs 7 (33.3) 6 (28.6) >7 hrs 0 (0) 1 (4.8) Comfortable using: Computers (median, IQR 1 to 4 (most)) 4.0 (2.0) 3.0 (2.0) Smartphone or tablet (median, IQR 1 to 4 2.0 (3.0) 3.0 (2.0) (most)) Internet (median, IQR 1 to 4 (most)) 4.0 (2.0) 3.0 (2.0) Email (median, IQR 1 to 4 (most)) 3.0 (3.0) 4.0 (1.0) Instant messaging (median, IQR 1 to 4 (most)) 2.0 (3.0) 3.0 (3.0) Social media (median, IQR 1 to 4 (most)) 1.0 (2.0) 3.0 (4.0) Initiating Physicians (n=10) (n=9) Computer usage – no. (%) At work 10 (100) 9 (100) At home 10 (100) 9 (100) Internet access 10 (100) 9 (100) Any use of other devices – no. (%) Tablet 1 (10) 1 (11.1) Smartphone 9 (90) 7 (77.8) Daily use of computers or related devices – no. (%) Not at all 0 (0) 0 (0) ≤2 hr 0 (0) 0 (0) 3-7 hrs 6 (60) 8 (88.9) >7 hrs 4 (40) 1 (11.1) Daily internet use – no. (%)

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Not at all 0 (0) 0 (0) ≤2 hr 1 (10) 4 (44.4) 3-7 hrs 8 (80) 5 (55.6) >7 hrs 1 (10) 0 (0) Comfort with: Computers (median, IQR 1 to 4 (most)) 3.5 (1.0) 4.0 (0.0) Smartphone or tablet (median, IQR 1 to 4 3.0 (1.0) 4.0 (1.0) (most)) Internet (median, IQR 1 to 4 (most)) 4.0 (1.0) 4.0 (0.0) Email (median, IQR 1 to 4 (most)) 4.0 (0.0) 4.0 (0.0) Instant messaging (median, IQR 1 to 4 (most)) 3.0 (2.0) 4.0 (1.0) Social media (median, IQR 1 to 4 (most)) 0.5 (3.0) 2.0 (1.0) Caregivers of consented patient participants (n=18) (n=8) Computer usage – no. (%) At work 10 (55.6) 4 (50.0) At home 15 (83.3) 7 (87.5) Internet access 15 (83.3) 7 (87.5) Any use of other devices – no. (%) Tablet 11 (61.1) 3 (37.5) Smartphone 10 (55.6) 4 (50.0) Daily use of computers or related devices – no. (%) Not at all 0 (0) 0 (0) ≤2 hr 7 (38.9) 5 (62.5) 3-7 hrs 7 (38.9) 2 (25.0) >7 hrs 1 (5.6) 0 (0) Daily internet use – no. (%) Not at all 0 (0) 0 (0) ≤2 hr 9 (50.0) 6 (75.0) 3-7 hrs 5 (27.8) 1 (12.5) >7 hrs 1 (5.6) 0 (0) Comfort with: Computers (median, IQR 1 to 4 (most)) 3.0 (1.0) 3.0 (2.0) Smartphone or tablet (median, IQR 1 to 4 3.0 (2.0) 2.0 (2.0) (most)) Internet (median, IQR 1 to 4 (most)) 3.0 (1.0) 4.0 (2.0) Email (median, IQR 1 to 4 (most)) 4.0 (1.0) 4.0 (1.0) Instant messaging (median, IQR 1 to 4 (most)) 3.0 (1.0) 2.0 (2.0) Social media (median, IQR 1 to 4 (most)) 2.0 (3.0) 1.0 (3.0) IQR= interquartile range

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APPENDIX 10: Coding Framework for Qualitative Study

Coding Framework

Parent Node Child Node Definition Patient perceptions MDs Patient feelings about the quality of of the quality of care care towards the physicians involved in their healthcare Other healthcare providers Patient feelings about the quality of care towards other healthcare providers including nurses, technicians, social workers, care coordinators etc. Patient perceptions of Patient perceptions on their current healthcare needs needs from healthcare providers or ailments that should be addressed by the healthcare system Circle of care Definition or description of care team, “circle of care” Existing modes of Descriptions of methods of communication communicating which are used currently to discuss healthcare issues and needs Participant Expectations of the patient All participant perceptions of what is expectations of expected (ie role of…), if anything, others in the care of from the patient in their own care a patient Expectations of the caregiver All participant perceptions of what is expected (ie role of…), if anything, from the caregiver in the care of the patient Expectations of the healthcare All participant perceptions of what is provider expected (ie role of…), if anything, from the healthcare provider in the care of the patient Participant Who is using the tool Identification of which participants experiences of using on a patient’s healthcare team, the tool including the patient use Loop Who is not using the tool Identification of which participants on a patient’s healthcare team, including the patient do not use Loop Accounts of using the tool Participant descriptions of how the tool has been used Reasons or circumstances Rationale for why patients, resulting in participants not caregivers, healthcare providers do using the tool not use or have chosen not to use Loop 231

Beliefs about Participant beliefs on electronic Beliefs about electronic electronic communication communication, which may impact communication choices to use digital health tools Beliefs about eHealth Participant views on integration of integration digital health tools into one system Participant beliefs or Participant beliefs or expectations expectations about use of the about who should drive the use of the tool from other healthcare team tool users Hypothesized ways Participant accounts of how they in which the tool think Loop should be used, other than could be used for communication/dialogue Feedback on tool Feedback on how the tool How participants expect Loop to be implementation should be introduced to users introduced as a new tool for healthcare to different members of the team Feedback on the need for Participant perceptions that Loop training in order to understand requires some form of training or how to use the tool education for its functionalities to be understood Descriptions of accessing the How users choose to access Loop (ie tool system/device) Usability Participant views on Loop’s ease of use, functionality User Interface Participant views on the Loop user interface layout, organization of subject matter on screen

Terms: • Loop refers to the web-based clinical collaboration tool for team-based care • Healthcare team- refers to the unit of healthcare providers and caregiver(s) who are involved in the care of a patient, but does not imply that they are regularly connected or function together as a “team”

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APPENDIX 11: Sample Consent Form for Pilot Trial CONSENT TO PARTICIPATE IN A RESEARCH STUDY

Patients

Title My Team of Care (MyTOC) Project

Principal Investigator Amna Husain, MD, MPH Temmy Latner Centre for Palliative Care, Mount Sinai Hospital, 416-586-4800 x6721

Joseph Cafazzo, P.Eng Centre for Global eHealth Innovation, University Health Network, 416-340-3634

Co-Investigators Jennifer Stinson, RN, PhD; Adam Rapoport, MD; Eyal Cohen, MD; Trevor Jamieson, MD; Eva Grunfeld, MD; Andrea Bezjak, MD; Russell Goldman, MD; Ken Sutcliffe; Denise Guerriere, MD.

Sponsor MSH-UHN AMO AFP Innovation Fund

Introduction

You are being asked to take part in a research study. Please read this explanation about the study and its risks and benefits before you decide if you would like to take part. You should take as much time as you need to make your decision. You should ask the study doctor or study staff to explain anything that you do not understand and make sure that all of your questions have been answered before signing this consent form. Before you make your decision, feel free to talk about this study with anyone you wish. Participation in this study is voluntary.

Background and Purpose

Cancer care requires many types of health care providers, who work in different locations including: homecare, family doctors’ offices, nursing homes and hospitals. Therefore, good communication between health care providers is important in achieving the best possible health outcomes. Currently, there is no easy way for health care providers to communicate with each other or with patients and their families.

Our research team has developed a tool for secure clinical communication, called “Loop”, that will bring together patients, their families, and health care providers. The web-based communication tool was built with input from patients, caregivers and health care providers who tested the system at various points during the development. We are conducting this study in order to test the usefulness of Loop in actual use in health care.

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You have been asked to take part in this research study because we would like to test the role that Loop will have in the quality of the health care you receive. While we know that communication between health care providers, and patients and families remains a major hurdle in the delivery of health care, it is not clear which mechanisms will help to improve communication.

We are aiming to recruit 100 patients from Mount Sinai Hospital and Princess Margaret Cancer Centre to participate in the study. About 50 patients will come from each hospital.

Study Design

This study is a pilot randomized control trial, which means that 50% of participating teams (a team is composed of 1 patient, 1 caregiver and at least 2 health care providers) will be randomly assigned to one of two groups.

Your primary oncologist or palliative care physician has agreed to participate in this study. Because they were randomized to the Loop group, you will be given access to Loop for a maximum of 3 months, after at least 1 of your other health care providers also joins Loop.

