Learning Through Telemedicine Networks - CiteSeerX

Proceedings of the 36th Hawaii International Conference on System Sciences - 2003

Learning Through Telemedicine Networks Liqiong Deng Texas A&M University, College Station, TX 77843-4217 [email protected]

Marshall Scott Poole Texas A&M University, College Station, TX 77843-4217 [email protected]

Abstract Telemedicine is advocated for its potential to improve the accessibility and quality of health care delivery while lowering costs [1]. Although the potential benefits of telemedicine have long been a subject of research and intense discussion, the results of actual implementations have been far from conclusive. Most current research, which views telemedicine as a substitute for travel and a basis for economies of scale, is rather limited in exploring the full potential of telemedicine. In this paper, we develop a new framework in which organizational learning is the theoretical basis for explaining the development and potential benefits of telemedicine. We conceptualize telemedicine as an integrated ITenabled health care network of collaborative relationships. A well-developed telemedicine network is high in density, maintains a balance of strong and weak network ties, and is comprised of a diverse set of relationships. This type of network facilitates learning through the exchange, transfer and distribution of medical information/knowledge, the generation and dissemination of new knowledge about how to collaborate effectively via telemedicine, and the application of this knowledge in telemedicine practice. Viewing telemedicine in this light directs our attention to outcomes not emphasized in most prior research, including the diffusion of medical knowledge and expertise, and the development of collaborative knowledge shared by the health care parties. This paper develops a research model to explain how learning occurs in telemedicine practice, identify factors influencing the learning process, and indicate how thriving telemedicine networks can be built. The model focuses on flexibility of information technology, network density, strength of network ties, and network diversity as key factors having impacts on learning. It also views the acquisition, transfer and sharing of medical knowledge and the development of telemedicine collaborative knowledge as two learning processes occurring simultaneously and recursively, and reinforcing each other. Ultimately, learning is the core process that helps realize the potential of telemedicine.

1. Introduction Telemedicine refers to the use of electronic information and communication technologies to provide and support health care when distance separates the participants [2]. It is perceived as having the potential to improve the accessibility and quality of health care delivery while lowering costs [1]. However, although these potential benefits of telemedicine have been the subject of much research, the results of actual implementations have not been conclusive. Paul [3] argues that the current research framework on telemedicine is inadequate due to the use of inappropriate concepts and measures to assess the telemedicine’s impact. Viewing telemedicine as a substitute for travel and as a basis for economies of scale leads the majority of current research to focus on technological capability, cost, and acceptance of telemedicine. While these are important issues, we believe they lead researchers to underemphasize other outcomes that are potentially more important, such as learning, knowledge creation, and the transformation of medical practice. The recent resurgence of telemedicine has the potential to start a trend toward virtual networking among health care parties. If it develops past isolated applications, telemedicine will tend to evolve from point-to-point connections toward more coordinated, integrated, and interoperable networks. These IT-enabled networks involve collaborations among multiple players across multiple sites and thus provide the foundation for the development of organizational learning communities. These communities can promote the knowledge acquisition, sharing, and creation, which would enable quality improvement and novel insights in the knowledgebased health care delivery industry. The purpose of this paper is to develop a framework that considers telemedicine as an IT-enabled integrated health care network that supports collaboration and learning for knowledge creation, acquisition, transfer and sharing. Propositions posit relationships between properties of the telemedicine network, learning processes, and health care delivery outcomes.

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2. Telemedicine Networks and Organizational Learning 2.1. Trends in Telemedicine Over the last 30 years, theories and evaluations of telemedicine have changed, reflecting the fact that telemedicine technologies evolve rapidly and that new applications of information technologies are constantly being discovered and implemented in health care [4]. Despite its origin in the manned space flight program of NASA in the 1950s, telemedicine is largely a product of the information age. The convergence of the rapid expansion of information and telecommunication technologies and the managed health care revolution has fueled a resurgence of telemedicine [5], which promises to provide solutions for the challenges facing health care delivery, such as limited accessibility to health care, escalating cost of care, and uneven quality of care. The concept of telemedicine embodies major transformations occurring simultaneously in medical care and in information technology. Telemedicine is not only a technological innovation, but a socio-cultural one as well [4]. At one level, telemedicine is a technological system adopted as a communication medium for medical information transfer or exchange between health care parties; at another, it is an innovative social/organizational system that has implications for the way health care delivery is structured and organized. Most current telemedicine research has focused on issues associated with the technical system, such as technological capability, cost and acceptance of telemedicine from the standpoint of demonstrating its viability and sustainability. This limited focus is also reflected in the ways in which telemedicine is conceptualized. The most widely used definition of telemedicine in literature  “the use of electronic information and communication technologies to provide and support health care when distance separates the participants” [2]  focuses on the technology that makes the interaction possible without physical presence, but largely ignores the social/organizational effects of telemedicine that may stem from its integrative functions. By electronically linking together health care parties (health care professionals, hospitals, researchers, institutions, patients, nurses and etc.) for effective collaboration, and by providing easy access to up-to-date information/knowledge, telemedicine has the potential to create interlinked learning networks. It has also been argued that the unique capabilities and integrative functions of telemedicine can be realized only when telemedicine is viewed as an integrated network providing single- or multiple- specialty health care services [6]. Bashshur et al [4] envision the development of virtual regions of telemedicine, which are in fact networks

