{"title":"急诊科病人流程设计","authors":"Y. Marmor, B. Golany, S. Israelit, A. Mandelbaum","doi":"10.1080/19488300.2012.736118","DOIUrl":null,"url":null,"abstract":"Emergency Department (ED) managers can choose from several operational models, for example, Triage or Fast-Track. The following questions thus naturally arise: why does a hospital choose to work with its particular operational model rather than another? Or what is the best model to operate under? More specifically, how to fit an operational model to an ED's uncontrollable (environmental) parameters? To address such questions, we develop a methodology for ED Design (EDD): we apply it to data collected over a period of two to four years from eight hospitals, of various sizes and deploying various ED operational models. (To cover all size-model combinations, we enrich our data via accurate ED simulation.) The EDD methodology first feeds the data into a Data Envelopment Analysis (DEA) program, which determines the relative efficiency of each month of the different operational models of each hospital. Then, after taking into account the individual hospitals effect, we identify the operational model that is dominant under each set of uncontrollable parameters. We discovered that different operational models dominate others over different combinations of uncontrollable parameters. For example, a hospital catering to an aging population is best served by a fast-track operational model.","PeriodicalId":89563,"journal":{"name":"IIE transactions on healthcare systems engineering","volume":"2 1","pages":"233 - 247"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19488300.2012.736118","citationCount":"31","resultStr":"{\"title\":\"Designing patient flow in emergency departments\",\"authors\":\"Y. Marmor, B. Golany, S. Israelit, A. Mandelbaum\",\"doi\":\"10.1080/19488300.2012.736118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Emergency Department (ED) managers can choose from several operational models, for example, Triage or Fast-Track. The following questions thus naturally arise: why does a hospital choose to work with its particular operational model rather than another? Or what is the best model to operate under? More specifically, how to fit an operational model to an ED's uncontrollable (environmental) parameters? To address such questions, we develop a methodology for ED Design (EDD): we apply it to data collected over a period of two to four years from eight hospitals, of various sizes and deploying various ED operational models. (To cover all size-model combinations, we enrich our data via accurate ED simulation.) The EDD methodology first feeds the data into a Data Envelopment Analysis (DEA) program, which determines the relative efficiency of each month of the different operational models of each hospital. Then, after taking into account the individual hospitals effect, we identify the operational model that is dominant under each set of uncontrollable parameters. We discovered that different operational models dominate others over different combinations of uncontrollable parameters. For example, a hospital catering to an aging population is best served by a fast-track operational model.\",\"PeriodicalId\":89563,\"journal\":{\"name\":\"IIE transactions on healthcare systems engineering\",\"volume\":\"2 1\",\"pages\":\"233 - 247\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/19488300.2012.736118\",\"citationCount\":\"31\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IIE transactions on healthcare systems engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/19488300.2012.736118\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IIE transactions on healthcare systems engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/19488300.2012.736118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Emergency Department (ED) managers can choose from several operational models, for example, Triage or Fast-Track. The following questions thus naturally arise: why does a hospital choose to work with its particular operational model rather than another? Or what is the best model to operate under? More specifically, how to fit an operational model to an ED's uncontrollable (environmental) parameters? To address such questions, we develop a methodology for ED Design (EDD): we apply it to data collected over a period of two to four years from eight hospitals, of various sizes and deploying various ED operational models. (To cover all size-model combinations, we enrich our data via accurate ED simulation.) The EDD methodology first feeds the data into a Data Envelopment Analysis (DEA) program, which determines the relative efficiency of each month of the different operational models of each hospital. Then, after taking into account the individual hospitals effect, we identify the operational model that is dominant under each set of uncontrollable parameters. We discovered that different operational models dominate others over different combinations of uncontrollable parameters. For example, a hospital catering to an aging population is best served by a fast-track operational model.