During your participation in the study, you will complete questionnaires every month about the quality of care you are receiving, communication, feelings toward the tool, and visits to health care providers. You will also take part in interviews every month with a research coordinator over the telephone. Your a) family caregiver, b) primary oncologist or palliative care physician, and c) at least one additional health care provider of your choice (family physician, nurse, chiropractor, respiratory therapist, etc.) may also participate in the study, use the tool, and complete questionnaires and interviews.

Study Visits and Procedures

Screening: When you are approached in clinic or contacted by telephone, the research coordinator will screen you for participation in the study. Completing the screening form with them is likely the first time the research coordinator has met you. When the screening form has been filled out, you will be presented with this consent form, and the research coordinator will administer or schedule the baseline study visit.

Baseline: The research coordinator will ask about your condition before you begin participating in the study. This information will be obtained by completing the baseline questionnaire. The results of the questions for the baseline questionnaire will help the researchers decide whether you can continue in this study.

We will ask you to complete the following questionnaires: 1. Demographics 2. Internet Preferences Survey 3. Patient Outcomes Scale (POS)

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4. Continuity & Coordination subscale of Picker System of Surveys (adapted) 5. Ambulatory and Home Care Record (AHCR) 6. Edmonton Symptom Assessment Scale (ESAS) 7. Eastern Cooperative Oncology Group (ECOG) Performance Status Scale

We will also conduct a brief semi-structured interview (10-20 minutes) about your current health care related communication needs and difficulties.

Clinical Communication System: The research coordinator will give you access to Loop. Once at least 2 of your healthcare providers have joined the system, the study will begin. You will have access Loop for 3 months and will be able to post messages to your healthcare providers. Please note that the clinical communication system is not meant to be used in emergency situations. Traditional methods of accessing care in emergency situations should be used (i.e. emergency department visit, phone call to doctor, etc.).

Study Visits: We will conduct follow up study visits with you on a monthly basis for up to 3 months.

Boxes marked with an X show what will happen at each visit: Internet POS Continuity & AHCR ESAS ECOG Semi- Total Visit Demographics Preferences Coordination Structured Time Survey Subscales Interview (min) Baseline X X X X X X X X 60

Month 1 X X X X X X 40

Month 2 X X X X X X 40

Month 3 X X X X X X 40 *Depending on how you are feeling, we can collect study data by phone, or in person at your home or at our office.

Reminders

It is important to remember the following things during this study:

• Ask your study team about anything that worries you. • Tell study staff anything about your health that has changed. • Tell your study team if you change your mind about being in this study.

Risks Related to Being in the Study

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There are no medical risks if you take part in this study, but being in this study may make you feel uncomfortable. Risks may include possible discomfort with sharing opinions with the investigator. If you feel anxious and/or uncomfortable, please bring your concerns to the investigator’s attention immediately. You may refuse to answer questions or stop the interview at any time if there is any discomfort.

Benefits to Being in the Study

You may not receive any direct benefit from being in this study. Information learned from this study may help the researchers in understanding the impact of the clinical communication system on improving workflow, enhancing primary care physicians engagement throughout the cancer trajectory, improve efficacy of health care utilization costs and improve cancer patients’ satisfaction with care and quality of life.

Voluntary Participation

Your participation in this study is voluntary. You may decide not to be in this study, or to be in the study now and then change your mind later. You may leave the study at any time without affecting your care. You may refuse to answer any question you do not want to answer, or not answer an interview question by saying “pass”.

We will give you new information that is learned during the study that might affect your decision to stay in the study.

Alternatives to Being in the Study

You do not have to participate in this study. If you do not participate in this study you will continue to receive usual care.

Confidentiality

Personal Health Information If you agree to join this study, the study doctor and his/her study team will look at your personal health information and collect only the information they need for the study. Personal health information is any information that could be used to identify you and includes your: • name, • address, • date of birth, • new or existing medical records, that includes types, dates and results of medical tests or procedures.

The information that is collected for the study will be kept in a locked and secure area by the study doctor for 10 years. Only the study team or the people or groups listed below will be allowed to look at your records. Your participation in this study also may be recorded in your medical record at this hospital.

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The following people may come to the hospital to look at the study records and at your personal health information to check that the information collected for the study is correct and to make sure the study followed proper laws and guidelines: • Representatives of the Mount Sinai Hospital Research Ethics Board • University Health Network including Research Ethics Board representatives

Study Information that Does Not Identify You Some study information will be sent outside of the hospital to co-investigators for analysis when the study is complete. Any information about you that is sent out of the hospital will have a code and will not show your name or address, or any information that directly identifies you.

All information collected during this study, including your personal health information, will be kept confidential and will not be shared with anyone outside the study unless required by law. You will not be named in any reports, publications, or presentations that may come from this study.

If you decide to leave the study, the information about you that was collected before you left the study will still be used. No new information will be collected without your permission.

In Case You Are Harmed in the Study

If you become ill, injured or harmed as a result of taking part in this study, you will receive care. The reasonable costs of such care will be covered for any injury, illness or harm that is directly a result of being in this study. In no way does signing this consent form waive your legal rights nor does it relieve the investigators, sponsors or involved institutions from their legal and professional responsibilities. You do not give up any of your legal rights by signing this consent form.

Expenses Associated with Participating in the Study

You will not be reimbursed for transportation, meals, time, inconvenience, etc.

Conflict of Interest

The MSH-UHN AMO, the sponsor of this study, will pay the hospital and researcher for the costs of doing this study. All of these people have an interest in completing this study. Their interests should not influence your decision to participate in this study. You should not feel pressured to join this study.

Questions About the Study

If you have any questions, concerns or would like to speak to the study team for any reason, please call: Principal Investigator (Mount Sinai Hospital): Amna Husain at 416-586-4800 x6721

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Principal Investigator (University Health Network): Joseph Cafazzo at 416-340-3634 Research Coordinator, Bhadra Lokuge at 416-586-4800 x1534 Research Coordinator, Allison Kurahashi at 416-586-4800 x6722 Graduate Student, Teja Voruganti at 416-946-5352

If you have any questions about your rights as a research participant or have concerns about this study, please call:

- Mount Sinai Hospital Research Ethics Board Chair Dr. R. Heselgrave or the Research Ethics Board Office at 416-586-4875 - University Health Network Research Ethics Chair and/or Research Ethics Office at 416-581-7849

The REB is a group of people who oversee the ethical conduct of research studies. These people are not part of the study team. Everything that you discuss will be kept confidential.

Consent

This study has been explained to me and any questions I had have been answered. I know that I may leave the study at any time. I agree to take part in this study.

Print Study Participant’s Name Signature Date

(You will be given a signed copy of this consent form)

My signature means that I have explained the study to the participant named above. I have answered all questions..

Print Name of Person Obtaining Consent Signature Date

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APPENDIX 12: University of Toronto Research Ethics Board Approval

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APPENDIX 13: Loop Terms of Use

Please read the following Loop User Agreement:

1. DO NOT use Loop for communication that requires an URGENT response. 2. Only people who are invited to join from your actual team of care will be part of your Patient Loop. 3. Although the system is secure and encrypted, it is impossible to guarantee privacy. Loop takes measures to protect, monitor, correct and promptly inform you of any breach of privacy. 4. You may deactivate your Patient Loop at any time. The Patient Loop will remain visible for 7 days and then stored as a medical record for 10 years.

Loop User Agreement

About Loop:

Loop is a secure online system that assembles the patient’s actual team of care in order to communicate, coordinate and collaborate in patient care. Loop is accessed by patients and health care professionals on an Internet database. Loop offers the Subscriber the opportunity to communicate electronically and share personal and medical information with a Patient’s health care team who have been invited to join the patient’s team on Loop database ("Patient Loop").

Definitions:

a. Subscriber can be a patient, patient’s designated caregiver, or health care professional. b. Health Care Professional, means patient’s health care professional, including nurses, doctors and case managers. c. Caregiver, means, a patient’s designated informal (non-professional) care giver, which may be a family member or friend. d. Device means any computer device, such as a lap top, desk top, mobile phone, smart phone or tablet.

Mount Sinai Hospital (the "Provider") agrees to provide access of Loop to the user ("Subscriber"), which may be a Patient, Caregiver or Health Care Professional, with access to a database that provides Loop ("Database"), and the Subscriber desires to subscribe to Loop according to the following terms:

Rights Granted:

1. The Provider grants Subscriber (Patient, Caregiver or Health Care Professional) the right to access the Database for the purpose of a. If the subscriber is Patient, communicating with his/her Health Care Professionals or his/her Caregiver to discuss matters related to the Patient’s medical health.

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b. If subscriber is Caregiver, communicating with the Health Care Professionals of the Patient he/she cares for, or the Patient. c. If subscriber is Health Care Professional, communicating with his/her Patient, the Patient’s other Health Care Professionals or with Patient’s Caregiver. 2. Ownership of all proprietary and intellectual property rights, including copyrights in Loop software, Database and related manuals shall remain with the Provider.

