The authors analyze competing forces affecting the diffusion of telemedicine practices across organizations, potential learning effects from telemedicine practice, and their implications for the development of telemedicine-based networks. They also speculate on the learning, diffusion, and institutional effects that telemedical collaboration may trigger; five sets of propositions are advanced to explain these effects.
Telemedicine can be broadly described as a bundle of technologies designed to deliver health care services where the patient and the health professional are separated by physical distance. In North America, early diffusion of telemedicine has been largely shaped by government push efforts in the U.S. and Canada. On the one hand, within Canada's publicly financed system of health care, government incentives have hastened a broad diffusion of telemedicine.1 On the other hand, within the mixed-market system of the U.S., government incentives such as grants and contracts have led to the limited diffusion of telemedicine programs to a relatively restricted number of health care settings such as prisons, rural areas, and university medical centers.2 Hence, U.S. government funding of telemedicine projects has pushed this technology's use with underserved or difficult-to-serve populations.
However, the conditions related to the adoption of telemedicine appear to be changing as the technology matures and the related institutional systems adapt to make its use more effective. For example, reimbursement has become more accessible3 and technology has improved with the availability of more bandwidth for transmission of data.4 In addition, telemedicine software programs and equipment have become more varied5 and much less expensive than early systems.6 These changes have reduced some of the reasons cited for nonadoption of telemedicine as a medical delivery strategy for many organizations.7,8
The main purpose of this article then is to explore how the diffusion of telemedicine will change as government sponsored "push" efforts are joined or replaced by market forces and even more efficient and effective technology. By understanding the potential patterns of relationships that may form between health care organizations, administrators will be better able to identify potential telemedicine partners, predict competitors' telemedicine collaboration activity, and focus resources on the telemedicine relationships most likely to meet their organizations' goals. Regulators will also benefit by understanding how future diffusion patterns of telemedicine may differ from past patterns induced mainly by government funding. This knowledge will enable the regulators to sharpen the focus of government incentives, deploying them where most needed to achieve social goals that might not be achieved without incentives, and minimizing the use of incentives in areas that will likely develop without intervention. Understanding likely changes in organizations that may result from telemedicine interaction will help administrators and physicians see potential implications of collaboration earlier making the effects of telemedicine partnerships on organizations more predictable. Better predictability will help in the preparation of the organization to minimize the negative effects of collaboration and maximize possible knowledge gains and improve service delivery using telemedicine collaboration.
In the following sections of this article we present how organizational learning, diffusion of innovation, and competitive forces will influence the adoption of telemedicine as a health care delivery technology.
David F. Robinson, Ph.D., is Assistant Professor, Texas Tech University, Area of Management, Lubbock, Texas.
Grant T. Savage, Ph.D., is Richard Scrushy/HealthSouth Chair and Professor in Health Care Management, Department of Management and Marketing, University of Alabama, Tuscaloosa, Alabama.
Kim Sydow Campbell, Ph.D., is Associate Professor, Department of Management and Marketing, University of Alabama, Tuscaloosa, Alabama.