{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T13:34:10Z","timestamp":1781530450070,"version":"3.54.1"},"reference-count":15,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2016,2,29]],"date-time":"2016-02-29T00:00:00Z","timestamp":1456704000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Health Informatics J"],"published-print":{"date-parts":[[2017,6]]},"abstract":"<jats:p>We demonstrate how to develop a simulation tool to help healthcare managers and administrators predict and plan for staffing needs in a hospital neonatal intensive care unit using administrative data. We developed a discrete event simulation model of nursing staff needed in a neonatal intensive care unit and then validated the model against historical data. The process flow was translated into a discrete event simulation model. Results demonstrated that the model can be used to give a respectable estimate of annual admissions, transfers, and deaths based upon two different staffing levels. The discrete event simulation tool model can provide healthcare managers and administrators with (1) a valid method of modeling patient mix, patient acuity, staffing needs, and costs in the present state and (2) a forecast of how changes in a unit\u2019s staffing, referral patterns, or patient mix would affect a unit in a future state.<\/jats:p>","DOI":"10.1177\/1460458216628314","type":"journal-article","created":{"date-parts":[[2016,2,29]],"date-time":"2016-02-29T21:23:34Z","timestamp":1456781014000},"page":"124-133","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":27,"title":["A discrete event simulation tool to support and predict hospital and clinic staffing"],"prefix":"10.1177","volume":"23","author":[{"given":"Christopher M","family":"DeRienzo","sequence":"first","affiliation":[{"name":"Mission Health System, USA"},{"name":"Duke University Hospital, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan J","family":"Shaw","sequence":"additional","affiliation":[{"name":"Duke University School of Nursing, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phillip","family":"Meanor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emily","family":"Lada","sequence":"additional","affiliation":[{"name":"SAS, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey","family":"Ferranti","sequence":"additional","affiliation":[{"name":"Duke University Hospital, USA"},{"name":"Duke Health Technology Solutions, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Tanaka","sequence":"additional","affiliation":[{"name":"Duke University Hospital, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2016,2,29]]},"reference":[{"key":"bibr1-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMsa1001025"},{"key":"bibr2-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1177\/1527154406291936"},{"key":"bibr3-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1097\/00005110-200501000-00014"},{"key":"bibr4-1460458216628314","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-153-8-201010190-00274"},{"key":"bibr5-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1001\/archsurg.142.4.329"},{"key":"bibr6-1460458216628314","doi-asserted-by":"publisher","DOI":"10.5430\/jha.v4n2p15"},{"key":"bibr7-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1176\/ps.49.8.1049"},{"key":"bibr8-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1542\/peds.2009-2959"},{"key":"bibr9-1460458216628314","volume-title":"SAS simulation studio 13.1: user\u2019s guide","author":"SAS Institute, Inc","year":"2013"},{"key":"bibr10-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1001\/jama.1988.03410240087037"},{"key":"bibr11-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1007\/s10729-006-6278-6"},{"key":"bibr12-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-009-9259-8"},{"key":"bibr13-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1542\/peds.2009-0810"},{"issue":"2","key":"bibr14-1460458216628314","first-page":"67","volume":"58","author":"Mark W","year":"2005","journal-title":"Prof Inf"},{"key":"bibr15-1460458216628314","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMsa012247"}],"container-title":["Health Informatics Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/1460458216628314","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/1460458216628314","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/1460458216628314","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T22:30:08Z","timestamp":1777501808000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/1460458216628314"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,2,29]]},"references-count":15,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2017,6]]}},"alternative-id":["10.1177\/1460458216628314"],"URL":"https:\/\/doi.org\/10.1177\/1460458216628314","relation":{},"ISSN":["1460-4582","1741-2811"],"issn-type":[{"value":"1460-4582","type":"print"},{"value":"1741-2811","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,2,29]]}}}