3. The Subscriber acknowledges that Loop is not an emergency communication tool, and it will not be used when an urgent response is needed. 4. Only Health Care Professionals that are authorized to access a Patient’s Loop according to the terms of this agreement will be permitted to participate in such Patient Loop. 5. No patients who are subscribed to Loop will have access to any other Patient’s Patient Loop. 6. If subscriber is a Patient or a Caregiver, Provider does not guarantee privacy of the Subscriber's personal or medical health information ("Information"). Loop uses secure architecture, secure hosting, encrypted messaging and monitors who is accessing what parts of the system. Provider will make all reasonable efforts to inform the Subscriber about any unauthorized disclosure of Subscriber's Information. 7. If subscriber is a Health Care Professional, Provider does not guarantee privacy of the Subscriber's personal account information ("Information") or messages. Loop uses secure architecture, secure hosting, encrypted messaging and monitors Database users. Provider will make all reasonable efforts to inform the Subscriber about any unauthorized disclosure of Subscriber's Information. 8. The Information on the Database may not be deleted and shall be encrypted and stored on a backup server that is kept at a secure location that meets high standards of security. However, Provider does not guarantee security of any information stored on its backup storage database. 9. If Subscriber is the Patient, he/she may personally deactivate his/her Loop account at any time. In the event that a Patient becomes deceased or unable to personally deactivate the Patient Loop, a Health Care Professional who is a member of the Patient’s Loop may request deactivation of the Patient Loop by the Loop administrator. Deactivating a Patient Loop means that the Patient, the Patient’s Caregiver and Patient's Health Care Professionals will no longer be able to post messages or change any information in the Patient Loop. The Patient Subscriber is the only team member who may directly deactivate his/her Patient Loop. Upon deactivation, each member of the Patient’s Loop will be notified about the deactivation, and the Patient Loop will only be accessible as a read-only file for a period of seven days before it is permanently inaccessible to all Subscribers. However, prior to permanently removing the Patient Loop, the Patient Subscriber information may be added to his/her medical record and when legally necessary, such medical record may be used as evidence in court, upon a court order. Following the seven day deactivation period, the Information will not be accessible by the Patient or their Health Care Professionals and will be securely stored as an inactive account for a period of ten years, then expunged from storage thereafter.

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10. If Subscriber is a Patient or a Caregiver, Subscriber's messages shall be accessible by all participants of that Patient Loop. 11. If Subscriber is a Health Care Professional, Subscriber’s message shall be visible either to either Health Care Professionals only (by selecting Team Only option in posting message) or to Health Care Professionals, Patient and Caregiver (by selecting Patient and Team option in posting message. 12. Patient Subscriber's Information shall be treated according to the Personal Information Protection and Electronic Documents, S.C. 2000 ("PIPEDA") and Personal Health Information Protection Act, 2004. S.O. 2004 ("PHIPA") acts (the "Acts"). 13. It is anticipated that each Health Care Professional Subscriber that is authorized to access the Patient Loop and has agreed to join the Patient Loop shall reasonably respond to Subscriber's medical health correspondence. However, participation in and use of the system are entirely voluntary. Therefore, in the event that a Health Care Professional joins a Patient Loop, he/she is not required to respond to patient inquiries using the Patient Loop Database. 14. All Subscribers (Patient, Caregiver or Health Care Professionals) acknowledges that Loop should not be used in place of clinical examinations. From time to time the Patient’s Health Care Professional will advise the Patient Subscriber to schedule an appointment with a health clinic for medical assistance. 15. Patient Subscriber is solely responsible for following up with his/her Health Care Professionals in regards to any Loop correspondence. 16. Patient Subscriber is solely responsible for informing his/her Health Care Professionals about information that the Subscriber does not want disclosed on Loop. 17. Provider is not responsible for information that is deleted, misplaced or accessed due to but not limited to, computer malfunctions or computer viruses. 18. Patient Subscriber's Health Care Professionals may invite the Patient to participate in Loop research studies. Any research study conducted with data from the Patient Loop requires prior written approval from the Research Ethics Board of the institution participating in such study and a data sharing agreement must be entered between the institution conducting the research, The Provider and the Health Pare Professionals that participate in such study. 19. If Subscriber is Health Care Professional, she/he may use data from Patient Loops that she/he has permission to view to assess and improve the quality and performance of the Health Care Professional’s program of care.

Access:

20. From time to time Loop may be interrupted in order to maintain, modify or enhance the Loop Database. Although The Provider shall use reasonable efforts to limit disruptions to Loop, the Provider assumes no responsibility for interruptions of or delays to Loop. 21. WITHOUT LIMITING ANY OF THE PROVISIONS OF THIS AGREEMENT, SUBSCRIBER (PATIENT, CAREGIVER or HEALTH CARE PROFESSIONAL) ACKNOWLEDGES THAT SUBSCRIBER AND NOT THE PROVIDER IS SOLELY RESPONSIBLE FOR ENSURING THE ACCURACY AND COMPLETENESS OF ANY ELECTRONIC FORMS PREPARED BY SUBSCRIBER AND SUBMITTED THROUGH LOOP. THE PROVIDER SHALL NOT BE LIABLE TO SUBSCRIBER

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OR ANY THIRD PARTY FOR ANY MALFUNCTION, INTERRUPTION, FAILURE, DELAY, ERROR OR OMISSION IN THE COMMUNICATION OR TRANSMISSION OF INFORMATION FROM SUBSCRIBER TO THE PROVIDER OR IN THE FILING OF ANY FORMS RECEIVED BY THE PROVIDER FROM SUBSCRIBER UNLESS CAUSED BY THE GROSS NEGLIGENCE OR WILFUL MISCONDUCT OF PROVIDER.

General Restrictions on Use:

22. Loop is provided exclusively for the use of the Subscriber (either a Patient, or a designated Caregiver or a Health Care Professional). A Patient Subscriber may authorize a Caregiver to be invited to join the Patient’s Loop or may authorize the Caregiver to be their delegate in the Patient Loop. In the event that the Patient Subscriber is below 18 years of age, Patient may authorize one parent or guardian access to the Subscriber's Patient Loop. 23. The Subscriber (Patient, Caregiver or Health Care Professional) agrees to co-operate with the Provider and protect the copyright and/or any other proprietary rights associated with Loop, and shall comply with reasonable requests made by the Provider to protect or enforce the Provider's rights to Loop and its Database during and after the term of this agreement. 24. Subscriber (Patient, Caregiver or Health Care Professional) shall not sell or attempt to sell, transfer, assign, publish, distribute, disseminate, allow any unauthorized third party access to, or convey any of Loop or its Database. 25. Subscriber (Patient, Caregiver or Health Care Professional) shall not attempt to copy, modify, reverse engineer, disassemble, decompile or decrypt Loop or its Database and shall not attempt to reconstruct copy or prepare derivative works similar to Loop or any portion thereof nor permit others to perform such activities. 26. Provider may notify Subscriber (Patient, Caregiver or Health Care Professional) in writing or by electronic means, about any additional conditions, requirements or restrictions ("New Restrictions") for using Loop. The continued use by Subscriber of Loop following receipt of such notice shall be deemed the Subscriber's confirmed acceptance of the New Restrictions. 27. Subscriber (Patient, Caregiver or Health Care Professional) acknowledges that Loop may be subject to a separate license agreement, and the Provider's continued ability to provide Subscriber with access to Loop may be subject to such license agreement while it is in force, and Subscriber's access to Loop may cease upon termination of such license agreement. 28. Subscriber (Patient, Caregiver or Health Care Professional) shall ensure compliance with the terms of this agreement or any applicable license agreement.

Charges:

29. Access to Loop Database will be provided to the Subscriber (Patient, Caregiver or Health Care Professional) free of charge. However, in the event that the Provider decides to implement a service fee to use Loop, the Subscriber shall be notified about such fee ("Fee Notice Letter") by email at least three months prior to receiving such charge. Upon

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notice, the Subscriber may deactivate their account on Loop. In the event that the account is not deactivated by the Subscriber, a second Fee Notice Letter will be sent 2 weeks prior to receiving charge and the Provider shall continue to permit the Subscriber to continue to use Loop for the fee described in the Fee Notice Letter.

Subscriber Responsibilities:

30. Subscriber (Patient, Caregiver or Health Care Professional) shall be responsible for arranging Internet access. 31. Subscriber (Patient, Caregiver or Health Care Professional) shall be solely responsible for protecting his/her password from unauthorized disclosure or use. Subscriber shall not share his/her login information or allow anyone else to use Loop with his/her login information.

Termination:

32. The Provider may terminate this Agreement by written notice to Subscriber (Patient, Caregiver or Health Care Professional), effective immediately: a. if Subscriber commits any default or breach of this agreement; b. if Provider is no longer able, or authorized to provide Loop; c. for no cause, upon 30 days advanced notice to Subscriber.

