{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T01:51:59Z","timestamp":1784512319080,"version":"3.55.0"},"reference-count":32,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T00:00:00Z","timestamp":1657065600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>Background: Operating rooms are the core of hospitals. They are a primary source of revenue and are often seen as one of the bottlenecks in the medical system. Many efforts are made to increase throughput, reduce costs, and maximize incomes, as well as optimize clinical outcomes and patient satisfaction. We trained a predictive model on the length of surgeries to improve the productivity and utility of operative rooms in general hospitals. Methods: We collected clinical and administrative data for the last 10 years from two large general public hospitals in Israel. We trained a machine learning model to give the expected length of surgery using pre-operative data. These data included diagnoses, laboratory tests, risk factors, demographics, procedures, anesthesia type, and the main surgeon\u2019s level of experience. We compared our model to a na\u00efve model that represented current practice. Findings: Our prediction model achieved better performance than the na\u00efve model and explained almost 70% of the variance in surgery durations. Interpretation: A machine learning-based model can be a useful approach for increasing operating room utilization. Among the most important factors were the type of procedures and the main surgeon\u2019s level of experience. The model enables the harmonizing of hospital productivity through wise scheduling and matching suitable teams for a variety of clinical procedures for the benefit of the individual patient and the system as a whole.<\/jats:p>","DOI":"10.3390\/bdcc6030076","type":"journal-article","created":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T09:41:10Z","timestamp":1657100470000},"page":"76","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Optimizing Operation Room Utilization\u2014A Prediction Model"],"prefix":"10.3390","volume":"6","author":[{"given":"Benyamine","family":"Abbou","sequence":"first","affiliation":[{"name":"Medical Management Department, Hillel-Yaffe Medical Center, Hadera 3810101, Israel"},{"name":"Ruth & Bruce Rappaport Faculty of Medicine, Technion\u2014Israel Institute of Technology, Haifa 3200003, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Orna","family":"Tal","sequence":"additional","affiliation":[{"name":"Medical Management Department, Shamir Medical Center (Assaf Harofeh), Be\u2019er Ya\u2019akov 7033001, Israel"},{"name":"Faculty of Management, Bar Ilan University, Ramat Gan 5290002, Israel"},{"name":"The Israeli Center for Emerging Technologies (ICET), Be\u2019er Ya\u2019akov 7033001, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1925-0320","authenticated-orcid":false,"given":"Gil","family":"Frenkel","sequence":"additional","affiliation":[{"name":"Division of Government Medical Centers, Israeli Ministry of Health, Jerusalem 9101002, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robyn","family":"Rubin","sequence":"additional","affiliation":[{"name":"Division of Government Medical Centers, Israeli Ministry of Health, Jerusalem 9101002, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7218-2558","authenticated-orcid":false,"given":"Nadav","family":"Rappoport","sequence":"additional","affiliation":[{"name":"Division of Government Medical Centers, Israeli Ministry of Health, Jerusalem 9101002, Israel"},{"name":"Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Be\u2019er Sheva 8410501, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,6]]},"reference":[{"key":"ref_1","first-page":"5341394","article-title":"Application of operatonal research techniques in operating room scheduling problems: Literature overview","volume":"2018","author":"Eren","year":"2018","journal-title":"J. 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