Healthcare Supply Chain Management: an Instructive Model 525

Healthcare supply chain management: An instructive model 525

Healthcare Supply Chain Management: An Instructive Model Designed to Create Service Value

Stan York, EdD, Charles Wainright, PhD, MHA, & Dennis C. Chen, PhD

Abstract In an environment of increasing costs and growing demand for higher quality service outcomes, the healthcare industry has been notably unenthusiastic in embracing supply chain management (SCM) practices. Healthcare organizations are reluctant to adopt practices which are goods-dominant and support an aggregate view of a single process not adequately addressing the permeable, interactive, and co-creative nature of the healthcare service supply chain (SSC). As healthcare organizations realign operations to improve outcomes, a new understanding of service supply chain dynamics is required to achieve the objectives of the Triple Aim. The authors introduce a theoretical framework for conceptualizing healthcare SCM grounded in service-dominant logic, and principles of service science within a complex adaptive system operating in concert with the Triple Aim objectives. This conceptual model is posited to assist academic professionals in educating future healthcare leaders in attempting to create service value within their respective organizations. Service is the fundamental basis of exchange interactions that are patient-focused and value is co-created. Using a service-dominant logic as framework, emphasis on value co-creation can focus on process agility tailored for unique patient requirements. Decentralized technology can become information exchanges. Complexity and uncertainty management paradigms can be shifted to a contextual approach that more adequately address provider-patient interactions and provide serendipitous opportunities for understanding and improving healthcare service supply chain management.

Please address correspondence to: Charles Wainright, PhD, Belmont University, Jack C. Massey College of Business Administration, 1900 Belmont Blvd., Nashville, Tennessee 37212, Phone: (615) 460-5407; Email: [email protected] 526 The Journal of Health Administration Education Fall 2017

Introduction and motivation As healthcare costs continue to rise and demand for greater access to higher quality services increases, value creation in the service supply chain (SSC) has gained more attention by healthcare providers (Chakraborty, & Dobrzykowski, 2014; Acharyulu et al., 2012; Nollet & Beaulieu, 2003; Burns et al., 2002). A driving factor behind the increased recognition is due in part to the acknowl- edgement that sub-optimization occurs if each organization operates for its own proprietary gain, independent of others in the chain, rather than seeking to co-create value and elevate chain performance by cooperating with the goals and activities of other organizations (Cooper et al., 1997). There is a recog- nized need for collaboration and coordination of management, logistics, and internal business services within and between decentralized organizations in the SSC that enables the delivery of high-quality, safe patient care throughout the healthcare system (Dobrzykowski et al., 2014; de Blok et al., 2012; Boyer & Pronovost, 2010). Historically, SSCs have been poorly understood traditional “goods” production practices and theories commanding the bulk of the academic attention to date. This goods-dominant logic has been the focus of much of the supply chain research attention in the past (Vargo & Akaka, 2009; Vargo & Lusch, 2004a, 2008) resulting in a paucity of research in service systems supply chains and even less in healthcare service supply chains (Dobrzykowski et al., 2014). Further, the body of knowledge that does exist is fragmented or compartmentalized (Vries & Huijsman, 2011; Boyer & Pronovost, 2010). As a result, many healthcare organizations have been reluctant to adopt practices which were goods-dominant and support an aggregate view of a single process which does not adequately address the permeability, interactive, and co-creative nature of the SSC (McKone‐Sweet et al., 2005). Until recently theoretical models were limited that integrated the role of customers in value creation and the customer-centric nature of SSCs – or similarly, the patient-focused nature of healthcare SSCs. Current goods- dominant frameworks fail to recognize the role the patient plays in the value creation where service is the fundamental basis of the transaction. (Stavrulaki & Davis, 2014). A framework was required based on the idea of service where resources or competencies were exchanged for the benefit of another system or person, and where goods are mechanisms deployed to distribute services. The service-dominant foundation for this framework is best supported by the work of Vargo & Lusch (2004a, 2008, 2009), with further development found in the discipline of service science (Maglio & Spohrer, 2008; Maglio et al., 2009; Maglio et al., 2010; Spohrer et al., 2008). Healthcare supply chain management: An instructive model 527

The need for collaboration and coordination within the healthcare supply chain and a service-dominant view of service exchange can drive healthcare organizations to seek designs that optimize service delivery performance. To achieve this, Berwick et al. (2008) concluded that healthcare organizations must pursue three objectives, collectively called The Triple Aim: improving the patient experience, improving population health, and reducing per capita cost of healthcare. Berwick et al. (2008) argue that in order to accomplish these aims there must be system integration at the macro level. Service models, organizations, or systems can take on the role of integration. “The important function of linking organizations across the continuum requires that the integrator be a single [sic] model, organization (not just a market dynamic) that can induce coordinative behavior among health service suppliers to work as a system for the defined population” (Berwick et al., 2008, p.763). Service supply chains are uniquely situated to (a) permit regular communication throughout the organization as well as with external stakeholders; (b) play an active role in cost management; (c) assist in evaluating clinical practice variations that may drive increases in cost of care of device or supply utilization; (d) promote the use of data and analytics in improving delivery; and (e) and build community relations to assist in community awareness (AHRMM, 2017). This paper seeks to introduce a new healthcare SSC framework that incorporates service-dominant logic and principles of service science. By focusing on service as the fundamental basis of exchange where the interaction is customer-oriented (i.e., patient-oriented) and value is co-created in a context that is “idiosyncratic, experiential, contextual, and meaning laden” (Vargo & Lusch, 2008, p. 7; Vargo et al., 2010). Using this service-dominant logic as a framework, emphasis on value co-creation can focus on process agility tailored for unique patient requirements, decentralized technology can become information exchanges, and complexity and uncertainty management paradigms can be shifted to a more contextual approach that more adequately address the provider-patient interaction, providing unique opportunities for understanding and improving healthcare service SCM (Chakraborty & Do- brzykowski, 2013; Gunasekaran & Ngai, 2012; Vonderembse et al., 2006; Lee, 2002). The authors first establish healthcare as a service system that is best ana- lyzed using principles of service science where service-dominant logic serves as the foundation for describing the complex interactions between provider and patient. Second, the paper provides a brief discussion examining the incongruence of production supply chain management (SCM) concepts with service system supply chains. Third, a contextual overview of the changes and complexities within the general and individual healthcare environment 528 The Journal of Health Administration Education Fall 2017 describes the need for a new approach to healthcare SSCs. Next, the paper develops a service-dominant healthcare service SCM model where the patient participates in dynamic interactions at various levels, creating a complex service environment that is uncertain yet simultaneously presents serendipitous opportunities for value creation. This service-dominant healthcare SCM model is viewed as a vehicle to educate future healthcare leaders in the unique aspects of the service-dominant supply system which can require a significantly different perspective and operational skillset from the skillsets and knowledge used in the traditional production supply chain management system. Finally, the paper identifies implications and limitations of the model and offers ideas for future research.

