A decision support system for real-time and dynamic scheduling of multiple patient classifications in ambulatory care services

Abstract

We propose a methodology to provide real-time assistance for outpatient scheduling, involving multiple patient types. Schedulers are shown how each prospective placement would impact the day's operational performance for patients and providers. Rooted in prior literature and analytical findings, the information provided to schedulers about vacant slots is based on the probabilities that the calling patient, the already-existing appointments, and the session-end time will be unduly delayed. The information is dynamically updated after every new booking; calculations are driven by historical consultation times and no-show data, and a simulation tool that implements the underlying analytical methodology. Our findings lead to practical guidelines for constructing templates that provide allowances for different service time lengths and variability, no-show rates, and provider-driven performance targets for patient delays and providers' overtime. Extensions to OR scheduling are viable as avoiding session overtime and procedures' completion time delays involve similar considerations.