The Impact of Perioperative Data Science in Hospital Knowledge Management

Journal of Medical Systems (2019) 43: 41 https://doi.org/10.1007/s10916-019-1162-3

SYSTEMS-LEVEL QUALITY IMPROVEMENT

Márcia Baptista1 & José Braga Vasconcelos2,3 & Álvaro Rocha4 & Rita Silva5 & João Vidal Carvalho6 & Helena Gonçalves Jardim7 & António Quintal8

Received: 10 August 2018 /Accepted: 8 January 2019 /Published online: 12 January 2019 # Springer Science+Business Media, LLC, part of Springer Nature 2019

Abstract Conservative practices, such as manual registry have limited scope regarding preoperative, intraoperative and postoperative decision making, knowledge discovery, analytical techniques and knowledge integration into patient care. To maximize quality and value, perioperative care is changing through new technological developments. In this context, knowledge management practices will enable future transformation and enhancements in healthcare services. By performing a data science and knowledge management research in the perioperative department at Hospital Dr. Nélio Mendonça between 2013 and 2015, this paper describes its principal results. This study showed perioperative decision-making improvement by integrating data science tools on the perioperative electronic system (PES). Before the PES implementation only 1,2% of the nurses registered the preoperative visit and after 87,6% registered it. Regarding the patient features it was possible to assess anxiety and pain levels. A future conceptual model for perioperative decision support systems grounded on data science should be considered as a knowledge management tool.

Keywords Perioperative data science . Knowledge management . Clinical decision support systems . Hospital information systems

This article is part of the Topical Collection on Systems-Level Quality Improvement

* Márcia Baptista 1 Information Technology Research Department, Santiago Compostela [email protected] University, Santiago, Spain 2 Knowledge Management and Engineering Research Group, José Braga Vasconcelos Universidade Atlântica, Barcarena, Portugal [email protected] 3 Centro de Administração e Políticas Públicas (CAPP) da Álvaro Rocha Universidade de Lisboa, Lisboa, Portugal [email protected] 4 Departamento de Engenharia Informática, Universidade de Coimbra, Rita Silva Coimbra, Portugal [email protected] 5 Bloco Operatório, Hospital Dr. Nélio Mendonça, Madeira, Portugal João Vidal Carvalho [email protected] 6 Politécnico do Porto, ISCAP, CEOS.PP, S. Mamede de Infesta, Portugal Helena Gonçalves Jardim [email protected] 7 Health Higher School, Madeira University and The Health Sciences Research Unit: Nursing, Coimbra, Portugal António Quintal [email protected] 8 Universidade da Madeira, Madeira, Portugal 41 Page 2 of 7 J Med Syst (2019) 43: 41

Introduction & Design, construct and implement a Perioperative Electronic System at Doctor Nélio Mendonça Hospital; Context & Define a research approach and conceptual model for perioperative decision support systems grounded on data sci- Population aging is an unquestionable reality and a growing ence and knowledge management (KM); phenomenon pointing to a large increase in the elderly popu- & Assess new patient features and create new clinical knowl- lation. In 2013 life expectancy was 80 years. Old population in edge for healthcare decision making before and after the the United States will result in a significant increase of surgical Perioperative Electronic System implementation; services and in Portugal the trend will be identical. On the & Produce perioperative nursing production and quality other hand, most health systems collect at least some individ- indicators. ual patient data during clinical face-to-face encounters. While the conventional way to collect such data are on paper forms and register books, increasingly, face-to-face encounters are Contributions being captured electronically. Electronic health systems have the potential to change the health care system from a mostly This study is a relevant step for perioperative care towards a paper-based production to one that utilizes clinical and other perioperative decision support system (PDSS). The theoretical pieces of information to assist care providers in delivering background is based on a conceptual model using data science more quality to their patients [1]. Keeping these data person- and knowledge management practices. This framework in- alized rather than anonymous is facilitated by using electronic tends to deal with the complexity and scope of the current records and hospital information systems which can more eas- perioperative demands, such as infections and adverse events ily store, access, analyse, and share data. This trend will con- reduction, information added to inform healthcare profes- tinue as improvements are made in computer hardware, soft- sionals, decisions, guidelines, best practices, policy, costs ware, and telecommunication infrastructure and as countries and training, thereby improving the safety and quality of develop the skills necessary to implement electronic data stor- healthcare and its value. age and transmission systems [2].

