Scheduling outpatient appointments in a dynamic environment

TLDR

Outpatient appointment scheduling is challenged by the uncertainty of client types that will call for appointments. The study compares scheduling rules to reduce client waiting time and provider idle time. Using receptionist interviews to distinguish client service‑time characteristics, the authors built a simulation model that varies scheduling rules, unscheduled slot positions, mean service time, and the proportion of low‑standard‑deviation clients. Across 30 rule–environment combinations, the authors identified that scheduling high‑standard‑deviation clients last and tailoring slot positioning to clinic goals yields performance improvements over existing rules.

Abstract

Abstract The primary issue addressed in this research is how to schedule clients as they call for appointments, without knowing which “types” of clients will call at a later time. The main goal is to compare various scheduling rules in order to minimize the waiting time of the clients as well as the idle time of the service provider. Interviews with receptionists verified that they have knowledge regarding differences between clients' service time characteristics. This information is used both to differentiate between clients and to develop various scheduling rules for those clients. A simulation model of a dynamic medical outpatient environment is developed based on insight gained from the interviews and from prior research. Two decision variables are analyzed (“scheduling rule” and “position of appointment slots left unscheduled for potential urgent calls”) while two environmental factors are varied (“expected mean of the clients' service time”, and “expected percentage of clients with low service time standard deviation compared to those with high service time standard deviation”). This resulted in 30 combinations of decision variables, each tested within 15 combinations of environmental factors. By using multiple performance measures, it is possible to improve considerably on some of the “best” rules found in the current literature. The “best” decisions depend on the goals of the particular clinic as well as the environment it encounters. However, good or best results can be obtained in all cases if clients with large service time standard deviations are scheduled toward the end of the appointment session. The best positioning of slots left open for urgent clients is less clear cut, but options are identified for each of a number of possible clinic goals.