O. Shylo, L. Luangkesorn, O. Prokopyev, J. Rajgopal, A. Schaefer
{"title":"Managing patient backlog in a surgical suite that uses a block-booking scheduling system","authors":"O. Shylo, L. Luangkesorn, O. Prokopyev, J. Rajgopal, A. Schaefer","doi":"10.1109/WSC.2011.6147852","DOIUrl":null,"url":null,"abstract":"Effective scheduling of elective cases in an operating room suite is a challenging task due to inherent uncertainty and competing performance metrics. In this paper, we present a simulation model for the surgical suite within the VA Pittsburgh Health Care System (VAPHS) that is used to evaluate and optimize different scheduling policies. A flexible set of probabilistic scheduling rules is evaluated and a dynamic scheduling policy is proposed as an alternative to static strategies. The dynamic scheduling policy allows us to reduce the variance in patient waiting times and backlogs. The developed simulation model is based on the data collected at the VAPHS.","PeriodicalId":246140,"journal":{"name":"Proceedings of the 2011 Winter Simulation Conference (WSC)","volume":"11 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2011 Winter Simulation Conference (WSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC.2011.6147852","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Effective scheduling of elective cases in an operating room suite is a challenging task due to inherent uncertainty and competing performance metrics. In this paper, we present a simulation model for the surgical suite within the VA Pittsburgh Health Care System (VAPHS) that is used to evaluate and optimize different scheduling policies. A flexible set of probabilistic scheduling rules is evaluated and a dynamic scheduling policy is proposed as an alternative to static strategies. The dynamic scheduling policy allows us to reduce the variance in patient waiting times and backlogs. The developed simulation model is based on the data collected at the VAPHS.