Service systems, service science and the service-dominant logic Service systems are “value-co-creation configurations of people, technology, value propositions connecting internal and external service systems, and shared information (e.g., language, laws, measures, and methods)” (Maglio & Spohrer, 2008, p.18). Service systems are complex networks of people, technology, and information interacting over varied configurations. The context of these interactions vary in characteristic and technique from person-to-person encounters, medical/health induced, self-service, technology-enhanced, computational services, multi-channel, multi-device, and location-based and context-aware services (Glushko, 2010). In service systems, the customer participates as a co-creator of value where the emphasis is on the interactional nature of value creation (Vargo & Lusch, 2008). In service systems such as healthcare, in which the customers (i.e., the patients) participate in the core service and are active participants in work activities, co-production becomes a component of value co-creation (Alter, 2013; Vargo & Lusch, 2008). Understanding these provider/ patient collaborations is crucial in articulating a healthcare SSC. Maglio and Spohrer (2008, p.18) define service science as “the study of service systems, aiming to create a basis for systematic service innovation. Service science combines organization and human understanding with business and technological understanding to categorize and explain the main types of service systems that exist, and how service systems interact and evolve to co-create value.” Perhaps no other industry demonstrates the integration of organizational and human aspects of systems thinking as healthcare, where outcomes are almost exclusively defined by these value-creating interactions. Understanding how value is co-created along the supply chain and the context of these interactions will contribute to improving operational efficiencies, reducing costs, and increasing sustainability of healthcare service systems. Healthcare supply chain management: An instructive model 529

Service science is theoretically rooted in service-dominant logic (Maglio & Spohrer, 2008). Service-dominant (S-D) logic provides a service-centered alternative to the goods-dominant (G-D) logic for the understanding of economic exchange and value co-creation (Vargo & Lusch 2004, 2008; Cambridge University & IBM, 2007; Maglio et al., 2009; Vargo & Akaka, 2009). The foundational premises of service-dominant logic are relevant for use in defining the context of healthcare services. In many ways, S-D logic parallels the care logic of healthcare systems, where service is the fundamental basis of exchange, where service is exchanged for service, and where goods are service-provision vehicles (Vargo & Akaka, 2009, p. 35). Several key foundational premises are of particular note: that the customer (patient) is always a co-creator of value; that a service-centered view is inherently customer oriented (patient-centered) and rational; and that value is always uniquely and phenomenologically determined by the beneficiary (patient) (Vargo & Lusch, 2008). These principles are critical in describing a patient-centered supply chain and assessing the contextual framing of healthcare services in which goods derive value through the goods-patient-provider exchange so that the patient is an active participant in the supply chain (Chandler & Vargo, 2011; Matsushita & Kijima, 2014).

Review of service supply chain models SCM provides an important foundation on which operational decisions can be made. While the actual conceptualization of supply chains varies, the common principles focus on the passage of an input through a transformation process to produce an output of value to or for the customer (Baltacioglu et al., 2007). SCM involves those decision-making activities that are intended to control the dynamics of the flow in the process. According to Mentzer et al. (2001), SCM definitions can be categorized in three groups: management philosophies, how to implement those philosophies, and sets of management processes. SCM focuses on business processes from the end user to original suppliers that provide the products, services, and information that add value for customers and stakeholders (Lambert et al., 1998). As the prominence of the service sector increases and leads economic expansion, it is difficult to find a generally accepted definition of SSC in the extant literature (Zhang & Chen, 2015). While there is no unified definition of SSC, most SSC research and modeling has focused on various attempts to adapt traditional production supply chain functions to the service sector. Two primary trends emerge in recent SSC modeling. First, the generalized expansion of traditional production-oriented SCM principles to key service processes, essentially servitizing the product process and emphasizing service aspects of products (Kinnunen & Turunen, 2012; Turunen, 2013; Zhang 530 The Journal of Health Administration Education Fall 2017

& Chen, 2015). The work done by Ellram et al. (2004) has contributed to this genre by proposing a general framework adapted from manufacturing, using the global supply chain forum model (GSCF) and supply chain operations reference (SCOR) model while identifying key service processes. The second trend focuses on the effect of existing traditional production supply chain practices deployed in the service industry (Sengupta et al., 2006). The customer/supplier duality was explored by Sampson (2000). Cook et al. (2001) applied traditional supply chain theories to healthcare. Kathawala and Abdou (2003) examined the relationship of decreasing costs and increasing quality in the SSC and described how traditional manufacturing SCM practices (especially inventory and production) can be adapted to the service sector. Recent research has begun to explore SSCs as the global economy becomes more service-oriented (Giannakis, 2011). Historically, the lack of attention paid to SSCs was in part due to a global economic dependence on manufacturing and farming (Ellram et al., 2007). While SSCs are generally considered more complex than manufacturing supply chains, concepts such as flow complexity, conceptual visualization, and intangible products as outcomes are slowly be- ing investigated and added to the understanding of service SCM (Baltacioglu et al., 2007; Maull et al., 2012). The notion that principles, theories, and constructs of production SCM are readily applicable to service processes has not been substantiated (Giannakis, 2011; Van Ark et al., 2008; Sengupta et al., 2006). There are a variety of ways in which SSCs differ from their manufacturing counterparts including the intangi- bility of services, heterogeneity, inability to be stored, simultaneous production and consumption, and difficulty of transferring ownership (Giannakis, 2011; Jacobs & Chase, 2011). Further, services have a unique labor component that contributes much of the value found in its supply chain (Sengupta et al., 2006). The high degree of human interaction in the SSC results in more uncertainty and variability in the service processes (Sengupta et al., 2006).

