Modeling Telemedicine Systems to Effectively Allocate Administrative and Medical Resources

Abstract

Telemedicine stands as one of the most promising innovations in healthcare. By delivering healthcare through electronic means, doctors can greatly expand the number and geographic diversity of patients they serve. While most telemedicine today focuses on more traditional health care applications, telemental health aims to apply telemedicine principles to mental health services. Telemental systems offer convenient and efficient ways for healthcare providers to provide psychological and psychiatric service to patients in far-flung geographic areas. Unfortunately, these systems can suffer from serious congestion if not well put-together. Maximizing the valuable time of doctors while ensuring short waits for patients should be a primary goal of telemedicine system design. Telemental health systems come in several varieties such as synchronous, asynchronous, and group telemental health. Each variety offers different system properties and flow behavior. This paper presents models for synchronous, asynchronous, and group telemental health systems using a discrete-event simulation and examines their properties using that tool. It compares their relative performance in this way. The analysis determines effective system capacity and demonstrates the effect of expanding the number of doctors and patients in the system. Moreover, the results can serve as a tool for healthcare providers seeking to establish telemental health systems. The models revealed that, given a single specialist, nurse, set of audiovisual equipment, and administrative team, group telemedicine offered the highest capacity of roughly 300 patients at a time. Asynchronous individual systems followed with a capacity of 30, and synchronous individual systems trailed with a capacity of 25. As capacity decreases, however, the configuration’s ability to provide patients with one-on-one care rises. The proper selection depends on the needs of the patient and the demands on the provider. The analysis also extends to some modifications of the original models that remove assumptions made in describing group telemedicine, probe the impact of variance reduction, and examine the maximum number of specialists a single administrative team can handle.