{"title":"病人未到的专科诊所超额预约:排队方法","authors":"Zhenghao Fan, Xiaolei Xie, Reynerio Sanchez, Xiang Zhong","doi":"10.1109/COASE.2018.8560573","DOIUrl":null,"url":null,"abstract":"Specialty clinics typically have a critical issue with patient adherence to their appointments, and suffer a huge backlog of patients who need to be seen. The goal of this study is to enhance care providers' productivity and patient access to care through effective clinic appointment scheduling. We introduce a novel discrete-time bulk service queue to model the backlog dynamics, and consider different overbooking strategies to reduce backlog at a minimum risk of working overtime. The modeling framework provides a tool for scheduling template design, and the insights obtained from the models can support clinic operation decision-making, ultimately improving the operational efficiency of clinics, and patient outcomes and satisfaction.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"68 1","pages":"396-401"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Overbooking for Specialty Clinics with Patient No-Shows: A Queueing Approach\",\"authors\":\"Zhenghao Fan, Xiaolei Xie, Reynerio Sanchez, Xiang Zhong\",\"doi\":\"10.1109/COASE.2018.8560573\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Specialty clinics typically have a critical issue with patient adherence to their appointments, and suffer a huge backlog of patients who need to be seen. The goal of this study is to enhance care providers' productivity and patient access to care through effective clinic appointment scheduling. We introduce a novel discrete-time bulk service queue to model the backlog dynamics, and consider different overbooking strategies to reduce backlog at a minimum risk of working overtime. The modeling framework provides a tool for scheduling template design, and the insights obtained from the models can support clinic operation decision-making, ultimately improving the operational efficiency of clinics, and patient outcomes and satisfaction.\",\"PeriodicalId\":6518,\"journal\":{\"name\":\"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)\",\"volume\":\"68 1\",\"pages\":\"396-401\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COASE.2018.8560573\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2018.8560573","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Overbooking for Specialty Clinics with Patient No-Shows: A Queueing Approach
Specialty clinics typically have a critical issue with patient adherence to their appointments, and suffer a huge backlog of patients who need to be seen. The goal of this study is to enhance care providers' productivity and patient access to care through effective clinic appointment scheduling. We introduce a novel discrete-time bulk service queue to model the backlog dynamics, and consider different overbooking strategies to reduce backlog at a minimum risk of working overtime. The modeling framework provides a tool for scheduling template design, and the insights obtained from the models can support clinic operation decision-making, ultimately improving the operational efficiency of clinics, and patient outcomes and satisfaction.