The healthcare context General environment The scarcity of research in healthcare service SCM can be attributed in part to the complexity of the individual healthcare organization and environment, rapid technological development (i.e., diagnostic, restorative, and operational) and the highly individualized and personalized nature of care. Peter Drucker (2002) described the healthcare organization and hospital as “altogether the most complex human organization ever devised” (p.74). The source of this complexity is derived from numerous stakeholders: practitioners, patients, payors, suppliers, governmental agencies, and administrators (often with Healthcare supply chain management: An instructive model 531 competing priorities, perspectives and timelines); decentralized payors and providers; decidedly dynamic interaction of diverse, highly trained, and educated professionals; rapidly advancing technology; while all occurring in an exceedingly interactive internal and external environment where service expectation for the patient is uniquely personal (Padula et al., 2014; Vries & Huijsman, 2011; Golden, 2006). The degree of change, interdependency of entities, and environmental munificence existing in the healthcare industry all combine to create an environment of performance uncertainty which impacts organizational efficiency and performance (Duncan, 1972; Davis, 1993; Van der Vorst & Beulens, 2002; Narasimhan & Talluri, 2009; Simangunsong et al., 2012; Gligor et al., 2015; Krishnan et al., 2015). Recent events in political and socio-demographic environments, both nationally and globally, point to an increased interest in SCM as a means of improving the delivery of healthcare services, eliminating waste, and controlling costs. Nationally, the need for a healthcare SCM research focus is underscored by the increasing cost of healthcare, which, in the United States, is projected to be approximately $4 trillion – or about 20% of the nation’s total Gross Domestic Product (GDP) – by 2020-22 (Cuckler et al., 2013; Berwick & Hackbarth, 2012; Keehan et al., 2011). Further, in the United States, the Patient Protection and Affordable Care Act (PPACA) was passed into law on March 23, 2010 with implementation beginning Jan. 1, 2014 (PPACA, 2010). While the impact of this watershed legislation on healthcare operations is uncertain, the aims of reform implicitly require changes in SCM. These include expanding insurance to near-universal coverage; increasing the affordability of health insurance; advancing healthcare service value, quality, and efficiency; reducing waste- ful costs; increasing primary healthcare access and availability of preventive healthcare and; investing in public health through preventive care, wellness programs, and education (Rosenbaum, 2011).

Care environment The highly individualized nature of care cannot be overlooked in any analysis of healthcare operations and SCM. The delivery of healthcare services must be addressed in terms of a complex service system. The complexity demands that individual components be free to respond in ways not always predictive and whose resultant interactions are interconnected such that response of one part of the process can change the environment for other components (Plsek & Greenhalgh, 2001; Wilson et al., 2001). In healthcare, the actual service delivery or clinical care encounter is the dominant function within the healthcare supply chain system for which all other functional interactions in the supply chain exist. The final outcome of any specific healthcare SCM system should 532 The Journal of Health Administration Education Fall 2017 improve the quality of healthcare and reduce defects in the care of patients in a single supply chain system as identified by the Institute of Medicine’s (IOM) six quality dimensions: safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity (IOM, 2001). As a discipline, SCM plays a critical role in meeting the goals of the National Institutes of Health’s (USA) mission in improving the experience of care, improving the health of populations, and reducing the per capita cost of healthcare (Berwick et al., 2008). Recognition of the patient clinical care episode as the central factor which drives the healthcare supply chain is a key premise of the model we propose. Within this complex service system, the interaction with the patient and the care provided to the patient ultimately shapes the complexity, uncertainty, and serendipity present in the supply chain. The behavior of the healthcare supply chain is determined in part by established rules and theories of supply and demand, but also by unique and adaptive responses to changes in the environment. The complexity of relationships and interactions are powerful determinants of supply interactions as are the social, political, and cultural expectations that accompany most all healthcare discussion.

Need The interactive and dynamic nature of the healthcare supply chain requires that all three overarching objectives of the Triple Aim (improving the patient experience, improving population health and, reducing the per capita cost of healthcare) be pursued simultaneously to effectively assess the contributing supply chain factors that impact healthcare delivery. Issues such as wait times, supply-driven care, and unbalanced capacity may all lead to poor coordination of care, preventable readmissions, and a dissatisfying patient experience (McCarthy & Klein, 2010). The authors suggest that healthcare supply chain management can serve in an integrator capacity within the greater healthcare organization and system by fulfilling the functions described by Berwick et al. (2008) including individual and family involvement, redesign of primary care services and structures, population health management, financial management, and system integration at the macro level. In linking supply chain management with the key integration functions of the Triple Aim, the Association for HealthCare Resource Management (AHRMM) in 2017 suggested the following connections: 1. Individual and family involvement: The supply chain is a rich source of evidence-based information that supports care givers. The sourcing of products, timing, and delivery may directly or indirectly impact patient safety and ultimately drive patient satisfaction. Healthcare supply chain management: An instructive model 533

2. Redesign of primary care services and structures: As systems and models of care change (e.g., patient-centered medical home model, or PCMHM), the supply chain crosses services boundaries and provides support to maintain a consistent continuum of care and manage cost across treatment specialties. This standardization helps ensure quality, cost, and value throughout the care process. 3. Population health management: The supply chain is in constant communication with the community and external stakeholders. This communication leads to knowledge which can be shared to increase prevention awareness and community action. 4. Financial management: Supply chain metrics are poised to provide information on cost and enhance value by managing the total cost of inventory across the continuum of care. 5. System integration: Supply chain management operates at a unique junction where strategic and organizational objectives must align to support the clinical care, and where variation and utilization are key factors in determining organizational performance.

Therefore, simple cause-and-effect, supply-and-demand models are inadequate to explain healthcare SCM to educate future healthcare leaders. Prior production-oriented SCM research may not have direct application to healthcare services, thus contributing to the misunderstanding and inconsistent application of SCM practices in healthcare organizations. Further, the serendipity presented by such an interactive dynamic system may be key in developing a model of healthcare SCM that provides a practical theoretical basis for the coordination of activities, transaction of business, and the purposeful care of patients that transcends operational efficiencies. We propose such a model in this manuscript.

