Integration of Simulation and DEA to Determine the Most Efficient Patient Appointment Scheduling Model for a Specific Clinic Setting
Abstract
This study develops a method to determine the most efficient scheduling model for
a specific clinic setting.
The appointment scheduling system assigns clinics' timeslots to incoming requests.
There are three major scheduling models: centralized scheduling model (CSM),
decentralized scheduling model (DSM) and hybrid scheduling model (HSM). In order to
schedule multiple appointments, CSM involves one scheduler, DSM involves all the
schedulers of individual clinics and HSM combines CSM and DSM.
Clinic settings are different in terms of important factors such as randomness of
appointment arrival and proportion of multiple appointments.
Scheduling systems operate inefficiently if there is not an appropriate match
between scheduling models and clinic settings to provide balance between indicators of
efficiency. A procedure is developed to determine the most efficient scheduling model by
the integrated contribution of simulation and Data Envelopment Analysis (DEA). A case
study serves as a guide to use and as proof for the validity of the developed procedure.