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Understanding the full financial effects of telemedicine systems on payers, providers, and patients has been hampered by the lack of data from full-fidelity systems operating at a steady state. The vast majority of telemedicine systems in the United States have yet to achieve their full potential in serving their target populations and are operating well below capacity. The purposes of this research are two-fold: (1) to develop a methodology that compensates for the limited availability of empirical data on the financial effects of telemedicine; and (2) to test this methodology in a comprehensive telemedicine system in West Virginia. The proposed methodology utilizes simulation modeling techniques for evaluating the financial performance of a mature telemedicine system. It is particularly suitable for analyzing large, complex systems that have not yet achieved steady-state operation. Although complex, the methodology can be described simply as consisting of two major steps. The first is the identification of all of the relevant variables and parameters for modeling. The second consists of simulating "real world" decision situations involving all relevant variables and parameters. The relation among the variables and parameters are described in terms of mathematical equations. The ability of the researcher to estimate the financial effects of a given telemedicine system is a function of the extent to which the resulting model approximates conditions of the real world; i.e., the fit between model and reality.
Cameron et al. (Mon,) studied this question.