Model development Service-dominant healthcare supply chain The healthcare supply chain has limited similarity to product supply chains (Lambert, 2008) but finds much in common with service system supply chains (Ellram et al., 2004). However, unlike the previously stated models, the patient often fulfills the role of the manufacturer and customer (provider and patient) simultaneously. The feedback loop, while two-way in nature, extends far into the supply side and continues to be necessary long after the original service. As a result, two distinguishing characteristics emerge. Healthcare supply chains 534 The Journal of Health Administration Education Fall 2017 are patient-focused and bi-directional in composition so that the flow of goods and services through the supply chain are moderated by the interaction with the patient to arrive at the value proposition. Assessment of this interaction is measured first by outputs including population health status, satisfaction with the care experience, and costs per capita. However, the final outcome (i.e., quality of life) is highly contextual and dependent on the idiosyncratic nature and serendipitous opportunities encountered in the interactive care process between provider and patient.

Patient-focused and bi-directional The healthcare supply chain should be patient-focused and managed with the good of the patient in mind. The outcome of the healthcare delivery process is not focused on productivity, efficiencies, or product, but rather the ef- ficacy of the interaction between all factors and resultant impact on patient health status. Figure A presents the patient (and family) as the focus of this interaction – the center of the healthcare supply chain. By taking a patient- focused view, the common understanding of the supply chain is altered. It becomes one where the patient interacts with many service providers in an effort to create a valuable experience (Chakraborty & Dobrzykowski, 2013). Understanding the patient-focused nature of service delivery as fundamental to healthcare SCM can provide meaningful information on how to create more value-adding activities for the patient (Maull et al., 2012). The Institute for Healthcare Improvement set forth the Triple Aim for describing value in the healthcare supply chain where outputs of the system include improved health of the population, improved patient experience of care, and reduced per capita cost of care (IHI, 2015; Berwick et al., 2008).

Figure A

Patient-focused and bi-directional characteristics Healthcare supply chain management: An instructive model 535

The healthcare supply chain is bi-directional. There must be information feedback between the various levels of interaction in the chain. Rather than goods, services, or information flowing from supplier to customer, the healthcare supply chain also exhibits a bi-directional flow. Healthcare providers rely upon the recurring feedback of information from regulatory agencies (e.g., the Food and Drug Administration), suppliers, other care providers, patients and families, and diagnostic testing and exams, to increase the value of care and services provided. In this way, the providers are “customers” of the patient’s feedback and personal knowledge which is incorporated back into the supply chain to moderate epidemiological (skill-based) assumptions that tend to dominate healthcare SCM. Thus, the exchange of operant resources, both provider and patient, become the key basis by which the final health service delivery is determined. The interaction of provider resources with patient application provides a contextually appropriate service that benefits the patient. As a result, managing economies of scale, while important (and common to most goods-based SCM), should not be the primary focus. Rather, service scope management of contextually appropriate operant resources should play a critical role in optimizing healthcare supply chains. This principle is consistent with the foundational premises (FP) of Vargo & Lusch (2008) and further established in Vargo & Akaka (2009) in which the primacy of operant resources (FP1 and FP4) and beneficiary specificity (F10) are critical to creating value in the service system.

Diverse and permeable boundaries In SSCs, the relationship between provider and customer is uniquely bi- directional, where the customer provides inputs and receives outputs (Samp- son, 2000). The duality of this relationship, framed by Sampson (2000) and expanded upon by Fitzsimmons et al. (2004), describes hubs rather than the linear structures of traditional manufacturing supply chains. In the healthcare industry, this concept is particularly useful in understanding interactions between patient, primary care physician, and other healthcare providers. The healthcare supply chain is composed of diverse agents operating at different and varying levels of permeable boundaries that learn from interactions at other levels (Cilliers, 1998, 2001). The proposed model goes beyond traditional limits of supply chain interaction (i.e., supply and demand) and is expanded to include how the customer (patient) manages interactions and makes decisions to create value (Maull, 2012). The concept of interaction is enlarged to include not only the exchange of goods and services but also the learning that accompanies these highly idiosyncratic and contextual encounters. 536 The Journal of Health Administration Education Fall 2017

The diversity of agents is a source of learning, creativity, and problem-solving (McDaniel & Walls, 1997; Anderson & McDaniel, 2000). When a patient enters the healthcare supply chain, that patient interacts with a number of suppliers (providers) who, in concert with other agents, develop, recommend, and provide treatment services in a climate in which the cumulative effect is unique to that patient similar to that described by Schneider & Bowen (2009). The patient may be interacting in more than one hub of service at a time. The cumulative effect of these interactions across and within service hubs produces a result that is altogether different than the sum of the parts. Equally, the supply chain may co-evolve as the patient responds to the specific treatment protocol so the healthcare supply chain is altered to be more adaptive, thus providing a solution that did not previously exist (Holland, 1995, 2012). This solution or value is both biologically and phenomenologically created uniquely for each patient. The boundaries between the levels are represented by dotted lines that become progressively solid to represent the porosity of these boundaries. Permeability represents the extent to which the structure of the service supply chain enables patients, providers, information, or goods to move between service levels in different directions. As the boundary of service extends further from the patient, the rate of porosity changes whereby less volume or specificity is transmitted or more time is required for the movement to pass from one level to the next. Boundaries suggest patients and families may have product and service exchanges across multiple tiers of the supply chain where service circumstances or product specifications are highly dependent upon unique characteristics of the patient or conditions associated with the diagnosis. Therefore, as the service or product moves further away from the patient and family, there is less interpersonal interaction and a decreasing need for supply specificity or service protocols. The standard for the service or product is based more on the general population need or epidemiological conclusions. The complexity of the healthcare supply chain is increased by the variability resulting from the number of boundaries and permeability. While the service provider at each boundary level may provide options to coordinate service interfaces, it is ultimately the patient who chooses to act upon options – a conscious decision made by the patient and family (Johnston et al., 2012). The resultant model represents a supply chain that has diverse as well as permeable and semi-permeable boundaries where the patient navigates the supply chain with providers to ensure necessary treatment services are provided. Figure B illustrates boundaries that exist in the healthcare supply chain. The coaxial ellipses increasing in size are intended to represent diverse boundaries Healthcare supply chain management: An instructive model 537 in the healthcare supply chain reaching out to various tiers of suppliers (both products and services). These boundaries converge at the patient and family, the central focus of the healthcare SSC.