composed of “a discontinuous set of points in an electronically connected virtual hierarchy of primary-, secondary-, and tertiary-care providers” [4]. These virtual health care regions, being structured into interconnected networks, transcend the space and time limitations of traditional health care delivery and are able to attend to a range of problems. Ideally, within the networks, specialty health care can be delivered from point to point as needed, regardless of geographical location. As a result of the development and utilization of telemedicine in rural areas, an ongoing virtual networking revolution has the potential to transform the rural health care system through increased integration and assimilation of health care professionals and institutions into systems and networks [7]. Electronic networks of health care providers and institutions are replacing traditional health care organizations to serve as the focus of health care delivery in communities. When telemedicine is defined as an integrated collaborative network for health care delivery [8] [9], the literature on organizational learning implies a theoretical approach to examine how telemedicine can most effectively be developed and utilized. Health care is a knowledge-based industry, characterized by an exponentially expanding knowledge base, increased uncertainty and equivocality, time compression and severe cost constraints [3]. So, individual and organizational learning that promotes knowledge creation, acquisition, transfer and sharing is of critical importance.

2.2. Organizational Learning The organizational learning literature distinguishes several different types of learning. Learning in terms of acquiring existing knowledge from external sources and integrating it into the current knowledge base of the organization [10] can be contrasted with learning by knowledge creation, developing and discovering new knowledge, through the actions and interactions among organizational members [11]. The distinction between single-loop and double-loop learning is also important [12]. Single-loop learning is largely based on stimulusresponse mechanisms. It is triggered by feedback generated by a process of observing the consequences of action and changing actions or strategies for achieving a desired outcome without changing the underlying theory or assumptions about those actions. Single loop learning focuses on solving problems in the present without examining the appropriateness of current learning behaviors [13]. In contrast, double-loop learning emphasizes continuous experimentation and feedback in an ongoing examination of the very way of defining and solving problems [13]. “Double loop learning involves reframing learning to see things in new ways” [14]. It comprises reflection on and change of the goals, action strategies, operating rules, as well as the governing

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variables about actions, i.e. the basic values and assumptions of the theory. Double-loop learning is particularly difficult because, as Argyris [15] notes, people tend to build defensive routines that make it very difficult to abandon the existing theory of action and to accept that a new theory is right and will work. Nevertheless, to perform and survive, organizations should engage in both single- and double-loop learning, as well as the process of knowledge acquisition, sharing and creation.

2.3. Processes of Organizational Learning Learning is also a social process that occurs during activities undertaken in conditions of uncertainty, complexity, and conflict [16]. Learning requires social interaction for the continuous conversion of tacit and explicit knowledge [17]. Moreover, this interaction must have certain qualities for learning to be effective. Learning will be easiest and most effective when parties engage in collaborative interaction marked by a cooperative climate in which mistakes are tolerated and free interchange of ideas is the norm [18]. And while learning occurs in dyadic interaction, interchanges among multiple parties with different ideas are more likely to eventuate in new insights. Hence, effective learning is most likely to occur during rich, spontaneous interaction among parties with different specializations and different types of experience and education. This is especially true of double-loop learning, which requires frame breaking and novel insights. Learning is easier and faster when a set of actors form a community that consults about a practice or problem [19]. Members of learning communities are aware of each other’s perspectives and tendencies. They value one another’s views and may even implicitly take others’ perspectives into account when facing an uncertain situation. A learning community is a public good. Its members know that they obtain value from the community and are willing to contribute their own questions, expertise, and insights in a system of generalized exchange. Once a learning community is recognized as a public good it acquires a momentum of its own. Members are drawn to contribute to the community and interaction within the community is self-sustaining. These considerations imply that networks are an important part of the learning process. Powell and Brantley [20] suggest that when knowledge is broadly

