This study evaluates patient classification for scheduling and sequencing appointments for patients differentiated by their mean and standard deviation of service times, no-show, and walk-in probabilities. Alternative appointment systems are tested through simulation using a universal Dome rule and some of the best traditional appointment rules in the literature. Our findings show that the universal Dome rule performs better in terms of reducing the total cost of patient’s waiting time, doctor’s idle time, and overtime, and its performance improves further with the right sequencing of patient groups. Although it is a challenge to find the best sequence, we propose a heuristic rule that successfully identifies the best sequence with an accuracy level of 98% for the universal Dome rule. Sensitivity analyses further confirm that our findings are valid even when assumptions on patient punctuality and service time distributions are relaxed. To facilitate the use of our proposed appointment system, an open source online tool is developed to support practitioners in designing their appointment schedules for real clinics.
healthcare, appointment scheduling and sequencing, simulation
Medicine and Health Sciences | Operations and Supply Chain Management
INFORMS Service Science
TUGBA, Cayirli and YANG, Kum Khiong.
A Universal Appointment Rule with Patient Classification for Service Times, No-Shows and Walk-Ins. (2014). INFORMS Service Science. 6, (4), 274-295. Research Collection Lee Kong Chian School Of Business.
Available at: http://ink.library.smu.edu.sg/lkcsb_research/4187
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