Figure B

Diverse and permeable boundaries environment

Beginning with the patient and family ellipse (i.e., the encounter), the model presents levels of service contact that progressively become less permeable and broader in scope. The encounter represents entrance of the patient into the supply chain process. The timing is determined by the patient. The encounter is highly influenced by patient expectations that may or may not emanate from the healthcare supply chain (Zeithaml et al., 1993; Coye, 2004). The second ellipse represents point-of-service contact. Point-of-service contact boundary represents providers or services which require direct face-to-face patient interaction. Patient service is highly interpersonal and idiosyncratic. Primary care providers (e.g., physicians, nurses, and lab assistants), urgent care facilities, and emergency rooms are examples of point of service contact. Moving left from point of service contact, a third, larger ellipse, describes the specified supportive products and services boundary. Patients and families may interact with healthcare specialists or providers of specific healthcare 538 The Journal of Health Administration Education Fall 2017 diagnostics (e.g., CT scans, EKG stress tests, etc.) or other specialty services (e.g., pharmacy) resulting from the point of service contact. These suppliers are analogous to primary partners identified by Lambert et al. (1998) who actually perform activities or produce products that are specific to a unique patient (customer). In the fourth and fifth ellipses, the boundary area increases as more suppliers are present to provide a variety of supporting activities or products. Specifically, the fourth ellipse,general supportive products and services, includes resources which are specific to healthcare or medical services and supplies. These are often building blocks for downstream individual medical services or products. As examples, these supportive resources could include sharps, syringes, exam gloves, blood pressure monitors, etc. Suppliers in this boundary are not focused on individual patient needs, but rather, epidemiological data that provides an aggregate demand for supplies. The final ellipse is thegeneral products and services. This boundary represents independent product and service providers. Resources provided in this boundary are primarily for the utility of healthcare organizations. While actual use of these products or services is not for direct care of patients, determina- tion of demand is closely related to the volume of patient care rendered as consumption of these resources often varies with the volume of patient visits and service type. Operating and office supplies, transportation, IT service providers, and consulting are examples of general products and services. Boundaries in the supply chain model are not categorically exclusive. Firms may operate as both a primary and secondary partner (Min & Zhou, 2002). Additionally, in the healthcare supply chain the patient may traverse multiple boundaries concurrently in one episode of care. Therefore, the dis- tinction between primary and secondary may not be obvious. However, this recognition permits analysis of upstream and downstream activity to assist in determining patient service impact at multiple points along the supply chain. As the upstream suppliers’ activity is often determined by the patient visit (i.e., the point of consumption) downstream, a better understanding of the economics and value of the customer (patient) visit can be determined (Holmström et al., 1999).

Multi-dimensional uncertainty Inherent to all supply chains is the concept of uncertainty (Simangunsong et al., 2012). Fynes et al. (2005) describe uncertainty as the inability to adapt to change in the environment. Simangunsong et al. (2012) identified 14 sources of uncertainty summarized in three groups: internal organization uncertainty, internal supply-chain uncertainty, and external uncertainty. While there is Healthcare supply chain management: An instructive model 539 not a consensus as to the source of uncertainty, the unifying theme of most approaches tends to be on the outcome resulting from uncertainty. Much of uncertainty research has focused on the management of uncertainty – cop- ing with or it reducing it – with success measured by the impact on supply, demand, product, and time (Simangunsong et al., 2012). These factors, supply, demand, product, and time construct the multi-dimensional uncertainty continuum in the proposed model. Lee (2002) explores the degree of predictability of supply and demand for a given product or service as the determinant of uncertainty. The less likely demand or supply can be regularly predicted, the more uncertainty. Expanding upon Lee’s (2002) work, examples of supply uncertainty in the healthcare supply chain includes both generic and custom characteristics such as inventories which are stable or easily substituted (generic) compared to inventories which are unstable or not-substitutable (custom). Likewise, examples of demand uncertainty may include characteristics which are general in nature for the general population (generic) compared to very unique demands from very specific individuals (custom). We propose two additional dimensions to uncertainty in the model, product and time uncertainty, acting in tandem with supply and demand uncertainty, as crucial components to understanding healthcare SCM. Product uncertainty includes description and performance uncertainty where certain characteristics cannot be defined, actual performance of products cannot be predicted (Dimoka et al., 2012) or the product has an unstable storage nature (Vila-Parrish et al., 2012). Time uncertainty draws many parallels with forecasting error. The lon- ger the time horizon, the more uncertainty increases. Gardner & McKenzie (1985) concluded, “As the (time) horizon increases, a linear trend frequently overshoots the data.” The goal is to reduce the length of these horizons so as to reduce the amount of errors and uncertainty (Van der Vorst et al., 1998). Time is a common but critical measure of supply chain performance (e.g., cycle time, throughput time, utilization time, etc.). In the healthcare supply chain, uncertainty must be viewed prospectively and retrospectively – prospectively to anticipate changes and mitigate uncertainty and retrospectively to reflect on the value proposition for the patient and to learn from serendipitous events. Multi-dimensional uncertainty, permeable boundaries, and bi-directional interactions demonstrate the complexity of healthcare supply chains. The ultimate purpose is to converge at the patient care encounter where value is co-created through the encounter to achieve better health through safe and quality care at a reasonable cost. 540 The Journal of Health Administration Education Fall 2017

