Abstract:
The goal of this work is to investigate the system configuration and information management of primary care delivery with electronic visits (e-visits). We consider a medi...Show MoreMetadata
Abstract:
The goal of this work is to investigate the system configuration and information management of primary care delivery with electronic visits (e-visits). We consider a medical institution employing primary care physicians and other clinicians that offer office visits (in-person) and e-visits (through secure messaging from patient portals), and where different queue-joining behaviors: denoted as the mixed strategy, the duplication strategy and the threshold strategy are adopted by flexible patients based on different system configurations. Different queueing models are developed to capture flexible patients’ queue-joining behaviors according to queueing information provision. In particular, we develop the equilibrium behavior of a dual server system where state information is available for one of the servers and the flexible patient exhibits a utility-maximizing behavior, which extends the literature on the analysis of queueing systems with strategic customers. The duplication strategy with deletion offers the least expected waiting time for the patients, and the threshold strategy provides the next best performance which is superior to the mixed strategy, which demonstrates the value of information. Note to Practitioners—We present a novel analytical framework for modeling the primary care delivery system and obtain the equilibrium patient flows under different queue-joining behaviors. This framework enables a rigorous analytical investigation of system configurations and their influence on system performance under a reasonable level of abstraction. System efficiency can be improved by taking advantage of patients’ heterogeneity in care preferences and time sensitivity. Queue information management and coordination of servers are found to be crucial in achieving the best efficiency, especially with growing flexible customers in the population. The methodology and analysis put forth in this study provide actionable insights into care delivery planners engaged in facili...
Published in: IEEE Transactions on Automation Science and Engineering ( Volume: 19, Issue: 2, April 2022)