Motivation and rationale Background and literature review Perioperative care is emerging rapidly as technology advances Perioperative electronic system as a hospital and increases complexity to maximize quality, healthcare val- information system ue, patient and professional security. While innovations in diagnostic and therapeutic technologies have driven past im- Modern hospital information systems (HIS) are comprehen- provements in quality of perioperative care, future transforma- sive, integrated and specialized information systems designed tion in care will be enabled by data [3]. to manage the administrative, financial and clinical aspects of The perioperative background is a unique environment that hospitals and healthcare facilities. They are considered one of includes many challenging variables: complex clinical care the most important focal points on which the delivery of performed by teams, high cost, sophisticated technologies that healthcare within hospitals and different types of medical in- often do not interoperate and a large array of supplies, instru- stitutions depends [5]. Despite evidence of these benefits, phy- ments, and implants that are difficult to manage. These vari- sicians’ and hospitals’ utilization of HIS and electronic health ables create a setting of massive complexity and are a source records are still low [5]. of a significant percentage of patient safety-related adverse Perioperative procedures and its different stages are often events [4]. the most intensive and efficacious therapeutic interventions Conventional methodologies, such as registry studies, are available in medicine and these treatments are frequently cu- limited in their scope for discovery and research, extent and rative and are sometimes the only alternative for patients. complexity of data, breadth of analytic techniques, and trans- Surgeons and other professionals are highly trained thus the lation or integration of research findings into patient care [3]. technology and resources that they employ are typically ad- vanced, expensive and scarce. So, the optimization of these Objectives limited resources is paramount to the safe, effective, and efficient delivery of healthcare [6]. The purpose of this research project was to assess the impact Perioperative information technology has the potential to of integrated perioperative data science tools in hospital improve the quality of health care, reduce costs, decrease med- knowledge management. The main objectives were: ication administration errors, reduce time spent on paperwork, J Med Syst (2019) 43: 41 Page 3 of 7 41 increase management efficacy and allow affordable access to Perioperative data science process is to create tools to measure, health care. model and quantify the pathways or processes within the con- According to Fig. 1 it should render all the preoperative text of patient health states or outcomes, and use information stages and process. Researchers concluded that IT or automa- gained to inform healthcare decisions. Data is pervasive tion of aspects of the surgical patient preparation process and throughout the surgical care pathway; thus, data science can the coordination and management of surgical equipment has impact various aspects of care including prevention, diagnosis, the potential to increase the speed of information exchange, intervention, or post-operative recovery. A data science ap- reduce interruptions to clinicians and decrease the possibility proach to surgical decision-making could more accurately pre- of adverse events in the perioperative setting. With migration dict severe complications using complex data from pre-, intra-, to the use of an electronic health record in the operating room and post-operative contexts, how it could support intra- (OR), time that nurses previously spent on paperwork and operative decision-making using both existing knowledge and administrative functions can be dedicated to providing better continuous data streams throughout the surgical care pathway, patient care and ensuring accuracy in documentation [7, 13]. and how it could enable effective collaboration between human care providers and intelligent technologies [3]. Data science in healthcare The confluence of science, technology, and medicine in our dynamic digital era has spawned new data applications to The emergence of perioperative data science is a key element to develop prescriptive analytics, to improve healthcare person- addressing limitations and creating a sustainable path toward alization and precision medicine, and to automate the evidence-based improvement for interventional healthcare. reporting of health data for clinical decisions.

Fig. 1 Perioperative electronic system (overview) 41 Page 4 of 7 J Med Syst (2019) 43: 41