Complex adaptive system Healthcare is a human-based system constantly changing in practice and preference resulting in perpetually complex processes (Tan et al., 2005). Hol- land (1992) described complex adaptive systems as distributed processes, where each process operates by its own rules, influencing an output which in turn influences the actions of other parts. McDaniel & Driebe (2001) applied theoretical concepts of complex adaptive systems to healthcare organizations. Other works soon followed highlighting the use of a complex adaptive system approach in healthcare organizational development where complexity science provides a platform to encourage a more comprehensive examination into healthcare organizations. (Begun et al., 2003; Stroebel et al., 2005; Tan et al., 2005; Rouse, 2008; McDaniel et al., 2009). The complexity of healthcare organizations requires development of interdependent and self-adjusting supply chain networks, enabling clinical practices to achieve the highest, safest, and most efficient level of service derived from best practices in management, education, research, and profes- sional development. This is the context of valuation creation in healthcare service. The dynamic nature of healthcare supply chains is inextricably linked to other systems in the environment. Interdependence of these factors results in co-creation of value rather than merely adaptive responses. The interactive multi-level nature of healthcare supply chain decision-making illustrates the complexity that often requires multiscale decision capabilities (Wernz & Henry, 2009). The network design of healthcare services implies that all participants are resource integrators along the chain and this integration leads to the creation of solutions, or value for the patient. As complex systems, healthcare organizations are composed of dynamic networks. The S-D logic presents these systems as dynamic networks of multiple stakeholders interacting for value co-creation (Vargo & Akaka, 2012). In healthcare, the interaction occurs between tangible and intangible resources often influenced by the norms, culture, and practices of individual organizations in the supply chain as well as the contextual meaning of the patient-provider relationship. Context in healthcare often moves beyond the personal or physical interaction to an interaction laden with familial, religious, and metaphysical meaning. Within this interaction milieu, healthcare service exchange occurs, not in one episode but over multiple interactions. Value becomes the cumulative effect over time created across a variety of environments. Healthcare supply chain management: An instructive model 541

Serendipity As a critical function of human-based healthcare systems, healthcare supply chains can create conditions for serendipity. The dynamics of interactions between individuals and organizations in the supply chain can often produce environments in which active management of serendipity permits better decision-making and enables innovation (Snowden, 2003). Serendipity has been defined as an “unsought finding” (Van Andel, 1994). Van Andel (1994) further states “The ‘unsought’ is related to the finder or any participant or actor in the chain. It does not exclude that the finder sought something else when he found the ‘unsought’ finding” in fact this is mostly the case (p. 643). When healthcare SCM maintains emphasis on the patient, serendipity becomes an opportunity for patient encounters to reveal information that may affect the outcome of a patient’s treatment and thus change supply chain requirements either at point of service or at any point in the chain. Serendipity or serendipitous opportunity in and of itself is not positive or negative, but rather directional. Examples of a serendipitous nature might include characteristics of the patient encounter from preventive to emergency visits or from a generalist to a specialized physician. The model in Figure C depicts serendipity as a shaded elongated diamond where the maximum span coincides with the patient encounter. Serendipitous opportunity is greatest at the patient encounter where value is created. Patient encounters afford primary care providers the first, and often the greatest, opportunity to acquire serendipitous knowledge and information from the patient. Often, this intelligence is accumulated through open-ended questions, structured interviews, medical tests, or simple observation. Analogously, as activities move away from the patient through various boundaries, patient- specificserendipitous opportunity decreases. As face-to-face patient encounters decrease and individual patient information becomes indistinguishable (or protected, e.g., HIPAA) and aggregated through tiers of the supplier network, patient-specific findings decline. These aggregate effects of repeated single events or groups of unique occurrences remain in the supply chain, contributing to fluctuations in supply and demand, and impacting the healthcare organization’s ability to respond to patient demands and improve operational efficiencies. 542 The Journal of Health Administration Education Fall 2017

Figure C Healthcare Supply Chain Management Model: Actively managing change, uncertainty and serendipity

The healthcare Supply Chain Management (SCM) model Figure C presents the proposed healthcare supply chain management (SCM) model. The model is patient-focused and presents the patient (and the patient’s family) at the center. The model demonstrates the bi-directional flow of service and products to/from the patient with patient information and patient feedback flowing back to providers. The healthcare supply chain is composed of diverse and permeable boundaries (coaxial ellipses) increasing in size as the number of suppliers and volume increases. Diagnostic need, service selection, and product specificity create permeable boundaries for patient interactions, direct and proxies (e.g., patient records), in the supply chain (e.g. primary care physician visits, specialist Healthcare supply chain management: An instructive model 543 visits, pharmacy visits, etc.). Multi-dimensional uncertainty, resulting from the complexity and the rate of change prevalent in the healthcare system, often moderates traditional SCM assumptions. In addition to the more established supply and demand uncertainty, we propose product uncertainty and time uncertainty as two additional key moderators of supply chain behavior. The healthcare supply chain operates as a service-dominant system where interactions of goods, patients, and providers create value and service is innately patient-focused. Healthcare is a complex service system presenting unique and non-repeating opportunities, serendipity, which can be leveraged to improve SCM. Past SCM research and subsequent models focused largely on deterministic management where the primary issues of concern were planning, implementation, measurement, and control of supply networks (Mabert & Venkataramanan, 1998). The healthcare supply chain network, as a system based on S-D logic, takes a new perspective. Healthcare SCM concerns itself with the application of operant resources in the supply chain for a more complete understanding of supply chain behavior. All information including “unsought findings” are integrated to create value for the patient. These interventions moderate the activities of the supply chain beyond simple control and permit the creation of new value-adding activities more likely to advance population health, improve the patient experience of care, and reduce per capita cost of care. The proposed model represents healthcare SCM as a dynamic, value co-creating system with an operational aim to achieve those same outcomes.

