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Telemedicine has been touted as a solution to the problems of access to health care experienced by rural and other isolated populations. Few studies exist, however, that explain the differential use of telemedicine by patients. Patient utilization of this technology is likely to be predicted by both those factors that affect the adoption of new ideas, on the one hand, and those factors that affect the utilization of health care, on the other. These include (1) propensity factors such as education and ethnicity; (2) enabling factors such as income and health insurance, and (3) need characteristics such as the severity of the illness as well as factors that impact (4) accessibility. Data were collected from samples of patients who had experienced telemedicine in one of two rural locations in Texas. A second sample of patients who had not experienced telemedicine was drawn from these same locations for comparative purposes. Models were developed to differentiate among patients who would elect to use telemedicine for each of six hypothetical medical conditions versus the alternatives of consulting their local physician without the presence of telemedicine or travel to see a specialist. Separate models were developed for those patients who had previous experience with telemedicine and for those without such previous experience. Prior experience was associated with a greater willingness to use telemedicine for all but the most serious of medical conditions. Predisposition factors had the greatest impact on the more serious conditions (e.g., problem pregnancy and cancer), and enabling conditions as well as access factors were more likely to affect the less serious conditions (e.g., cough and rash).

Proponents of telemedicine believe this technology will resolve many of the problems associated with the lack of access to specialty care by isolated populations. However, in order for telemedicine to be successful, health care professionals and patients must be willing to use it. Few studies exist that identify those characteristics that differentiate adopters from non-adopters of this technology. Furthermore, little is known about the kinds of health care professionals and patients who are willing to make continued use of telemedicine after initial adoption. Prior studies of the adoption of medical technology have identified personal characteristics such as age and gender among patients and age, gender, years since graduation from medical school, and medical specialty among providers as predictors of the adoption of medical technolgy. Using data collected from the first 483 teleconsultations performed by a West Texas medical system, we developed prediction models of the continued use of telemedicine using the personal characteristics of patients, primary care professionals, and medical specialists as predictors. We included the number of primary care professionals and specialists involved in prior teleconsultations in these prediction models. Patient characteristics contributed little to the prediction of continued use of telemedicine; however, characteristics of the health care professionals such as age, gender, and years since graduation as well as the number of health care personnel involved in previous consultations were significant predictors of the continued use of telemedicine.