distributed and brings a competitive advantage, the locus of innovation is found in a network of inter-organizational relationships. In such cases learning often occurs in the interstices between firms, universities, research laboratories, suppliers and customers [21]. According to Cohen and Levinthal [22], networks increase absorptive capacity, the capability for utilizing and building on external new knowledge, which is critical for effective learning to occur. Grundmann [23] also argues that networks provide learning benefits because they have a greater variety of search routines and convey richer, complex information. These notions imply the potential of telemedicine as an ongoing, interactive learning system for knowledge creation, acquisition, transfer, and sharing. For telemedicine to yield its potential benefits, it is important that it be managed to provide and sustain the proper context for learning, as learning involves complex interactions, exchange of information, and collaboration that are all crucial to learning. In this paper, we focus on the learning about two important kinds of knowledge  medical knowledge and knowledge about how to collaborate. These two kinds of knowledge are the products of two learning processes occurring simultaneously and recursively [24] through the telemedicine network. First, health care parties make use of the telemedicine linkages to enhance the acquisition, exchange, transfer, and sharing of specific medical information/knowledge; and second, they learn to become adept at collaborating with their partners [24] via the telemedicine network. These two learning processes reinforce each other, because learning about medical knowledge can be facilitated and enhanced by the telemedicine collaborative knowledge, and learning about telemedicine collaborative knowledge must build on the process of acquiring, transferring and sharing medical knowledge.

3. Theoretical Model and Propositions What characteristics of telemedicine networks are most conducive to effective learning? How do these characteristics influence the different types of learning involved in the network? Figure 1 presents a model of the factors influencing the impact of organizational learning on telemedicine outcomes. The variables and the proposed relationships among these variables are described below.

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V a lu e -A d d e d H e a l th C a r e D e liv e r y

F le x ib il ity o f I n f o rm a tio n T e ch n o lo g y

D e n s ity o f T el em ed ic in e N e tw o r k L e a r n in g t h r o u g h T ele m ed ic in e N e tw o r k s S tr e n g th o f T e le m e d ic in e N et w o r k T ie s

S h a re d M e d ic a l K n o w le d g e

T el em e d ic in e C o lla b o r a tiv e K n o w led g e

D iv er s i ty o f T e le m e d ic in e N et w o r k T ie s

Figure 1. Research Model of Telemedicine Networks

3.1. Telemedicine as an Integrated Health Care Network of Collaborative Relationships The socio-technical network of collaborative relationships in telemedicine is composed of network ties created and maintained through social interaction, and the nature of these ties influences learning. Each tie has at least two dimensions: the electronic connection enabled by information and communication technologies, and the relational linkages the electronic connection supports, for example consultation, education, and workflow. The electronic connection is established with wires, computers, software and hardware and sets the basic parameters for relational linkages; in turn, the relational linkages determine the regularity, frequency and nature of interaction among health care parties. The nature and properties of the telemedicine network influence whether the network entails learning and what types of learning can occur. Consider the case of a telemedicine network link that is set up to support storeand-forward transmission of X-ray and “cat scan” images so that specialists can interpret them and consult with rural physicians. If the technology supports high speed transmission of the images to the specialist, but does not allow specialists and rural physicians to view and point to regions of the image while discussing it, opportunities for learning are limited. The specialist will tend to stipulate diagnoses, and transactions through the network are likely to resemble an “assembly line.” The knowledge and

status of the specialist will tend to prevail, and the rural physician is likely to take the role of “consumer” of the specialist’s opinions. However, if there is the capability to simultaneously view and work with the image, the specialist and rural physician can interact more easily and the interchange becomes more collaborative. In this case, the rural physician has the opportunity to question and explore the specialist’s interpretations and the interchange takes on a more collaborative cast. The rural physician can learn about interpreting images and the specialist can learn about local conditions that should be taken into account and sharpen her ability to consult. Such collaboration is possible even without the shared view just discussed: if the specialist and rural physician set up a reference grid on the image and refer to areas on that grid as they communicate, rich and informative interchanges can occur. However, this type of improvisation requires extra steps and a special agreement between the two physicians, and is not likely to be the norm. In cases where the link was characterized by other relationships between the two physicians, such as friendship or membership in an integrated care network that required such close consultation, the collaborative relationship is more likely to develop. Since information technology is the enabler of telemedicine network connections, it can be argued that the attributes of the technologies used for telemedicine influence the learning occurring within the telemedicine network. Learning involves considerable social

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interaction and experimentation, which require flexibility in utilizing information technologies to achieve different tasks and goals. Therefore, flexible information technologies are likely to provide an appropriate context for learning to occur. Thus, the following proposition can be suggested: Proposition 1: Effectiveness of learning will be positively related to the flexibility of the information technologies used for telemedicine. In addition to information technologies, there are three properties of telemedicine networks that are likely to influence learning: density, strength of tie, and diversity.