Data science in health care has seen recent and rapid prog- and information but rather does require a new perspective to ress along 3 paths: (1st) through big data via the aggregation link the pieces of information that promotes understanding of large and complex data sets including electronic medical and accelerates action - in other words, to create knowledge records, social media, genomic databases, and digitized phys- [12]. iological data from wireless mobile health devices; (2nd) The methods and techniques in KM can be categorized in through new open-access initiatives that seek to leverage the three groups: people and technology, requirements elicitation availability of clinical trial, research, and citizen science data and value measurement. Regarding the Technical Perspective, sources for data sharing; and (3rd) in analytic techniques par- KM tools deals with explicit knowledge, meaning that ticularly for big data, including machine learning and artificial Knowledge can be written on a support that is mainly an intelligence that may enhance the analyses of both structured electronic one. Several concepts from the broad computer sci- and unstructured data [8]. ence research, such as data mining, rules based reasoning, and multi-agent systems have been integrated in KM solutions, the Knowledge management in healthcare integration of those tools depends on the processes in action [11]. Information and knowledge are key organizational resources Knowledge management practices need more effective re- used to define appropriate strategies and business plans that sults for the healthcare learning organization. Data science should translate reality accurately. Knowledge is organized techniques can be used to automate knowledge extraction and analysed information in order to make it understandable and representation, helping KM program leaders to get closer to apply to problem resolution and decision making [9]. to that elusive goal (see Fig. 2). Value creation is only achieved through knowledge creation, its disseminating throughout the organization, developing and expanding new products and services. On the other Research methodology hand, the competitive success is reflected by the way intellec- tual capital is managed, since its capture, encoding and trans- Sample and setting fer to obtain new skills through training and business process reengineering. Knowledge management also allows individ- The setting for this project was the operating room at Dr. Nélio uals to make informed and effective decisions [10]. Mendonça Hospital between 2013 and 2015 (Funchal, In service base companies, knowledge is a central intangi- Madeira Island, Portugal). ble asset where knowledge management deals with the crea- Perioperative nurses and patients were the targeted population, use, reuse, dissemination of Knowledge. The growing tions for this project and were divided in two groups and role of information technologies enabled the development of stages: before and after the implementation of the electronic efficient KM tools using databases and collaborative software system. [11]. This sample population was non-probabilistic and causal as Knowledge management (KM) is a recognised field with a matter of convenience. The 113 nurses were divided in two many applications and techniques and its implementation in groups: the 1st group had 83 nurses and 2nd had 30 nurses. health care is challenging. Health care can profit from many These nurses came from all areas of perioperative services. advantages that KM can provide but numerous challenges are Inclusion criteria for the sample included the following: must current, some are proper to KM and other particular to the be a perioperative registered nurse. health care ground [11]. There was a second sample of 460 surgery patients also Health care delivery relies heavily on knowledge and divided in two groups with 230 patients in each one. evidence-based medicine and the delivery of care replies on Inclusion criteria for this sample included patients with cooperation of several partners that need to exchange their 65 years old and more for elective surgery with no signs of knowledge in order to provide care with quality and efficien- cognitive deficit. cy. In health care, KM is being developed mainly in the domain of electronic health record management and health organization management; in this context, previous researches Type of study in the business domain have been adapted and applied to the Healthcare Knowledge Management [11]. An observational, quantitative and descriptive survey design A strong technological infrastructure, customized for the was used to determine perioperative nursing registry practices needs of each organization, provides the tools necessary for towards the use of the electronic system in providing. ensuring the success of knowledge management efforts. What Regarding the surgery patients, a correlational and emerges from the countless of corporate experiences is that longitudinal study design was performed to evaluate KM does not require more or better tools to gather more data new assessed features. J Med Syst (2019) 43: 41 Page 5 of 7 41

Fig. 2 Knowledge creation process using data science and KM tools

Data collection and perioperative nursing records from imperative organiza- tions like Direção Geral da Saúde (DGS) (Portuguese admin- An observation grid was prepared for the perioperative nurses istrative healthcare) and Dr. Nélio Mendonça Hospital to as- in the intraoperative, postoperative and preoperative stages. sure its effective execution. For perioperative patients, a questionnaire was created to de- The intervention strategies established periodic meetings mographic and clinical data, Amsterdam Preoperative with the different intervening areas; training session’sdevel- Anxiety and Information Scale (APAIS), Spielberger State- opment for surgical services nurses in the operating room and Trait Anxiety Inventory (STAI), postoperative pain, pressure in the BPerioperative Nursing^ situation; monitoring and eval- ulcers, Barthel scale and falling risk were features also uating perioperative electronic system procedures; continued measured. adjustment and development and confidentiality concerning the use of clinical data.

Preparedness planning Perioperative nurses observation Electronic perioperative system creation and implementation This system was designed with a specific layout for the surgi- First of all, for the Electronic Perioperative System conception cal procedure which gathers three main stages: intraoperative, and implementation a task force was gathered, including sur- postoperative and preoperative processes. This system imple- geons, anesthesiologists, nurses and computer engineers. mentation led all health professionals like surgeons, The main stages included: anaesthesiologists, nurses and other technicians to work in an organized manner and in one platform, with more detailed, & Presentation of the Perioperative Electronic System to sur- standard, completed and updated procedures. These proce- geons, anaesthetists, perioperative nurses and others in- dures followed DGS guidelines and policies. New data was volved in the surgical process; registered like surgical procedure duration that was not & Clarification of its implementation; accounted for surgical safety checklist. A new direct connec- & Explanation of the advantages of improving assistance tion to national databases, participation in HELICS - Hospitals care, with greater security to the surgical process, not only in Europe Link for Infection Control through Surveillance and for the patient, but also for health professionals and units; updated waiting lists were promising. & Alert to the importance of this system as a knowledge In the preoperative stage a preoperative visit was conducted management tool, innovating and developing the periop- and applied a preoperative checklist (service and block) ob- erative process by gathering production, structure, process serving the patient reception at the OR and recorded and outcome indicators. registration. In the intraoperative stage the action plan continuity, nurs- A literature review on perioperative nursing was performed ing diagnoses and record registration were observed. with special consideration for external/internal norms, guide- In the postoperative stage the post anaesthetic care, postop- lines and mandatory protocols inherent to the operating room erative visit and record registration were observed. 41 Page 6 of 7 J Med Syst (2019) 43: 41

