{"title":"改进急诊科资源规划:一个多案例研究。","authors":"Daniel Bouzon Nagem Assad, Thaís Spiegel","doi":"10.1080/20476965.2019.1680260","DOIUrl":null,"url":null,"abstract":"<p><p>Sizing and allocating health-care professionals are a critical problem in the management of emergency departments (EDs) managed by a public company in Rio de Janeiro (Brazil). An efficient ED configuration that is cost and time effective must be developed by this company for hospital managers. In this paper, the problem of health-care professional configurations in EDs is modelled to minimise the total labour cost while satisfying patient queues and waiting times as defined by the actual ED capacity and current clinical protocols. To solve this issue, mixed integer linear programming (MILP) that allocates health-care professionals and specifies the amount of professionals who must be hired is proposed. To consider the uncertainties in this environment and evaluate their impacts, a discrete-event simulation model is developed to reflect patient flow. An optimisation and simulation approach is used to search for efficiency leads for different ED configurations. These configurations change depending on the shift and the day of the week.</p>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2019-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/20476965.2019.1680260","citationCount":"9","resultStr":"{\"title\":\"Improving emergency department resource planning: a multiple case study.\",\"authors\":\"Daniel Bouzon Nagem Assad, Thaís Spiegel\",\"doi\":\"10.1080/20476965.2019.1680260\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Sizing and allocating health-care professionals are a critical problem in the management of emergency departments (EDs) managed by a public company in Rio de Janeiro (Brazil). An efficient ED configuration that is cost and time effective must be developed by this company for hospital managers. In this paper, the problem of health-care professional configurations in EDs is modelled to minimise the total labour cost while satisfying patient queues and waiting times as defined by the actual ED capacity and current clinical protocols. To solve this issue, mixed integer linear programming (MILP) that allocates health-care professionals and specifies the amount of professionals who must be hired is proposed. To consider the uncertainties in this environment and evaluate their impacts, a discrete-event simulation model is developed to reflect patient flow. An optimisation and simulation approach is used to search for efficiency leads for different ED configurations. These configurations change depending on the shift and the day of the week.</p>\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2019-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/20476965.2019.1680260\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/20476965.2019.1680260\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/20476965.2019.1680260","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Improving emergency department resource planning: a multiple case study.
Sizing and allocating health-care professionals are a critical problem in the management of emergency departments (EDs) managed by a public company in Rio de Janeiro (Brazil). An efficient ED configuration that is cost and time effective must be developed by this company for hospital managers. In this paper, the problem of health-care professional configurations in EDs is modelled to minimise the total labour cost while satisfying patient queues and waiting times as defined by the actual ED capacity and current clinical protocols. To solve this issue, mixed integer linear programming (MILP) that allocates health-care professionals and specifies the amount of professionals who must be hired is proposed. To consider the uncertainties in this environment and evaluate their impacts, a discrete-event simulation model is developed to reflect patient flow. An optimisation and simulation approach is used to search for efficiency leads for different ED configurations. These configurations change depending on the shift and the day of the week.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.