Disclaimer of Warranties; Limitation of Liability:

33. Provider warrants that it has the right to grant this license to the Subscriber (Patient, Caregiver or Health Care Professional). 34. Except as expressly provided in this section, there are no understandings, representations, warranties, covenants, conditions, promises, guarantees or agreements, express or implied, statutory or otherwise, or arising from a course of dealing or usage of trade, relating to Loop, including but not limited to any implied warranty of merchantability or fitness or adequacy for any particular purpose or use, or of quality, productiveness, capacity or accuracy. In no event shall the Provider be liable for any indirect, incidental, special, consequential or punitive damages occurring out of or in connection with the delivery, use or performance, or failure thereof, of Loop or arising from the negligence of the Provider or from a fundamental breach, even if the Provider has been advised of the possibility of such damages. Without limiting the generality of the foregoing, the Provider does not warrant that Loop will perform uninterrupted or error free, that any deficiency can or will be corrected, or that the functions or performance of Loop will meet the Subscriber's (Patient, Caregiver or Health Care Professional) requirements.

General:

35. Changes. The Provider may from time to time, and in its sole discretion, change the content or format of Loop in accordance with general changes made to its standard service offering. The terms and conditions applicable to use Loop may be amended at any

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time upon reasonable notice to Subscriber (Patient, Caregiver or Health Care Professional). 36. Assignment. This agreement and any rights arising out of this agreement may not be assigned in whole or in part by Subscriber (Patient, Caregiver or Health Care Professional). 37. Entire agreement. This Agreement constitutes the entire agreement between the parties and supersedes all prior agreements, understandings, representations, negotiations and discussions, whether oral or written, of the parties, and there are no warranties, representations or other agreements between the parties in connection with the subject- matter hereof except as specifically set forth herein. No waiver, alteration or amendment of this agreement or any schedule, if any, shall be effective unless authorized by an authorized representative of the Provider. The terms and conditions in this agreement shall prevail notwithstanding any variance with the terms and conditions of any order submitted by the Subscriber (Patient, Caregiver or Health Care Professional). 38. Force majeure. The Provider shall not be liable for any default or delay resulting from circumstances beyond its reasonable control. 39. Notifications. Subscriber (Patient, Caregiver or Health Care Professional) requests and authorizes the Provider to inform Subscriber from time to time of other services available from the Provider or its affiliates. 40. Injunctive relief. The Subscriber (Patient, Caregiver or Health Care Professional) acknowledges that the Database is compiled, revised, selected and arranged by the Provider through the application of methods and know how that have been developed and applied through the expenditure of substantial time, money and effort, and constitutes valuable copyright, including protected compilations and trade secrets of the Provider. Therefore, since unauthorized use or disclosure of Loop may diminish the value of the copyright, proprietary rights and/or trade secrets interests that are embodied in the Database to the Provider, in the event that Subscriber breaches any of Subscriber's obligations with respect to limited use of same, the Provider will be entitled to all remedies available at law or in equity to protect their interests therein, including but not limited to injunctive relief as well as money damages. 41. Electronic agreement. The Provider may utilize electronic means to provide (Patient, Caregiver or Health Care Professional) with notice of change to applicable terms and conditions or applicable charges. The Provider may also propose the formation of new agreements through electronic means. The assent to such contracts through electronic means by Subscriber or any user utilizing Subscriber's login information and associated password shall be equivalent to Subscriber's written signature, and Subscriber agrees to be bound to such agreement. 42. Jurisdiction. The terms of this Agreement shall be construed according to the laws of Ontario and shall be subject to the non-exclusive jurisdiction of the courts of Ontario, Canada. 43. Survival. Any terms which by their nature are intended to survive the termination of this agreement shall continue in full force and effect after termination. 44. Severability. The invalidity or unenforceability of any provision or covenant in this Agreement shall not affect the validity or enforceability of any other provision or covenant herein contained, and this agreement shall be construed as if such invalid or unenforceable provision or covenant were omitted.

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45. Action. No action, regardless of form, arising out of or pertaining to Loop, its software or the Database may be brought by Subscriber (Patient, Caregiver or Health Care Professional) more than one year after the cause of action, its discovery by Subscriber or such time as it should have reasonably been discovered by Subscriber. 46. Acceptance. By using Loop and its Database and accepting this agreement, you acknowledge that you are the Subscriber (Patient, Caregiver or Health Care Professional) and agree to accept and be bound by the terms herein.

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APPENDIX 14: My Team of Care Study Protocol

Trial Protocol

Title: A pilot randomized controlled trial of an online communication tool in patients with advanced cancer

Objectives: The overall objective of this study is to conduct a pilot randomized controlled trial (RCT) to assess the feasibility of implementing an online communication tool for team-based communication in the care of patients with advanced cancer.

Feasibility Objectives: The following preliminary measures of feasibility will be taken: a) number of participants approached, eligible, and consenting, and rates and reasons for nonparticipation b) patient recruitment and retention rates c) healthcare provider recruitment and retention rates d) caregiver recruitment and retention rates e) instrument and item response rates over time

Effectiveness Objectives: Preliminary measures of effectiveness will be taken of: a) the effect of the intervention on patient-reported continuity of care b) the effect of the intervention on patient-reported quality of care c) the effect of the intervention on patient- or caregiver-reported on ambulatory and home-based health services utilization d) the effect of the intervention on patient-reported symptom severity

Other Objectives: The following data will also be gathered: a) statistics on usage and operations, including number of times users access the platform b) patient, caregiver and healthcare provider experience and engagement with the intervention c) number of healthcare providers involved indirectly in multiple study arms

Rationale and Relevance: Loop is an online communication tool that assembles the actual team of care, centered on each patient, in order to arrive at care plans together. Loop is designed to bridge the gap between patients, caregivers, and healthcare providers from across disciplines and settings, facilitating communication without the hierarchies inherent in a clinical setting. As a secure online communication portal, Loop has the potential to make communication of information more timely and tailored to patient needs and preferences The Loop team is a broad partnership led by Husain et al., and includes the design expertise of the Healthcare Human Factors team at the University Hospital Network and the

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Development Team at Cancer Care Ontario.168 Loop was developed in a multiphase, iterative process with end-user input throughout development. The development involved a user needs assessment, prototyping and simulation, and usability testing. The next phase of evaluation is the purpose of this study, and involves pilot-testing Loop in the real-world, clinical setting. This aligns with Phase II of the Medical Research Council’s Framework for the Evaluation of Complex Interventions368. Smits et al., proposed a framework for the Design and develOpment, Testing early iterations, Testing for Effectiveness, Integration and implementation (DoTTI) for web-based tools369. The DoTTI framework specifies the intertwining of iteration and evaluation inherent in the development of web-based tools. It has four phases, of which this study may fit into the second phase (testing of early iterations). The evaluation of eHealth interventions is best accomplished with a mixed methods approach, as both quantitative and qualitative data provide valuable insight into the effect of the intervention on outcomes and subsequently reasons for the effect206. A pilot RCT design will enable the evaluation of the tool in a manner allowing for comparison of the intervention in one arm with a control group, and allow for feasibility measures to be collected both as a means of feedback of the tool in an early evaluation stage, as well as for planning future large-scale evaluations. A trial design also provides a basis to collect qualitative data concurrently with collection of quantitative data.

Study Design: This study is conceived as a pilot pragmatic, single-blind, stratified cluster-randomized controlled feasibility trial. The population of interest is patients with advanced cancer. Medical oncologists and palliative care physicians will be recruited to take part in the study, and stratified by specialty into two arms of attending physicians: medical oncologists and palliative care physicians. Randomization to the intervention or control arms will occur within these two strata. Patients will be recruited through participating physicians using purposive sampling, and receive the corresponding intervention in line with the allocation assignment of their physician. The intervention is meant to be used by a patient and their care team (defined here as individuals directly involved in all aspects of healthcare of the patient and referred to henceforth as a “patient Loop”). Therefore, in addition to the attending physician and patient, family caregivers and two or more other healthcare providers will be recruited to take part in the respective intervention. The broader patient Loop will include “additional healthcare providers” which may include other physicians, nurses, pharmacists and allied health professionals identified by the patient as being involved in their care.

Setting: Patients and caregivers will be recruited through their attending physicians at the Temmy Latner Center for Palliative Care (TLCPC) at Mount Sinai Hospital, or from the medical oncology program at Princess Margaret Cancer Center (PMH).

Patients/Participants: The primary unit of analysis for this study will be the patient. The attending physician will provide patients to participate in the study. Patients who meet the following inclusion and exclusion criteria will be eligible to participate in the study. In addition to providers and the patient, family caregivers will be invited to participate in a patient Loop.