Statistical methods registered the preoperative visit and after its implementation 87,6% of the nurses registered it. The statistical methods used descriptive measures, T-Student test for independent samples and One-way Anova. The statistical package was IBM SPSS 22.0 and the significance level Discussion α =0,05. This research project aims to contribute in the fields of data science and knowledge management for healthcare systems, Principal results and more specifically, for perioperative (and clinical) decision support systems. Perioperative patients The purpose of this research project was to assess the impact of integrated perioperative data science tools in hospital Perioperative patients assessed in both groups were mostly knowledge management. According to the literature review, women (1st group: 57,8%/ 2nd group: 63%) between 65 and electronic health records utilization is still low despite evi- 69 years old (1st group: 36,5%/ 2nd group: 30%). Performed dence of HIS benefits [5]. By implementing a perioperative surgeries were manly major (1st group: 70%/ 2nd group: electronic system at Dr. Nélio Mendonça Hospital operating 78,7%) with general anaesthetic (1st group: 58,7%/ 2nd room the records in paper form were now computerized. group: 59,1%). The medium surgery time was 2 h and Perioperative nursing practices which included preoperative 58 min in the first group. In the second group it was 3 h and visit data, intraoperative interventions and postoperative visit 2min. were performed with higher data registry after implementing Patient features assessed were anxiety and pain levels, fall- the perioperative electronic system. Regarding the surgical ing risk exhibited that after the implementation of the periop- patient, postoperative acute pain and anxiety levels were also erative electronic system the anxiety levels (1st group: 13,72/ monitored showing lower levels after this system 2nd group: 10,97) monitored and the falling risk (1st group: implementation. 57,0%/ 2nd group: 48,3%) were lower than before (p value The migration to the electronic health records in the oper- <0,05). The pain level observed in the preoperative stage (1st ating room (OR), time that nurses previously spent on paper- group: 2,66/ 2nd group: 1,19), intraoperative stage (1st group: work and administrative functions were dedicated to provid- 2,05/ 2nd group: 0,72) and postoperative stage (1st group: 4,5/ ing better patient care and ensuring accuracy in documentation 2nd group: 0,45) was also inferior after the implementation of [7]. With the reorganization and compilation of these compo- the perioperative electronic system (p value <0,05). nents and instruments in the OR, professionals cooperated by resolving many problems, never discussed before, and that, in a way, converged for the quality assurance and safety of peri- Perioperative nurses operative care conditions, for all the intervenient. Technology that is designed expressly for and adequately The nursing plan was registered by 62,7% nurses; there was tailored to the demands of the perioperative care process and no register about the security checklist and time indicators like requirements resulted in optimal clinical adoption and out- the operative times. After the electronic system implementa- comes. By assessing health gains through the application of tion, the nursing plan was registered by 96,7% of the nurses, a dynamic and holistic model created for surgery patient fea- security checklist and operative times was recorded by 100%. tures and perioperative nursing practices the results indicate In the postoperative stage, before the perioperative electronic that the perioperative electronic system was beneficial to the system implementation in the OR the acute pain monitoring nurses and to the surgery patients. was not registered, and the register of the postoperative visit was recorded by only 4,8% of the nurses. After the electronic system implementation, the acute pain monitoring and the postoperative visit was registered by 86,7% of the nurses. Conclusions and final recommendations The new registry in the perioperative period included recorded operative times, which were not counted in the patients, sur- Nowadays challenges in perioperative and surgical care are gical safety checklist application, with direct linkage to the overwhelming. Perioperative care is complex and involves national database for epidemiological surveillance of surgical multiple interconnected subsystems which are a microcosm site infection HELICS-Surgical Site Infection and updated of the hospital. Surgical procedures are major drivers of pa- waiting lists. tient morbidity, mortality, satisfaction, and overall hospital Regarding professionals, before the perioperative electron- costs and profitability. 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