Serendipitous opportunity as a moderator Healthcare organizations are complex service systems in which traditional notions of supply and demand are often shaped by the serendipitous nature of patient encounters. Small perturbations can lead to significant changes in value creation for the entire supply chain. Understanding the interactive nature of uncertainty, change and serendipity, in the context of a service-dominant logic system, is critical to improving the current state of operational decision- making impact process outputs and ultimately service outcomes. The model (Figure C) demonstrates the complexity and uncertainty often encountered in a healthcare delivery system. The interactive nature between the patient and various supply chain elements can be shaped by serendipitous events. Understanding this idiosyncratic and contextual nature of the patient encounter, a system of management decision-making emerges. Change management is reconstructed so that incremental adjustments rather than sweeping adjustments recognize the integrated and changing nature of the system. Controls encompass standardized parameters permitting flexibility so 544 The Journal of Health Administration Education Fall 2017 quality of care can be accessible and equitable throughout the supply chain. Recognizing the need for shortened response or lead times at the point of care requires backup redundancy at strategic supply chain constraint points where failure is not an option. Serendipitous opportunities in the patient encounter bring the greatest chance of new discoveries when the patient first interacts with the healthcare system. Uncertainty in relation to the supply chain system (supply, demand, product, and time) is lowest at the patients’ first initial encounter in the healthcare system, but uncertainty increases the further one moves out from this encounter into the supply chain. Interactions are less direct and interactive with the patient, thus emphasizing the need for feedback loops throughout the supply chain. While feedback loops are common elements of most supply chain models, it is typical to see these loops connecting the output of a process (or sub-process) with some decision-making component of another process or sub-process with subsequent process behavior modified. As a result, most supply chains are depicted as retroactive versus proactive. We propose a model that suggests managers treat unexpected events throughout the supply chain as opportunities to change and assess responses. Serendipitous opportunity is viewed as a moderator leveraging patient encounters and patient information to make supply chain modifications. Managers should learn from small histories and use near histories and hypo- thetical histories of serendipitous activities to anticipate change. Unexpected events should be seen as opportunities to change as opposed to outliers to be explained away. As the focus of service moves away from the patient, patient contact decreases as uncertainty increases and the system becomes less permeable. Managers, providers, and other healthcare professionals should be aware of and understand uncertainty and its effect on the supply chain system (demand, supply, products, services, and time) in order to adjust inventory levels, manage just-in-time strategies, create expedited orders, improve response times, and increase agility of ordering systems resulting in a more efficacious response to patient needs. This way, decisions become timelier permitting the supply chain to respond sooner to change. Healthcare managers meet the critical requirements of the patients and providers in their system more rapidly and effectively, thus reducing or eliminating undue harm to the patients they serve. Both patient and provider satisfaction increase as time is managed and costs are reduced. The resultant environment allows the system to become more adaptable and more mutable in order to serve all constituents using the system. Healthcare supply chain management: An instructive model 545

The model maintains a focus on the patient encounter. Future healthcare managers must understand that serendipitous opportunities are events for learning and adjusting. Leveraging serendipitous opportunity may require redesigning existing business/healthcare processes and possibly investing in more readily shareable database repositories (e.g., electronic health records). Performance measures must shift from single unidirectional output measures to collecting additional information from multiple sources throughout the supply chain process. By positing this model, the authors of this conceptual paper wish to assist in the education of all future healthcare leaders on the complexity and unique differences which appear in a patient-centered and service-oriented supply chain system versus traditional production supply chain models.

Implications for the healthcare supply chain, providers, patients and managers Impact of HC SCM on Triple Aim – enhancing the patient care experience Healthcare organizations are interested in enhancing the patient care experience (Institute of Health, 2015). The healthcare supply chain management principles advocated herein will help accomplish this aim by requiring healthcare organizations to focus on the patient and family as the center of supply chain management. The proposed Healthcare SCM Model shows patients and families at the center of the model. Listening to and understanding patient and family concerns will be the core to enhancing the patient care experience. Table 1 discusses two potential sets of measures to help healthcare organizations enhance the patient care experience: (1) specific questions from patient satisfaction surveys (e.g., likelihood to recommend), and (2) set of measures based on the Institute of Medicine’s six dimensions for quality improvement (i.e., Safe, Efficient, Effective, Timely, Patient Centered, and Equitable healthcare). 546 The Journal of Health Administration Education Fall 2017

Table 1

Menu of Triple Aim outcome measures

Dimensions of the IHI Triple Aim Outcome Measures Improving Population Health Outcomes: Health • Mortality: Years of potential life lost; life expectancy • Health and Functional Status: Single-questions assessment or multi-domain assessment • Healthy Life Expectancy: Combines life expectancy and health status Disease Burden: • Incidence and/or prevalence of major chronic conditions Lifestyle and Behavioral Factors: • Behavioral factors include smoking, alcohol consumption, physical activity, and diet • Physiological factors include blood pressure, body mass index, cholesterol, and blood glucose Enhancing the Patient Specific questions frompatient satisfaction surveys Care Experience Set of measures based on key quality dimensions (e.g. Institute of Medicine’s six aims for improvement: safe, effective, timely, efficient, equitable, and patient- centered) Reducing (or Control- Total cost per member of the population per month ling) Per Capita Cost Hospital and emergency department utilization rate of Care and/or cost Reduction or elimination of patient wait times NOTE: Adapted from Stiefel & Nolan (2012).

Developing supply chain measures such as lead time (wait time), utilization, and other specific patient/family satisfaction survey questions would be an effective initial assessment for any organization wishing to enhance the patient care experience. Patients (and their families) are often willing to share the “story” of healthcare experiences that either enhanced or hindered their episode of care (York et al., 2012). By listening to the patients and their Healthcare supply chain management: An instructive model 547 families and understanding their expectations, the healthcare network can then put actions in place to better meet these expectations. Priorities can then be developed to support changes which would have the greatest impact on the patient experience. Changes such as sourcing of products, timing, and delivery may impact patient satisfaction and ultimately patient safety.

Impact of HC SCM on Triple Aim – reducing (or controlling) the per capita cost of care A primary objective of all healthcare organizations is the reduction (or at least control) of costs associated with delivery of patient care (i.e., per capita cost). Healthcare SCM programs will assist organizations by providing information on cost and inventory management across the continuum of care. Analyz- ing these linkages throughout the networks will enhance the value of service delivery by improving processes and reducing various forms of waste. Cross organizational and cross-functional human resources can work together to identify specific opportunities to increase service value. Table 1 discusses potential outcome measures to reduce per capita costs: (1) measuring the total cost per member of the population per month: (2) hospital and emergency department (ED) utilization rate and/or costs; and (3) reduction or elimination of patient wait times. The proposed Healthcare SCM Model suggests opportunities to reduce (or control) cost per capita exist at each of the linkages throughout the network (e.g., at face-to-face interactions, or face-to-face with specific diagnostic protocols, or without any face-to-face interaction, but with standard protocols). The efficiency and effectiveness of these linkages may be used to develop plans to improve the flow of value, while identifying and reducing wastes. By managing these major linkages and relationships within the healthcare supply chain network, value should be increased and per capita costs of care should be minimized.