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Inclusion Criteria 1. Patients with Stage IV cancer, or Patients with stage III cancer and poor prognosis as determined by a physician (≥3 months but <2 years) 2. Eastern Cooperative Oncology Group (ECOG) performance status score ≤2 3. Each patient must have at least two healthcare providers, including an attending oncologist or palliative care physician* 3. Patient and, if applicable, family caregiver must be ≥18 years of age 4. Literacy and language capacity and competency to provide informed consent 5. Patient or caregiver must access to a computer and the internet

Exclusion Criteria The following exclusion criteria will apply only to those patients who satisfy the inclusion criteria: 1. Patients without the capacity to participate in use of the online tool, and do not have a caregiver who can engage in use of the tool on their behalf 2. Participants without the capacity to participate in evaluation of outcome measures, including, but not limited to, online and paper-based multiple-choice questions, checklists, and visual analogue scales, and do not have a family caregiver who can complete outcome measures on their behalf 3. A potential candidate for or currently receiving hormone therapy for breast or prostate cancer 4. Patients with a prognosis of <3 months as determined by a physician 5. Patients with impaired mental status as previously assessed by a physician or judged by research staff using the Bedside Confusion Scale (score ≥2 suggests cognitive impairment, and study exclusion) 6. It has been determined that the patient is participating in another study precluding them from taking part in this study, as determined by an agreed-upon algorithm determined by study coordinators at each research site

*a minimum of two healthcare providers per patient may participate, including the initially- recruited attending physician

Research Procedure: Intervention Group Loop is a secure online communication tool that allows for patients and caregivers to communicate with the different members of their healthcare team. A patient profile and space is created which can be viewed by the patient, their caregiver, and healthcare providers after logging in. On the main page, individuals can post messages that can be read and responded to by those healthcare providers (“subscribers”) who have been granted access by the patient to view the profile. All entries remain on the patient space, allowing for previous posts to be viewed. The tool was designed with an intuitive user interface to allow for use without prior training. Patient Loops consist of a patient, their caregiver and at least two healthcare providers. In this study, those that are randomized to the intervention arm will receive access to register for Loop. The tool is not meant to be used in urgent situations.

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Participant enrolment will begin with recruitment of the attending physician at their site (PMH or TLCPC). The physician will be invited by the study administrators to register on Loop. Once they are registered, they are required to invite their patient to register on Loop. Once the patient is registered on Loop, they have the option of inviting their family caregiver and additional health care professionals who they feel should be a part of the patient Loop. Thus, registration can only occur based on invitation of an individual who is already registered.

Control Group The control group will receive usual care with the option of being given access to Loop from the time once their duration of participation in the study is complete until the entire study has concluded. All quantitative outcome measures will be captured from control group patients and caregivers. Control group patients and attending physicians will take part in monthly semi- structured interviews.

Recruitment Procedures: Initiating physicians are oncologists or palliative care physicians at either of the two study sites who treat patients meeting the study inclusion/exclusion criteria. Initiating physicians are recruited through announcements at grand rounds, research rounds, and institutional mass mailer emails. The study should be explained to the initiating physicians according to the information presented in the consent forms. Any questions should be answered as per the information presented in the study consent forms or in the protocol; anything not answered should be followed up with the study investigators. A physician may have up to four patients registered in the study at a given time but there is no limit on number of patients that an initiating physician can contribute. Patients will be recruited from initiating physician clinics. As patient rosters are not accessible unless the research assistant is affiliated with the hospital clinical research unit at the respective institution, reviewing patient eligibility from the physician rosters must be done by the physician. Permission to recruit the patient should be obtained from the initiating physician, and the patient should only be approached only after the physician has indicated to the patient that a researcher would like the opportunity to explain a potential study of interest to them. The patient should be introduced to the study according to the consent form. If the patient expresses interest, the research assistant should review the screening form with the patient to confirm eligibility. Once eligible, the research assistant should collect contact information. After the initial contact, the research assistant should follow-up with the patient within 1 day with a link to register on Loop, if in the intervention group, and arrange a time to schedule the baseline interview within 1- 2 weeks of meeting. The questionnaires may be emailed from the REDCap system or mailed to participants according to the schedule of assessments. Interviews and collection of the AHCR data should occur by phone or in-person. Follow-ups should be scheduled within 1-1.5 weeks of the monthly follow-up schedule ahead of time. Up to four contacts can be made to arrange follow-up until a patient is declared loss to follow-up. Once a patient has been determined to be lost to follow-up, contact the initiating physician to ascertain patient status. Complete a study termination form, documenting reason for termination.

Main Outcome Measures:

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Outcomes will be measured at the level of the patient. In addition to descriptive statistics, feasibility objectives will be captured with demographic questionnaires and user statistics capture by the audit functionality of Loop, measured at baseline and every month for 3 months of follow-up (four time points). Additionally the following feasibility metrics will be ascertained: a) Patient, healthcare provider and family caregiver recruitment and retention rates will be measured with: a. the proportion of eligible participants who are invited to participate b. the proportion of invited participants who consent to participate c. the proportion of invited participants in the intervention arm who consent, complete baseline questionnaire, and register on Loop, ≥70% indicates success d. the duration of participation in the study e. participant retention and drop out b) Instrument and item response rates will be measured for the relative completeness of each of the efficacy outcome questionnaires. It will also be noted whether assessments are completed by the patient or if a caregiver or healthcare provider, where applicable, completes them on a patient’s behalf.

Effectiveness objectives will be captured with selected measurement tools. Comparison of mean post-study scores will be computed. Outcome measures will be captured at monthly intervals over the three month study duration in all intervention group participants and both control group participants. a) Patient-reported quality of care will be measured with the Palliative Care Outcomes Scale (POS), a 12 item questionnaire. It can be completed by the patient, as well as caregiver on a patient’s behalf b) Patient-perceived continuity and coordination of care will be measured with a modified Picker Ambulatory Cancer Care Survey (Picker survey) Continuity and Coordination subscale questionnaire, containing 8 questions. Patients will complete this questionnaire. c) Ambulatory and home-based health services utilization will be measured with the Ambulatory and Home Care Record (AHCR), and can be completed by patient or caregiver on patient’s behalf. d) Symptom intensity will be measured with the Edmonton Symptom Assessment Scale, a 10 item questionnaire that asks patients to rate on a scale of 0-10, the intensities of ten symptoms and completed by the patient e) Performance status will be measured using the Eastern Cooperative Oncology Group score, and completed by interview with the trained research staff

Furthermore, the following metrics will be obtained: 1. Statistics on usage and operations for patients, healthcare providers and caregivers: a. Number of posts b. Number of times a participant logs in c. Which functions are being used d. Content analysis of messages for general purposes of tool use293

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2. An 11-item self-developed baseline questionnaire concerning experience and usage of a computer and the internet will be completed. 3. Subjective experiences with using the tool of patients, caregivers and healthcare providers will be gathered with semi-structured interviews conducted at monthly intervals with patients, caregivers and the initiating oncologist or palliative care physician in the intervention group and the control group. Additional team members may voluntarily take part in an exit interview at three months. Qualitative data will be generated and collected using thematic analysis178. Interview questions are guided by the main components of the technology acceptance model184 and by usability testing methods.318 4. The number of healthcare providers involved indirectly in multiple study arms will be noted. As this feasibility study is conducted at a single center with overlap in provider care between institutions, there is the possibility that healthcare providers may be involved in multiple patient Loops, including being involved in a Loop allocated to the control arm, and a Loop allocated to the intervention arm. The available funding for this pilot RCT limits the recruitment to two centers and with the resultant small number of physicians involved there is a possibility that they will be part of the team of more than one patient recruited. The result of this contamination would dilute the observed effect.

See Schedule of Assessments Appendix Figure 1

Sample Size: A formal sample size calculation has not been computed as this is a feasibility study. A target sample size of 25 patients in the intervention group and 25 patients in the control group is believed to be appropriate for a single-center pilot study in a palliative patient population.

Analysis: Collected outcomes data will be analyzed with intention-to-treat analysis according to intervention group. Difference in mean change scores between baseline and 3 month follow-up will be reported between intervention and control arms. Data will be analyzed using SAS 9.3 (Cary, North Carolina, USA). Audit data from the Loop tool will be obtained from host Carbon60 on a monthly basis in the form of audit reports and data dumps. Checks of enrolment and outcome completion rate will be done by the primary research investigators on an ongoing basis throughout the trial. Qualitative data will be gathered with semi-structured interviews conducted with a subset of patients, caregivers and healthcare providers. It is expected that the estimated sample size will sufficient for saturation of themes. Analysis of qualitative data will be done using NVivo 10 (QSR International).

Feasibility: Approximately 110 new patients are seen by 23 palliative care physicians per month at the TLCPC. Approximately, 18000 new patients are seen by approximately 100 oncologists per year at PMH. We anticipate that recruitment of physicians will be challenging and expect a degree of participant attrition. However, the current study aims to pilot the presented design for the purpose of optimization for the full scale trial.