3.2. Density of Telemedicine Network Density of a telemedicine network refers to the extent to which the members of the network are electronically interconnected. It is calculated as a ratio of the number of actual ties to the number of potential ties in a network [25]. The higher the density of a telemedicine network, the greater the interconnectedness among health care parties within the network. The degree of interconnection among health care parties greatly affects the likelihood and ease with which they will be able to gain access to medical information/knowledge and other medical resources within the network. A dense network allows rapid flow of substantive knowledge as well as the knowledge of who knows what [26]. Thus, the greater the network density, the more likely parties become aware of, access and adopt the medical knowledge from others in the same network. This suggests the following proposition: Proposition 2: The greater the network density is, the more effective the learning process of medical knowledge acquisition, transfer and sharing. Furthermore, the dense network provides a rich, fast stimulus-feedback mechanism, through which the network members can adjust their behaviors for better, quick response to feedbacks acquired in information communication and collaboration. So, the denser the network, the more likely a learning community is to form and sustain itself through effective single-loop learning. Thus, the following proposition can be suggested: Proposition 3: Density of a telemedicine network positively influences the effectiveness of single loop learning.

3.3. Strength of Telemedicine Network Ties The strength of a network tie is “a combination of the amount of time, the emotional intensity, the intimacy, and the reciprocal services which characterizes the tie” [27]. Strong ties exist when considerable time and emotions are invested in a relationship, and when reciprocity is involved between participating actors; however, weak ties entail more limited investments of time and intimacy.

While network density is concerned with the network structure, the strength of network ties refers to the nature of relational linkages in the network. The strength of network ties determines the nature of social interactions and has an impact on the learning processes. Strong ties, existing between formally tied health care work pairs or teammates, are associated with high levels of trust and with long-term, close relationships. Those strongly tied participants need frequent communication and also are motivated to communicate and collaborate with each other. As a result, strong network ties often involve intense social interaction, which facilitates the transfer of tacit and complex knowledge among participants. Strong ties are necessary to form the core of a learning community. By contrast, weak ties exist among participants who communicate infrequently and have less close relationships. They can be sustained through email lists or discussion forums in the context of a telemedicine network. Weak ties provide interpersonal, instrumental contact and connectivity for otherwise unconnected health care parties. Weak ties also function to interconnect different health care networks. Conway [28] identified three roles of actors that can serve as weak ties that join networks  the liaison who acts as intermediary between two or more networks, the bridge that exists between the gatekeepers of two networks, and the link-pin who has overlapping membership in two or more networks. As weak ties bridge otherwise disconnected health care networks, they also play an important role in distributing information and resources. Weak ties open the network to new participants, introduce novel information, and simultaneously allow for autonomy and adaptation to changes. While both are important for knowledge transfer and learning, strong and weak ties perform different functions and facilitate different types of learning. Strong ties breed norms and shared perspectives and may even promote conformity pressures, and thus provide a common ground for communication and interaction. Strongly tied participants show similarities in attitudes, background, experiences, and access to resources [29]. They are motivated to communicate and share information, and provide each other with early, frequent access to resources available within their social circle [30]. Thus, they will be likely to undertake joint activities of efficiently exploiting the available resources and making improvements to existing practices. But since intense social interaction involved in strong-tie relationships often leads to routinized responses and ingrained patterns of thinking, there is little departure from the established ways of doing things. This promotes single-loop learning, which will help members acquire new, more efficient insights into and improve on existing practices without changing the underlying assumptions. While strong ties facilitate efficient exploitation of existing resources within the network, they simultaneously create an

