基于随机优化的门诊患者调度研究

项目名称： 基于随机优化的门诊患者调度研究

项目编号： No.71471113

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 管理科学

项目作者： 耿娜

作者单位： 上海交通大学

项目金额： 62万元

中文摘要： 经过近三十年的医疗改革，中国医疗系统取得了一定的成就，但传统的看病难、看病贵问题一直未能得到有效解决。本项目针对看病难问题突出的门诊服务，从以下两个时间维度研究患者调度：以日或周为单位的提前调度和以小时或分钟为单位的预约调度，以减少患者从进行预约到接受医疗服务之间的等待时间。本项目基于随机规划、马尔科夫决策支持等随机优化方法，针对不同门诊服务的特点，即单次、重入或组合的医疗服务，考虑患者的可忍耐等待时间，未来可能到达的患者信息，组合服务的不确定性，进行患者提前调度研究；考虑医患双方的不确定因素，首诊、复诊患者不同的服务时间，患者所需的组合医疗服务，进行患者预约调度研究；最后结合上海瑞金医院、上海市第一人民医院，无锡、常州等多地医院的实际情况，进行多样化的案例研究。本项目将丰富完善医疗服务中的患者调度研究，具有重要的理论和应用价值。

中文关键词： 门诊患者；提前调度；预约调度；马尔科夫决策支持；随机规划

英文摘要： After about three decades' healthcare reform, medical system of China has been greatly improved. However, the traditional problem of the difficulty and high cost of getting medical treatment has not been resolved now. To deal with the difficulty problem, this project aims at developing new models and methodologies for the outpatient scheduling. According to the time horizon, outpatient scheduling is divided into advanced scheduling (in terms of weeks or days) and appointment scheduling (in terms of hours or minutes). The features of different medical services, i.e., single, multi-reentrant, and combined diagnostic or treatments, are considered. Based on Markov decision process, stochastic programming, and other stochastic optimization methods, this project will deal with the following two issues: 1) advanced scheduling by considering the waiting time targets of outpatients, future patients' arrival, and uncertainties of combined medical resources; 2) appointment scheduling by considering uncertainties from both patients and physicians, different service time of new and reentrant patients, and combination of different medical services. Finally, case study will be performed by using the data from Ruijin Hospital, First Hospital of Shanghai, and other hospitals from Wuxi and Changzhou. This project will enrich the patient scheduling, which is important for both theory and application.

英文关键词： Outpatient;Advanced Scheduling;Appointment Scheduling;Markov Decision Process;Stochastic Programming