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The estimated time to complete all questionnaires is 1 hour, as was observed in a previous study in this population by Husain et al.,98. Additionally, qualitative interviews are estimated to take 30 minutes based on pilot-testing.

Trial Management: Trial data will be managed using Research Electronic Data Capture (REDCap), a data management system hosted at the Applied Health Research Center (AHRC) of St. Michael’s Hospital, Toronto, ON. Baseline and follow-up measurements will be captured electronically using online surveys emailed to study participants via REDCap. Data will be stored on a data server at St. Michael’s Hospital and provided to the study investigators as described above. Data will be stored on REDCap servers at the AHRC and on computers at the TLCPC. Electronic study data at the AHRC will be stored behind two sets of locked doors accessible using an elevator requiring key card access. Paper study materials will be stored in locked cabinets within the TLCPC also behind two sets of locked doors. Original data will be destroyed after 10 years. Only study personnel will have access to this data. The Loop intervention, as a communication tool, will also contain personal health information. Patients randomized to the intervention arm will discuss health issues through the Loop tool which will only be visible by a caregiver who is also enrolled in the study, the healthcare providers who are linked to their Loop profile, and the study investigators. Loop data is stored on secure servers hosted by Carbon60.

Ethics Approval and Consent: Ethics approval will be obtained from the Research Ethics Boards of the relevant institutions and the University of Toronto. All participants in the study will be required to sign a written consent form prior to participation.

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Figure 1 Schedule of Assessment a) Assessments over course of study STUDY PERIOD Physician Patient Close- Allocation Enrolment out Prior to study Baseline Month Month Month 3 TIMEPOINT commencement (T1) 1 (T2) 2 (T3) (T4) (T0) Physician Enrollment X Screening Form X Informed Consent X Baseline Questionnaire X Palliative Care Outcomes X X X X Scale (POS)

Continuity and X X X X Coordination subscales of Picker Survey Edmonton Symptom X X X X Assessment Scale Eastern Cooperative X X X X Oncology Group Scale Ambulatory and Home X X X X Care Record (AHCR) Statistics on usage and X X X X operations, healthcare providers in multiple study arms Semi-structured X X X X interview with patient Semi-structured X X X X interview with caregiver Semi-structured X X X X interview with attending oncologist or palliative care physician

254 b) Outcome assessments by role

Baseline Month 1 Month 2 Month 3 Intervention group Attending physician: Use of Loop for 3 months Baseline questionnaire X Quantitative outcome measures Qualitative semi-structured interviews X X X X Patient and/or caregiver: Use of Loop for 3 months Baseline questionnaire X Quantitative outcome measures X X X X Qualitative semi-structured interviews X X X X Additional health care professional: Use of Loop for 3 months Baseline questionnaire X Quantitative outcome measures Qualitative semi-structured interviews Optional Baseline Month 1 Month 2 Month 3 Control group Attending physician: Baseline questionnaire X Quantitative outcome measures Qualitative semi-structured interviews X X X X Patient and/or caregiver: Baseline questionnaire X Quantitative outcome measures X X X X Qualitative semi-structured interviews X X X X

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APPENDIX 15: Patient Screening Form Patient Screening Form Instructions: This patient screening form is to be completed by the research coordinators. Please print clearly.

Date: Screener’s Initials:

Day Month Year

Patient Name: ______Age: ______

ID Number:  Patient is deceased

Clinic Location:  MSH Specify Clinic/Program: ______

 PMH Specify Clinic/Program: ______

Attending Physician (select one):  Palliative Care Specify Name: ______

 Oncologist Specify Name: ______

Primary Cancer Site (select one):

 Breast cancer  Colorectal cancer  Lung cancer  Ovarian cancer

 Other, please specify: ______

SECTION A: Inclusion Criteria Yes No   1. Stage III cancer with poor prognosis as determined by a physician, or Stage IV cancer

  2. Eastern Cooperative Oncology Group (ECOG) Score of ≤ 2

  3. Patient has at least two health care professionals, including an attending oncologist or palliative care physician

  4. Prognosis of ≥ 3 months as determined by attending oncologist or palliative care physician

  5. Patient is ≥ 18 years of age

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  6. Patient has the English language and literacy competency to provide informed consent

  7. Patient or, if applicable, caregiver has access to a computer and the internet ______

SECTION B: Exclusion Criteria Yes No   1. Unable to comply with study protocol including completion of questionnaires

  2. A potential candidate for or currently receiving hormone therapy for breast or prostate cancer

  3. Impaired mental status as previously assessed by a physician, or using the Bedside Confusion Scale

  4. It has been determined that the patient is participating in another study precluding them from taking part in this study, as determined by an agreed-upon algorithm determined by study coordinators at the research site

Were all of the Inclusion Criteria answered “Yes” and all of the Exclusion Criteria answered “No”? No  Patient not eligible Yes 

Date eligibility status confirmed:

Day Month Year

To be completed if patient meets eligibility criteria:

SECTION C: Participation and Consent

Patient was offered to participate in the study (select one):  Yes  No Patient accepted participation in the study (select one):  Yes  No

If no, reason for nonparticipation by a patient who is otherwise eligible to participate:  Patient is not interested in participating in study  Too ill, as determined by patient  Too ill, as determined by physician  Recruitment phase ended

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 Unable to reach patient  Other, please specify: ______

Patient signed consent forms (select one):  Yes  No

Date consent signed:

Day Month Year If no, please specify reason: ______

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APPENDIX 16: Baseline Demographics, Computer and Internet Usage Questionnaire Patient Baseline Questionnaire

1) Patients Demographic Information and Internet Preferences

ID Number:

Assessment Date: Day Month Year

1. Gender:  Female  Male

2. Age:

3. Primary Cancer Site (check one):

 Breast cancer  Colorectal cancer  Lung cancer  Prostate cancer

 Other, please specify: ______

4. Date of original diagnosis: Month Year

5. Recurrence of cancer:  Yes  No

If Yes, date of recurrence: Month Year

6. Have you had cancer treatment in the past six months?  Yes  No

If Yes, type of therapy: (please check all that apply to you)

 Chemotherapy

 Radiation

 Surgery

 Bone marrow/stem cell transplantation

 Other (please specify): ______

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7. How far away from the cancer center do you live? ______in km

8. Conditions requiring ongoing care: (please check all that apply to you)  a) Previous myocardial infarction  b) Congestive heart failure  c) Peripheral vascular disease  d) Cerebral vascular accident  e) Dementia  f) Pulmonary disease  g) Connective tissue disorder  h) Peptic ulcer  i) Liver disease  j) Diabetes complications  k) Paraplegia  l) Renal disease  m) Metastatic cancer  n) Severe liver disease  o) HIV

9. Do you live alone? (please check one)  Yes  No

10. Do you have a caregiver? (please check one)  Yes  No

11. Your educational background: (please check one)  Primary/middle school  High school  College/University  Professional/Graduate Degree  Other (please specify)______

12. Annual household income: (please check one)  $0 - $21,999  $22,000 - $49,999  $50,000 - $89,999  > $90,000  prefer not to disclose

13. Primary language: (please check one)  English  French  Other, please specify:______

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Internet Preferences Directions: For these questions, please check in the box next to the answer that best describes you. 1. Do you use a computer at work?  Yes  No  N/A

2. Do you use a computer at home?  Yes  No

If Yes, do you have internet access at home?  Yes  No

3. How many hours each day do you use a computer or other related technologies (e.g. smartphone [not limited to phone calls], tablet for portable computer use)?

 Not at all  <1 hour  1-2 hours  2-7 hours  >7 hours

4. How comfortable do you feel using a computer?

1 2 3 4 Not at all A little Very Comfortable comfortable comfortable comfortable

5. How comfortable are using a smartphone or tablet for portable computer use? (circle one)

0 1 2 3 4 Do not use a Not at all A little Very smartphone Comfortable comfortable comfortable comfortable or tablet

6. How many hours do you use the internet each day?

 Not at all  <1 hour  1-2 hours  2-7 hours  >7 hours

7. How comfortable do you feel using the internet? (circle one)

0 1 2 3 4 Do not use the Not at all A little Very Comfortable internet comfortable comfortable comfortable

8. How comfortable do you feel using email? (circle one)

0 1 2 3 4 Do not use Not at all A little Very Comfortable email comfortable comfortable comfortable

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9. How comfortable do you feel using instant messaging (texting, blackberry messenger, imessenger, Google-chat, etc.)? (circle one)

0 1 2 3 4 Do not use Not at all A little Very any texting Comfortable comfortable comfortable comfortable applications

10. How comfortable do you feel using social media (e.g. Facebook, Twitter etc.)? (circle one)

0 1 2 3 4 Do not use any social Not at all A little Very Comfortable media comfortable comfortable comfortable applications

11. Which of the following devices do you use (check all that apply)?  Computer  Smartphone  Tablet

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APPENDIX 17: Palliative Care Outcomes Scale Palliative Care Outcomes Scale295 Please answer the following questions by ticking the box next to the answer that is most true for you. Your answers will help us to keep improving your care and the care of others. Thank you.

