This paper provides a comprehensive survey of research on appointment scheduling in outpatient services. Effective scheduling systems have the goal of matching demand with capacity so that resources are better utilized and patient waiting times are minimized. Our goal is to present general problem formulation and modeling considerations, and to provide taxonomy of methodologies used in previous literature. Current literature fails to develop generally applicable guidelines to design appointment systems, as most studies have suggested highly situation‐specific solutions. We identify future research directions that provide opportunities to expand existing knowledge and close the gap between theory and practice.

The current climate in the health care industry demands efficiency and patient satisfaction in medical care delivery. These two demands intersect in scheduling of ambulatory care visits. This paper uses patient and doctor-related measures to assess ambulatory care performance and investigates the interactions among appointment system elements and patient panel characteristics. Analysis methodology involves simulation modeling of clinic sessions where empirical data forms the basis of model design and assumptions. Results indicate that patient sequencing has a greater effect on ambulatory care performance than the choice of an appointment rule, and that panel characteristics such as walk-ins, no-shows, punctuality and overall session volume, influence the effectiveness of appointment systems.

T his paper investigates two approaches to patient classification: using patient classification only for sequencing patient appointments at the time of booking and using patient classification for both sequencing and appointment interval adjustment. In the latter approach, appointment intervals are adjusted to match the consultation time characteristics of different patient classes. Our simulation results indicate that new appointment systems that utilize interval adjustment for patient class are successful in improving doctors' idle time, doctors' overtime and patients' waiting times without any trade-offs. Best performing appointment systems are identified for different clinic environments characterized by walk-ins, no-shows, the percentage of new patients, and the ratio of the mean consultation time of new patients to the mean consultation time of return patients. As a result, practical guidelines are developed for managers who are responsible for designing appointment systems.

This study introduces a universal “Dome” appointment rule that can be parameterized through a planning constant for different clinics characterized by the environmental factors—no‐shows, walk‐ins, number of appointments per session, variability of service times, and cost of doctor's time to patients’ time. Simulation and nonlinear regression are used to derive an equation to predict the planning constant as a function of the environmental factors. We also introduce an adjustment procedure for appointment systems to explicitly minimize the disruptive effects of no‐shows and walk‐ins. The procedure adjusts the mean and standard deviation of service times based on the expected probabilities of no‐shows and walk‐ins for a given target number of patients to be served, and it is thus relevant for any appointment rule that uses the mean and standard deviation of service times to construct an appointment schedule. The results show that our Dome rule with the adjustment procedure performs better than the traditional rules in the literature, with a lower total system cost calculated as a weighted sum of patients’ waiting time, doctor's idle time, and doctor's overtime. An open‐source decision‐support tool is also provided so that healthcare managers can easily develop appointment schedules for their clinical environment.

Due to copyright restrictions, the access to the full text of this article is only available via subscription.This study investigates appointment systems (AS), as combinations of access rules and appointment-scheduling rules, explicitly designed for dealing with walk-in seasonality. In terms of 'access rules', strategies are tested for adjusting capacity through intra-week, or monthly seasonality of walk-ins, or their combined effects. In terms of 'appointment rules', strategies are tested to determine which particular slots to double-book or leave open in cases where seasonal walk-in rates exceed or fall short of the overall yearly rate. In that regard, this study integrates capacity and appointment decisions, which are usually addressed in an isolated manner in previous studies. Simulation optimization is used to derive heuristic solutions to the appointment-scheduling problem, and the findings are compared in terms of in-clinic measures of patient wait time, physician idle time and overtime. The goal is to provide practical guidelines for healthcare practitioners on how to best design their AS when seasonal walk-ins exist.TÜBİTA