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Integration of simulation and DEA to determine the most efficient patient appointment scheduling model for a specific healthcare setting

Journal Name:

  • Journal of Industrial Engineering and Management

Publication Year:

  • 2014
DOI: 
http://dx.doi.org/10.3926/jiem.1058

Key Words:

Author NameUniversity of Author
Abstract (2. Language): 
Purpose: This study is to develop a systematic approach for determining the most efficient patient appointment scheduling (PAS) model for a specific healthcare setting with its characteristics of multiple appointments requests in order to increase patients’ accessibility, improve resource utilization, and reduce operation cost. In this study, three general appointment scheduling models, centralized scheduling model (CSM), decentralized scheduling model (DSM), and hybrid scheduling model (HSM), are considered. Design/methodology/approach: This study integrates discrete event simulation and data envelopment analysis (DEA) to determine the most efficient PAS model. Simulation analysis is used to obtain the outputs of different configurations of PAS, and the DEA based on the simulation outputs is applied to select the best configuration in the presence of multiple and contrary performance measures. The best PAS configuration provides an optimal balance between patient satisfaction, schedulers’ utilization, and the cost of the scheduling system and schedulers’ training. Findings: The case study shows that in the presence of high proportion (more than 70%) of requests for multiple appointments, CSM is the best PAS model. If the proportion of requests for multiple appointments is medium (25%-50%), HSM is the best. Finally, if the proportion of requests for multiple appointments is low (less than 15%), DSM is the best. If the proportion is in the interval from 15% to 25% the selected PAS model can be either DSM or HSM based on expert idea. Similarly, if the proportion is in the interval from 50% to 70% the best PAS model can be either CSM or HSM. Originality/value: This is the first study that determines the best PAS model for a particular healthcare setting. The proposed approach can be used in a variety of healthcare settings.
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