Publication | Closed Access
Minimizing Total Cost in Scheduling Outpatient Appointments
285
Citations
0
References
1992
Year
Family MedicineEngineeringOperations ResearchPrimary CareEnvironmental FactorsMedical Clinic OutpatientsResource OptimizationOutpatient AppointmentsHealth Services ResearchCost AllocationScheduling (Computing)Integer ProgrammingQueueing SystemsScheduling AnalysisScheduling ProblemHealth Care ReimbursementScheduling (Operating Systems)Patient SafetyScheduling (Production Processes)Health Care CostScheduling RulesMedicineScheduling (Project Management)Emergency MedicineAnesthesiology
Idle times for clinic appointments are driven mainly by no‑show probability, variability of service times, and patient load per session, and selecting an optimal rule requires knowing these parameters and the relative idle‑time costs of staff versus patients. This study evaluates multiple outpatient scheduling rules to minimize a weighted sum of medical personnel and patient idle‑time costs. Using simulation across 27 combinations of the three environmental factors, the authors assess nine scheduling rules—some newly proposed—and compare their performance. The analysis yields efficient frontiers and a simple rule‑selection procedure that adapts to limited parameter knowledge, revealing that Bailey‑Welch individual‑appointment rules are surprisingly robust.
This paper considers various rules for scheduling appointments for medical clinic outpatients and investigates their ability to minimize a weighted sum of medical personnel's and patients' idle-time costs. It is shown that the idle times incurred by any given rule are affected by the following three “environmental factors” (in decreasing order of importance): the probability of no-show, the coefficient of variation of service times, and the number of patients per clinical session. Theoretically, an appropriate scheduling rule can be identified only if one knows the values of these parameters and the ratio between the medical personnel's and patients' idle-time costs. Under environments characterized by 27 different combinations of the three environmental factors, the performance of nine scheduling rules are evaluated using simulation. Some of the rules evaluated are original to this study. The results are presented in the form of “efficient frontiers,” together with a simple procedure for identifying the best scheduling rule for given environmental-parameter values. This rule-identification procedure is shown to be easily adaptable for circumstances with limited knowledge about the environmental factors; it also reveals that the simple Bailey-Welch individual-appointment rules are surprisingly robust.