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insularity from new ideas and developments outside their narrow focus of attention. In contrast, weak ties enable the effective detection and exploration of novel opportunities and innovative ideas. They make possible wide-ranging information exchanges that are important for broadening the knowledge base of the network and exposing the health care parties within the network to ideas and approaches different from their own. In addition, weak ties also increase members’ ability to recognize and take advantage of new opportunities and resources, which then contributes to the development of the network’s absorptive capacity. Therefore, weak ties help to obtain novel insights that put existing way of work into question, allow for continuous experimentation of new ways of learning, and thus foster double-loop learning, which emphasizes new ways of looking at the world. There is clearly a tradeoff between strong and weak ties in terms of learning. If the telemedicine network is too heavily weighted toward strong ties, its learning will improve present practice, but be low in innovation. If the network is weighted too heavily toward weak ties, new knowledge will be generated, but the community will be loosely knit and the diffusion and consolidation of these insights will be difficult. So, the following propositions can be suggested: Proposition 4: The more strong ties there are in a telemedicine network, the more effective its single-loop learning. Proposition 5: The more strong ties there are in a telemedicine network, the more effective the learning process concerning how to collaborate effectively via telemedicine. Proposition 6: The more weak ties there are in a telemedicine network, the more effective it is at introducing new ideas that promotes double-loop learning. Proposition 7: A balance between strong and weak links must be maintained for a telemedicine network to promote both single- and double- loop learning.

3.4. Network Diversity Telemedicine network diversity refers to the different types of health care parties that are electronically connected. Relational variety provides the opportunity for the health care parties, when undertaking healthcarerelated activities, to access and combine information from qualitatively different sources, thus enabling learning through novel integration of relevant information and knowledge. Thus, a telemedicine network of relations between diverse health care parties provides unique sources of knowledge creation by enabling each participant to draw on and innovatively combine a wide span of information and knowledge. Oftentimes, this is essentially a double-loop learning process, which

introduce news ideas and challenges existing routines. So, a telemedicine network with diversified network ties can promotes double-loop learning by introducing a diversity of knowledge and expertise and stimulating the questioning and reconsideration of the assumptions underlying current practices. In addition, the exposure to and integration of different knowledge and expertise entail effective collaborations among health care parties. When working with those who are from different specialties or cultures, on the one hand, people often have problems in interacting with their partners, and on the other hand, they are more motivated and eager to learn how to communicate and collaborate effectively to obtain the desired outcomes. So, the following propositions are suggested: Proposition 8: The diversity of telemedicine network ties positively influences the effectiveness of double-loop learning. Proposition 9: The more diversified the telemedicine network ties, the more effective the learning process concerning how to collaborate effectively via telemedicine.

3.5. Learning and Quality of Health Care Delivery Then how the learning processes through telemedicine network influence the quality of health care delivery? To fully understand its implication for value-added health care delivery, we need to examine the two learning processes about medical knowledge and collaborative knowledge, which explain what kinds of knowledge are created and transferred as a result of learning through telemedicine network. The first learning process about medical knowledge directly contributes to value-added health care delivery by promoting fast and wide sharing of medical knowledge so that the network promotes the best possible medical practices. For the second learning process, health care parties learn how to apply a combination of available technologies effectively and how to interact with each other around the technologies and information in a way that supports trusting exchanges. As a result, shared knowledge is developed among health care parties as to the productive applications of telemedicine technologies and the way participants can be best organized around the tasks for effective collaborations in health care delivery. Thus, the second learning process indirectly influences value-added health care delivery by creating shared telemedicine collaborative knowledge, which enhances collaborations that in turn further facilitate various learning processes through telemedicine. Based on the above analysis, the following propositions are suggested: Proposition 10: The learning process of medical knowledge acquisition, transfer and sharing enhances shared medical knowledge across the whole network of

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telemedicine, which significantly contributes to valueadded health care delivery. Proposition 11: The learning process concerning how to collaborate effectively via telemedicine generates shared telemedicine collaborative knowledge among health care parties, which in turn lead to value-added health care delivery.

4. Conclusions and Implications This paper provides a conceptual framework to understand the role telemedicine plays in the new health care paradigm that requires the efficient and effective transfer of health care information/knowledge across an integrated health care network and to point to the importance of various learning processes related to the development of telemedicine and its contribution to value-added health care delivery. This paper discusses four types of learning that might occur in telemedicine networks: single-loop learning, double-loop learning, learning about specific medical knowledge, and learning about how to collaborate effectively during telemedicine activities. Conceptualizing telemedicine as an integrated health care network of collaborative relationships, and adopting the perspective of organizational learning as the theoretical basis for explaining the development and potentials of telemedicine, the proposed model focuses on the construct of network ties that make up the network structure and provide the context for learning, making medical knowledge and expertise a shared resource wherever and whenever needed. This paper also contributes to the understanding of how the properties of telemedicine network influence the occurrence and nature of learning processes. In sum, telemedicine’s full potential and benefits can be realized only when all health care parties are committed to construct and participate in a network of learning through their active exploration and exploitation of a well-developed telemedicine network, which is enabled by flexible information technologies, is high in density, sustains a balance of strong and weak ties, and maintains a set of relations among diverse health care parties.

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