Design and Analysis of Diagnostic Service Centers

Abstract

In the health-care domain, diagnostic service centers provide advice to patients over the phone about what the most appropriate course of action is based on their symptoms. Managers of such centers must strike a balance between accuracy of advice, callers' waiting time, and staffing costs by setting the appropriate capacity (staffing) and service depth. We model this problem as a multiple-server queueing system, with the servers performing a sequential testing process and the customers deciding whether or not to use the service, based on their expectation of accuracy and congestion. We find the dual concerns of accuracy and congestion lead to a counterintuitive impact of capacity: Increasing capacity might increase congestion. In addition, (i) patient population size is an important driver in management decisions, not only in staffing but also in accuracy of advice; (ii) increasing asymmetry in error costs may not increase asymmetry in the corresponding error rates; and (iii) the error costs for the two major stakeholders--the service manager and the patient--may impact the optimal staffing level in different ways. Finally, we highlight the relevance of our model and results to challenges in practice elicited during interviews with current clinical researchers and practitioners.