Impact of HC SCM on Triple Aim – improving population health Improving the health of the population is a major goal of the healthcare system in the US and highlighted within the objectives of the Triple Aim. However, the term “population health” has not had broad consensus as to its precise definition within the US healthcare community. Only in the last decade have agencies like the NIH and the Institute for Healthcare Improvement (IHI) made it a top priority and added some specific meaning to the term. Kindig and Stoddart (2003 proposed that population health be defined as “the health outcomes of a group of individuals, including the distribution of such outcomes within the group. These populations are often geographic regions, such as nations or communities, but they can also be other groups, such as employees, 548 The Journal of Health Administration Education Fall 2017 ethnic groups, disabled persons, or prisoners. Such populations are of relevance to policymakers. In addition, many determinants of health, such as medical care systems, the social environment, and the physical environment, have their biological impact on individuals in part at a population level” (p.381). Using this definition as a reference point, the Healthcare SCM Model proposed in this manuscript asserts that this definition is not only of relevance to policymakers, but also to supply chain manager who are in constant communication with communities and other external stakeholders. This communication can serve as a rich basis of knowledge for improving the efficiency and effectiveness of healthcare service delivery. The general health of the community population may be improved in a system where healthcare professionals can quickly access the appropriate areas of the supply chain network, making the service supply chain more agile and responsive to the providers and the needs of their patients. When examining outcome measures associated with health outcomes, the Healthcare SCM Model proposes that healthcare professionals will have a better understanding of the supply chain network and would be able to leverage this knowledge in tailoring treatments for patients that eventually improves mortality rates and functional status. Chronic diseases, which can place greater requirements on the service supply chain, may be more ap- propriately managed early in the disease process. Because the supply chain crosses all service boundaries, it may provide support to maintain a consistent continuum of care across multiple treatment specialties for patient lifestyle and behavioral factors (e.g., alcohol consumption, physical activity, and diet).

Key insights for the healthcare educator In light of the discussions provided in this manuscript, it is crucial for healthcare educators to stress the importance of the interactive and dynamic nature of the healthcare supply chain to future healthcare professionals. Prior production- oriented SCM research generally appears not to have a consistent and direct application to healthcare services, thus contributing to the misunderstanding and inconsistent application of SCM practices in healthcare organizations. As a result, previous cause-and-effect knowledge of traditional supply and demand models are simply inadequate to explain healthcare SCM to future healthcare leaders. Connecting the knowledge of the proposed healthcare SCM with the Triple Aim objectives outlined in this manuscript may generate new insights and improve communications between healthcare managers, healthcare practitioners, and supply chain network professionals. It could not only improve system efficiency and effectiveness, but also allow future leaders Healthcare supply chain management: An instructive model 549 to jointly create innovative solutions to complex supply chain management issues in support of national policy objectives. Further, the notions of serendipity and uncertainty presented by such an interactive and dynamic system are essential parameters in developing an agile service model of healthcare SCM that provides a practical theoretical basis for the coordination of activities, transaction of business, and the purposeful care of patients that transcends operational efficiencies.

Limitations and future research This paper only begins the process of discovery for understanding healthcare SCM by attempting to present a model that better reflects the realities of the healthcare environment. The scant research in SCM within service industries in general – and within the healthcare industry specifically – limits the ability to draw direct application of industrial SCM models to healthcare service and at the same time calls for further exploration and a study of factors characteristic of SSCs such as complexity, uncertainty, and serendipity. We believe the model presents a framework for understanding and research into healthcare SCM. As with any new innovation or discovery, there are limitations on the use and application of the model. While not all of these benefits will be im- mediately noticed or acquired, the sheer impetus of improved discussions on the serendipitous nature and uncertainties affecting the healthcare supply chain processes may provide the necessary catalyst to witness an overall improvement in the performance of healthcare supply chains. Therefore, many concepts and ideas that are derived from production supply chain research may not be directly transferable. The model proposes that the patient and the patient’s family should be at the center of the model. While this provides a focus for decision-making, it may not account for other opportunities that occur prior to the patient encounter. The model recognizes the complexity and interactive nature of the healthcare system and supply chain network, but does not specifically account for the simultaneous interactions or mitigating effects of these cross-interactions. Be- cause the model portrays a complex service system in a dynamic environment, these factors will compound the difficulty of measurement and observation of interactions. While grounded in existing SCM theory, the model provides a framework for further research and study, and has not been empirically tested. Future research opportunities are abundant and could further clarify product categories with demand and supply uncertainty. Research from healthcare purchasing managers and healthcare professionals regarding categories and characteristics of the uncertainty framework could improve the classification of 550 The Journal of Health Administration Education Fall 2017 variables. As well, the healthcare industry is very interested in learning about best practices in demand management and supplier relationship management (Lambert, 2008).

Conclusion Application of SCM processes and principles in the complex environment of the healthcare industry can offer valuable opportunities to improve operational efficiencies and competitive advantages of healthcare organizations. Limited research and theoretical modeling in healthcare SCM have greatly impeded the ability to improve the overall functioning of the healthcare supply chain and improve operational efficiencies as a whole. However, with the continuing growth of healthcare costs, regulatory reforms, and potential for pandemic diseases and illnesses, healthcare professionals must gain new insights and adaptive strategies to reduce costs and improve operational efficiencies to ultimately improve the quality of care provided to patients. Using the concepts of uncertainty and serendipity in the context of a complex service system, the authors of this article propose a theoretical model to assist in the education of future healthcare professionals in the distinctiveness of a healthcare SCM, a model that places patients and families at the center of the care process. The model proposed provides a framework for recognizing and understanding the patient care encounter as the primary event that drives the healthcare supply chain, and is paramount to acknowledging the potential strategies and managerial actions that are needed to bring about effectual change to healthcare SCM. Therefore, the authors of this manuscript firmly believe that providing a conceptual healthcare SCM with detailed explanations tied to the mission of the Triple Aim should serve as a meaningful addition to the curriculum of future healthcare leaders.

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