{"title":"Studying nurse workload and patient waiting time in a hematology-oncology clinic with discrete event simulation","authors":"C. Baril, V. Gascon, Jonathan Miller, C. Bounhol","doi":"10.1080/19488300.2016.1226212","DOIUrl":null,"url":null,"abstract":"ABSTRACT Our study is performed in a hematology-oncology clinic in Québec. This clinic experienced a 20% increase for hematology treatments and a 131% increase for oncology treatments. Clinic managers and personnel felt that this increase led to higher patient waiting time and personnel workload. Clinic managers decided to examine the possibility of adding resources to alleviate nurse workload. Patient trajectories and lead times, appointment scheduling and nurse workload are analyzed with a discrete-event simulation model. It is shown that patient waiting time is not too long. A nurse overload problem is observed with a nurse occupancy rate of 86.98% in the morning and 64.48% in the afternoon. New schedule appointments taking into account nurse capacity are proposed. These result in a decrease of the difference in nurse occupancy rates in the morning and in the afternoon.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"6 1","pages":"223 - 234"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2016.1226212","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IIE transactions on healthcare systems engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/19488300.2016.1226212","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
ABSTRACT Our study is performed in a hematology-oncology clinic in Québec. This clinic experienced a 20% increase for hematology treatments and a 131% increase for oncology treatments. Clinic managers and personnel felt that this increase led to higher patient waiting time and personnel workload. Clinic managers decided to examine the possibility of adding resources to alleviate nurse workload. Patient trajectories and lead times, appointment scheduling and nurse workload are analyzed with a discrete-event simulation model. It is shown that patient waiting time is not too long. A nurse overload problem is observed with a nurse occupancy rate of 86.98% in the morning and 64.48% in the afternoon. New schedule appointments taking into account nurse capacity are proposed. These result in a decrease of the difference in nurse occupancy rates in the morning and in the afternoon.