1. Over the past two weeks have you been affected by pain?  0 Not at all, no effect  1 Slightly - but not bothered to be rid of it  2 Moderately - pain limits some activity  3 Severely - activities or concentration markedly affected  4 Overwhelmingly - unable to think of anything else

2. Over the past two weeks, have other symptoms e.g. nausea, coughing or constipation seemed to be affecting how you feel?  0 No, not at all  1 Slightly  2 Moderately  3 Severely  4 Overwhelmingly

3. Over the past two weeks, have you been feeling anxious or worried about your illness or treatment?  0 No, not at all  1 Occasionally  2 Sometimes - affects my concentration now and then  3 Most of the time - often affects my concentration  4 Can’t think of anything else - completely pre-occupied by worry and anxiety

4. Over the past two weeks, have any of your family or friends been anxious or worried about you?  0 No, not at all  1 Occasionally  2 Sometimes – it seems to affect their concentration  3 Most of the time  4 Yes, always preoccupied with worry about me

5. Over the past two weeks, how much information have you and your family or friends been given?  0 Full information or as much as wanted – always feel free to ask  1 Information given but hard to understand  2 Information given on request but would have liked more  3 Very little given and some questions were avoided  4 None at all – when we wanted information

6. Over the past two weeks, have you been able to share how you are feeling with your family or friends?  0 Yes, as much as I wanted to  1 Most of the time  2 Sometimes  3 Occasionally  4 No, not at all with anyone

7. Over the past two weeks, have you felt that life was worthwhile?  0 Yes, all the time  1 Most of the time  2 Sometimes  3 Occasionally  4 No, not at all

8. Over the past two weeks, have you felt good about yourself as person?  0 Yes, all the time  1 Most of the time  2 Sometimes  3 Occasionally  4 No, not at all

9. Over the past two weeks, how much time do you feel has been wasted on appointments relating to your healthcare, e.g. waiting around for transport or repeating tests?  0 None at all  2 Up to half a day wasted  4 More than half a day wasted

10. Over the past two weeks, have any practical matters resulting from your illness, either financial or personal, been addressed?  0 Practical problems have been addressed and my affairs are as up to date as I would wish  2 Practical problems are in the process of being addressed  4 Practical problems exist which were not addressed  0 I have had had no practical problems

APPENDIX 18: Picker Coordination and Continuity of Care Scale Picker Coordination and Continuity of Care Scale83

Please tick the box that best describes your recent care experiences. Please tick only one box unless requested otherwise. You may write any comments you have in the box at the end of the survey if you wish.

1. Do you think the health care providers knew enough about treatments appropriate for you?  Yes, completely  Yes, somewhat  No

2. Did you know who was in charge of different aspects of your care?  Yes, completely  Yes, somewhat  No

3. How often were your health care providers familiar with your medical history?  Never  Sometimes  Usually  Always

4. How often were your health care providers aware of your test results?  Never  Sometimes  Usually  Always

5. How often were you given confusing or contradictory information about your health or treatment?  Never  Sometimes  Usually  Always

6. How often did you know who to ask when you had questions about your health problems?  Never  Sometimes  Usually  Always

7. How often did you know what the next step in your care would be?

 Never  Sometimes  Usually  Always

8. If you had a visit with your family doctor in the past 6 months, did you feel your family doctor knew enough about your care?  Yes, completely  Yes, somewhat  No  Doesn’t apply

APPENDIX 19: Edmonton Symptom Assessment Scale Edmonton System Assessment Scale (ESAS)299 Please circle the number the best describes each of the following symptoms you are experiencing right now (at time of assessment):

______No pain 0 1 2 3 4 5 6 7 8 9 10 Worst possible pain

______Worst possible Not tired 0 1 2 3 4 5 6 7 8 9 10 tiredness

______Not nauseated 0 1 2 3 4 5 6 7 8 9 10 Worst possible nausea

______Worst possible Not depressed 0 1 2 3 4 5 6 7 8 9 10 depression

______Not anxious 0 1 2 3 4 5 6 7 8 9 10 Worst possible anxiety

______Worst possible Not drowsy 0 1 2 3 4 5 6 7 8 9 10 drowsiness

______Worst possible Best appetite 0 1 2 3 4 5 6 7 8 9 10 appetite

______Best feeling of Worst possible feeling 0 1 2 3 4 5 6 7 8 9 10 well-being of well-being

______No shortness of Worst possible 0 1 2 3 4 5 6 7 8 9 10 breath shortness of breath

Other problem (describe): ______Worst possible other ______0 1 2 3 4 5 6 7 8 9 10 symptom Least possible other symptom

Assessment (please check one): __ Baseline (Initial Assessment) __ Month 1 __ Month 2 __ Month 3

ESAS completed by (please check one): □ Patient □ Caregiver □ Caregiver-Assisted

Original Citation – Bruera E, Kuehn N, Miller MJ, Selmser P, Macmillan K. The Edmonton Symptom Assessment System (ESAS): A simple method for the assessment of palliative care patients. J Palliat Care. 1991 Summer;7(2):6-9 267

APPENDIX 20: Ambulatory and Home Care Record Ambulatory and Home Care Record ( Coyte & Guerriere, 1998)300,301

The Record asks you about the amounts of time and money that you/your family members spend to care for the patient at home. While I’m asking you these questions, I will be writing down notes so if there is any silence in between that’s why.

HEALTH CARE VISITS (home and outside of home; public and private)

HOME VISITS: How many health care professionals visited the patient at home in the past two weeks (including family doctor, physiotherapist, chiropractor, Community Care Access Center etc.)?

Provider 1:

Provider type: ______

# of visits: ______

Approximate length of each visit (# of hours): ______

 Public or  private paid

Out-of-pocket cost per visit: $______

$ or % reimbursement: ______

Provider 2:

Provider type: ______

# of visits: ______

Approximate length of each visit (# of hours): ______

 Public or  private paid

 Coyte & Guerriere, 1998 268

Out-of-pocket cost per visit: $______

$ or % reimbursement: ______

Provider 3:

Provider type: ______

# of visits: ______

Approximate length of each visit (# of hours): ______

 Public or  private paid

Out-of-pocket cost per visit: $______

$ or % reimbursement: ______VISITS OUTSIDE OF HOME: How many health care professionals did the patient visit outside of home in the past two weeks (including family doctor, physiotherapist, chiropractor, Community Care Access Center etc.)?

Provider 1:

Provider type: ______

Average # of visits: ______Approximate length of each visit (# of hours): ______ Public or  private paid Out-of-pocket cost per visit: $______$ or % reimbursement: ______

Mode of transportation (car/bus/taxi etc.) to visit: ______Distance to appointment (km/min): ______Costs (parking, transportation, food, coffee etc.): ______

 Coyte & Guerriere, 1998 269

Did caregiver travel with you? Y/N

Provider 2:

Provider type: ______

Average # of visits: ______Approximate length of each visit (# of hours): ______ Public or  private paid Out-of-pocket cost per visit: $______$ or % reimbursement: ______

Mode of transportation (car/bus/taxi etc.) to visit: ______Distance to appointment (km/min): ______Costs (parking, transportation, food, coffee etc.): ______

Did caregiver travel with you? Y/N

Provider 3:

Provider type: ______

Average # of visits: ______Approximate length of each visit (# of hours): ______ Public or  private paid Out-of-pocket cost per visit: $______$ or % reimbursement: ______

Mode of transportation (car/bus/taxi etc.) to visit: ______Distance to appointment (km/min): ______Costs (parking, transportation, food, coffee etc.): ______

 Coyte & Guerriere, 1998 270

Did caregiver travel with you? Y/N

PHONE CALLS: How many phone calls have been made to any health care professionals such as nurses, your family doctor, or Community Care Access Center (CCAC) case manager in the past two weeks? Excluding booking appointments

Provider 1:

Person spoken to (i.e., type of provider): ______

Provider affiliation (i.e. clinic, TLCPC): ______

Average call duration (in minutes): ______

# calls during interview period: ______

Who made the call (patient/caregiver): ______

Provider 2:

Person spoken to (i.e., type of provider): ______

Provider affiliation (i.e. clinic, TLCPC): ______

Average call duration (in minutes): ______

# calls during interview period: ______

Who made the call (patient/caregiver): ______

 Coyte & Guerriere, 1998 271

Provider 3:

Person spoken to (i.e., type of provider): ______

Provider affiliation (i.e. clinic, TLCPC): ______

Average call duration (in minutes): ______

# calls during interview period: ______

Who made the call (patient/caregiver): ______

EMERGENCY DEPARTMENT, PAST 4 WEEKS: How many times has the patient been seen in the emergency room in the past four weeks?

