When outpatient appointment meets online consultation: A joint scheduling optimization framework

被引:2
|
作者
Guo, Hainan [1 ]
Xie, Yue [1 ,2 ]
Jiang, Bowen [3 ]
Tang, Jiafu [4 ]
机构
[1] Shenzhen Univ, Coll Management, Shenzhen 518060, Peoples R China
[2] Southwestern Univ Finance & Econ, Sch Business Adm, Chengdu 611130, Peoples R China
[3] Northeastern Univ, Sch Business Adm, 3-11 Wenhua Rd, Shenyang 110169, Peoples R China
[4] Dongbei Univ Finance & Econ, Coll Management Sci & Engn, Dalian 116025, Peoples R China
基金
中国国家自然科学基金;
关键词
Appointment scheduling; Online consultation service; Healthcare; HEALTH-CARE; MULTI-PRIORITY; PATIENT; SYSTEMS; SHOWS;
D O I
10.1016/j.omega.2024.103101
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
While the provision of Online Consultation Services (OCS) has brought convenience to patients, the original offline outpatient workflow may struggle to maintain efficiency. Hospital managers ' concerns lie on how to reconcile the operations of offline service with the provision of OCS and what are the latent impacts of OCS on the operational performances of healthcare system. The outpatient appointment scheduling is a crucial part of the workflow decision that affects both quality of offline services and the fragmented idle time that doctors can reply to their Follow-up patients (FUP) during working hours. To smooth the fluctuations in workload of OCS, we introduce a novel decision variable - the recommended maximum number of FUP that a doctor should serve during overtime hours (FUP-MN) - and propose an inter-day service shifting strategy that any requests for OCS exceeding the FUP-MN will be deferred to be served in the fragmented idle time of the next session. We formulate a stochastic programming model to search for the optimal combination of the appointment schedule and FUPMN. Propositions are conducted to demonstrate the model is valid not only in coordinating the dual demand for online and offline services, but also in restricting the potential overflow of OCS requests. We provide a general solution approach and also develop a heuristic algorithm to quickly obtain optimal workflows at different OCS demand levels. The numerical experimental results indicate that an appropriate introduction of OCS can give the healthcare system a strong ability to resist the adverse effects of uncertainty.
引用
收藏
页数:16
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