EconPapers    
Economics at your fingertips  
 

Outpatient appointment scheduling problem considering patient selection behavior: data modeling and simulation optimization

Xuanzhu Fan (), Jiafu Tang (), Chongjun Yan (), Hainan Guo () and Zhongfa Cao ()
Additional contact information
Xuanzhu Fan: Dongbei University of Finance and Economics
Jiafu Tang: Dongbei University of Finance and Economics
Chongjun Yan: Dongbei University of Finance and Economics
Hainan Guo: Shenzhen University
Zhongfa Cao: Dalian Dermatosis Hospital

Journal of Combinatorial Optimization, No 0, 23 pages

Abstract: Abstract In medical outpatient services, due to patients’ imbalanced selection for doctors of different levels and for different visiting periods, inefficiency of resource utilization and dissatisfaction of patients have become the main problems faced by hospital managers. For the first time, this research has considered patients’ preference between high-ranking professional titles of general doctor and expert doctor. Through analyzing real data of the outpatient clinic at Dalian City Dermatology Hospital, the behavioral pattern of patients’ patience limit adjusted with expected waiting time was obtained. This research also established a data-driven discrete event simulation model that takes into account walk-in patients’ time preferences, appointment patients’ no-shows and cancellations, and considers complex patient flow caused by unbalanced selection of doctor resources and patience limit of waiting time. To optimize scheduling for appointment patients with two types of doctors, this research put forward a simulation optimization framework that maximized hospital benefit and minimized patients’ dissatisfaction. At the same time, simulation budget allocation based on multi-objective optimization and genetic algorithm were combined to obtain the approximate Pareto joint capacity plan of multi-servers and a patient scheduling scheme. The simulation model was validated through a case study based on real data of outpatient service for the whole year, and the proposed optimization method can comprehensively improve performance of outpatient service scheduling system. The simulation optimization framework can provide an effective scheduling scheme for all multi-server service systems involving consumer selection and impatient behavior.

Keywords: Appointment scheduling; Simulation optimization; Data-driven; Patient selection behavior (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10878-019-00487-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jcomop:v::y::i::d:10.1007_s10878-019-00487-x

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/10878

DOI: 10.1007/s10878-019-00487-x

Access Statistics for this article

Journal of Combinatorial Optimization is currently edited by Thai, My T.

More articles in Journal of Combinatorial Optimization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:jcomop:v::y::i::d:10.1007_s10878-019-00487-x