1ST VISIT:

Distance to appointment (km/min) :______

Mode transportation (car/bus/taxi/ambulance) to visit: ______

$ Parking:______$ Public transit/cab:______

Was this visit in the past two weeks? YES or NO

Did caregiver travel with you? YES or NO

2nd VISIT:

Distance to appointment (km/min) :______

Mode transportation (car/bus/taxi/ambulance) to visit: ______

 Coyte & Guerriere, 1998 272

$ Parking:______$ Public transit/cab:______

Was this visit in the past two weeks? YES or NO

Did caregiver travel with you? YES or NO

3rd VISIT:

Distance to appointment (km/min) :______

Mode transportation (car/bus/taxi/ambulance) to visit: ______

$ Parking:______$ Public transit/cab:______

Was this visit in the past two weeks? YES or NO

Did caregiver travel with you? YES or NO

HOSPITAL ADMISSIONS, PAST 4 WEEKS: How many times has the patient been admitted to the hospital in the past four weeks? (Y/N)

1ST VISIT:

Length of stay (days): ______

Distance to hospital (km/min) : ______

Mode transportation (car/bus/taxi/ambulance) to visit: ______

$ Parking: ______$ Public transit/cab: ______

Was this visit in the past two weeks? YES or NO

 Coyte & Guerriere, 1998 273

Did caregiver travel with you? YES or NO

2nd VISIT:

Length of stay (days): ______

Distance to hospital (km/min) : ______

Mode transportation (car/bus/taxi/ambulance) to visit: ______$ Parking: ______$ Public transit/cab: ______

Was this visit in the past two weeks? YES or NO

Did caregiver travel with you? YES or NO

3rd VISIT:

Length of stay (days): ______

Distance to hospital (km/min) : ______

Mode transportation (car/bus/taxi/ambulance) to visit: ______$ Parking: ______$ Public transit/cab: ______

Was this visit in the past two weeks? YES or NO

Did caregiver travel with you? YES or NO

 Coyte & Guerriere, 1998 274

CAREGIVING

How much time has you/family members/friends/volunteers etc. spent looking after the patient in the past two weeks (Examples of care: travelling to and attending health care appointments; feeding; changing a dressing)?

PRIMARY UNPAID CAREGIVER:

Caregiver Relationship (Spouse/Child/Volunteer etc.): ______

Age: ______

Gender: MALE or FEMALE

Dates of caregiving for patient: From (MM/DD/YYYY): _____/_____/______To (MM/DD/YYYY): _____/_____/_____

Average # of hours spent providing care to patient per day: ______

Employment of caregiver (Are you currently employed?): Are you currently on leave from work?: YES or NO

Sick time (# of hours): ______

Unpaid hours (# of hours): ______

Unpaid leave (# of hours): ______

OTHER UNPAID CAREGIVERS

1st other unpaid caregiver:

Caregiver Relationship (Spouse/Child/Volunteer etc.): ______

Age: ______

Gender: MALE or FEMALE

 Coyte & Guerriere, 1998 275

Dates of caregiving for patient: From (MM/DD/YYYY): _____/_____/______To (MM/DD/YYYY): _____/_____/_____

Average # of hours spent providing care to patient per day: ______

Employment of caregiver: On leave from work?: YES or NO

Sick time (# of hours): ______

Unpaid hours (# of hours): ______

Unpaid leave (# of hours): ______

2nd other unpaid caregiver:

Caregiver Relationship (Spouse/Child/Volunteer etc.): ______

Age: ______

Gender: MALE or FEMALE

Dates of caregiving for patient: From (MM/DD/YYYY): _____/_____/______To (MM/DD/YYYY): _____/_____/_____

Average # of hours spent providing care to patient per day: ______

Employment of caregiver: On leave from work?: YES or NO Sick time (# of hours): ______Unpaid hours (# of hours): ______Unpaid leave (# of hours): ______

 Coyte & Guerriere, 1998 276

3rd other unpaid caregiver:

Caregiver Relationship (Spouse/Child/Volunteer etc.): ______

Age: ______

Gender: MALE or FEMALE

Dates of caregiving for patient: From (MM/DD/YYYY): _____/_____/______To (MM/DD/YYYY): _____/_____/_____

Average # of hours spent providing care to patient per day: ______

Employment of caregiver: On leave from work?: YES or NO Sick time (# of hours): ______Unpaid hours (# of hours): ______Unpaid leave (# of hours): ______

PAID CAREGIVERS How many paid caregivers are involved in the care of the patient (Shift nurse, Personal support worker etc.)? ______

1st Paid Caregiver:

Caregiver Relationship (Personal Support Worker/Nurse etc.): ______

Age (ballpark): ______

Gender: MALE or FEMALE

Dates of caregiving for patient: From (MM/DD/YYYY): _____/_____/______To (MM/DD/YYYY): _____/_____/_____

Average # of hours spent providing care to patient per day: ______

Total provided to caregiver ($): ______

 Coyte & Guerriere, 1998 277

Will the patient be reimbursed for this money? YES or NO

If yes, indicate % or amount reimbursed: ______

2nd Paid Caregiver:

Caregiver Relationship (Personal Support Worker/Nurse etc.): ______

Age: ______

Gender: MALE or FEMALE

Dates of caregiving for patient: From (MM/DD/YYYY): _____/_____/______To (MM/DD/YYYY): _____/_____/_____

Average # of hours spent providing care to patient per day: ______

Total provided to caregiver ($): ______

Will the patient be reimbursed for this money? YES or NO

If yes, indicate % or amount reimbursed: ______

3rd Paid Caregiver:

Caregiver Relationship (Personal Support Worker/Nurse etc.): ______

Age: ______

Gender: MALE or FEMALE

Dates of caregiving for patient: From (MM/DD/YYYY): _____/_____/______To (MM/DD/YYYY): _____/_____/_____

Average # of hours spent providing care to patient per day: ______

 Coyte & Guerriere, 1998 278

Total provided to caregiver ($): ______

Will the patient be reimbursed for this money? YES or NO

If yes, indicate % or amount reimbursed: ______

Notes

 Coyte & Guerriere, 1998 279

APPENDIX 21: Bedside Confusion Scale Bedside Confusion Scale290

Interview Date: Unique Study Number:

I) Level of Alertness Scoring: Normal = 0 Observe the patient: is he/she alert? Hyperactive = 1 Hypoactive = 1 Level of consciousness: Normal□ Hypoactive□ (includes Hyperactive □ (includes agitated drowsiness, stupor, or coma) behaviour, pressured speech, W or W/O aggressive or disinhibited actions) Score, Section I: _____ II) Test of Attention Can the patient correctly recite the month of the year in reverse order? (No coaching except the patient may be urged to complete the task by the examiner if he stops midtask. Timing is performed with the second hand of either a wallclock or watch)

Tick box if an error is observed at month: Scoring: December Delay > 30 s = 1 November 1 omission = 1

October 2 omissions = 2

September ≥3 omissions, reversal of task,

August termination of task = 3

July Inability to perform task = 4 June May Results: April Time > 30s March 1 omissions February 2 omission Reversal of months ≥ 3 omissions Inability to perform

January

Score, Section II: ______Total BCS Score (I + II):_____

A total score of 0 = normal [Patient appears to be cognitively intact; proceed with surveys] Score of 1 = borderline [Patient shows some signs of cognitive impairment. Make note of status, but continue with surveys] Score of 2-5 = abnormal [Patient is cognitively impaired. Do not continue surveys.]

Original citation: Sarhill N, Walsh D, Nelson KA, LeGrand S, Davis MP. Assessment of Delirium in Advanced Cancer: The Use of the Bedside Confusion Scale. Am J Hosp Palliat Care. Sep-Oct 2001;18(5):335-341. 280

APPENDIX 22: Eastern Cooperative Oncology Group Scale ECOG Performance Status370

Screening Date: Day Month Year

Grade ECOG

0 Fully active, able to carry on all pre-disease performance without restriction.

1 Restricted in physically strenuous activity but ambulatory and able to carry out work of a light or sedentary nature, e.g., light house work, office work.

2 Ambulatory and capable of all self-care but unable to carry out any work activities. Up and about more than 50% of waking hours.

3 Capable of only limited self-care, confined to bed or chair more than 50% of waking hours.

4 Completely disabled. Cannot carry on any self-care. Totally confined to bed or chair.

5 Dead.

Thank you for completing this form.

Original citation: Oken MM, Creech RH, Tormey DC, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J of Clin Onc. 1982;5(6):649-655.