Appointment Scheduling Considering Outpatient Unpunctuality Under Telemedicine Services

সংরক্ষণ করুন:
গ্রন্থ-পঞ্জীর বিবরন
প্রকাশিত:Mathematics vol. 13, no. 16 (2025), p. 2591-2608
প্রধান লেখক: Chen, Wei
অন্যান্য লেখক: Chen, Liang, Shen Xiaoxiao, Zhang, Yutao, Wang Xiulai
প্রকাশিত:
MDPI AG
বিষয়গুলি:
অনলাইন ব্যবহার করুন:Citation/Abstract
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সার সংক্ষেপ:Patient unpunctuality substantially complicates appointment scheduling in integrated telemedicine–traditional outpatient systems. The current research frequently ignores behavioral distinctions between telemedicine patients and outpatients, while neglecting to measure the intangible burden on physicians from service mode switches. To address these gaps, this study incorporates patient heterogeneity and introduces two novel cost metrics. Specifically, we implement penalties for service-mode switching and penalties for consecutive telemedicine sessions. We develop a Stochastic Mixed-Integer Programming (SMIP) model. This stochastic model is transformed into a deterministic Mixed-Integer Linear Programming (MILP) formulation via Sample Average Approximation (SAA). Linearization techniques enhance computational efficiency. In numerical experiments, the dual-penalty model yields balanced schedules with moderate patient mix, reducing physician overtime by 62.5% and service mode switches by 55% compared to baseline approaches. Sensitivity analysis confirms that narrowing outpatient unpunctuality ranges significantly reduces patient waiting and overtime, while raising telemedicine patient proportions bolsters system stability at the cost of increased physician idle time. These insights offer actionable guidance for healthcare institutions managing integrated online–offline services.
আইএসএসএন:2227-7390
ডিওআই:10.3390/math13162591
সম্পদ:Engineering Database