{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T01:10:07Z","timestamp":1789953007755,"version":"4.0.1"},"reference-count":49,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2017,6,29]],"date-time":"2017-06-29T00:00:00Z","timestamp":1498694400000},"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":["Med Decis Making"],"published-print":{"date-parts":[[2018,2]]},"abstract":"<jats:p>Background. Hospitalized patients are assigned to available staffed beds based on patient acuity and services required. In hospitals with double-occupancy rooms, patients must be additionally matched by gender. Patients with methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant Enterococcus (VRE) must be bedded in single-occupancy rooms or cohorted with other patients with similar MRSA\/VRE flags. Methods. We developed a discrete event simulation (DES) model of patient flow through an acute care hospital. Patients are matched to beds based on acuity, service, gender, and known MRSA\/VRE colonization. Outcomes included time to bed arrival, length of stay, patient-bed acuity mismatches, occupancy, idle beds, acuity-related transfers, rooms with discordant MRSA\/VRE colonization, and transmission due to discordant colonization. Results. Observed outcomes were well-approximated by model-generated outcomes for time-to-bed arrival (6.7 v. 6.2 to 6.5 h) and length of stay (3.3 v. 2.9 to 3.0 days), with overlapping 90% coverage intervals. Patient-bed acuity mismatches, where patient acuity exceeded bed acuity and where patient acuity was lower than bed acuity, ranged from 0.6 to 0.9 and 8.6 to 11.1 mismatches per h, respectively. Values for observed occupancy, total idle beds, and acuity-related transfers compared favorably to model-predicted values (91% v. 86% to 87% occupancy, 15.1 v. 14.3 to 15.7 total idle beds, and 27.2 v. 22.6 to 23.7 transfers). Rooms with discordant colonization status and transmission due to discordance were modeled without an observed value for comparison. One-way and multi-way sensitivity analyses were performed for idle beds and rooms with discordant colonization. Conclusions. We developed and validated a DES model of patient flow incorporating MRSA\/VRE flags. The model allowed for quantification of the substantial impact of MRSA\/VRE flags on hospital efficiency and potentially avoidable nosocomial transmission.<\/jats:p>","DOI":"10.1177\/0272989x17713474","type":"journal-article","created":{"date-parts":[[2017,7,7]],"date-time":"2017-07-07T10:13:05Z","timestamp":1499422385000},"page":"246-261","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":10,"title":["A Discrete Event Simulation Model of Patient Flow in a General Hospital Incorporating Infection Control Policy for Methicillin-Resistant\n                    <i>Staphylococcus Aureus<\/i>\n                    (MRSA) and Vancomycin-Resistant\n                    <i>Enterococcus<\/i>\n                    (VRE)"],"prefix":"10.1177","volume":"38","author":[{"given":"Erica S.","family":"Shenoy","sequence":"first","affiliation":[{"name":"Infection Control Unit, Massachusetts General Hospital, Boston, MA, USA (ESS, DCH)"},{"name":"Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA (ESS, RPW, DCH)"},{"name":"Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA (ESS, ER, TH, RPW)"},{"name":"Harvard Medical School, Boston, MA, USA (ESS, RPW, DCH)"},{"name":"Massachusetts General Hospital Biostatistics Center, Boston, MA, USA (HL)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hang","family":"Lee","sequence":"additional","affiliation":[{"name":"Infection Control Unit, Massachusetts General Hospital, Boston, MA, USA (ESS, DCH)"},{"name":"Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA (ESS, RPW, DCH)"},{"name":"Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA (ESS, ER, TH, RPW)"},{"name":"Harvard Medical School, Boston, MA, USA (ESS, RPW, DCH)"},{"name":"Massachusetts General Hospital Biostatistics Center, Boston, MA, USA (HL)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erin E.","family":"Ryan","sequence":"additional","affiliation":[{"name":"Infection Control Unit, Massachusetts General Hospital, Boston, MA, USA (ESS, DCH)"},{"name":"Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA (ESS, RPW, DCH)"},{"name":"Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA (ESS, ER, TH, RPW)"},{"name":"Harvard Medical School, Boston, MA, USA (ESS, RPW, DCH)"},{"name":"Massachusetts General Hospital Biostatistics Center, Boston, MA, USA (HL)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taige","family":"Hou","sequence":"additional","affiliation":[{"name":"Infection Control Unit, Massachusetts General Hospital, Boston, MA, USA (ESS, DCH)"},{"name":"Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA (ESS, RPW, 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