{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T08:46:35Z","timestamp":1766738795007},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685274","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T00:00:00Z","timestamp":1721779200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,24]]},"abstract":"<jats:p>The effective management of human resources in nursing fundamental to ensuring high-quality care. The necessary staffing levels can beis derived from the nursing-related health status. Our approach is based on the use of artificial intelligence (AI) and machine learning (ML) to recognize key workload-driving predictors from routine clinical data in the first step and derive recommendations for staffing levels in the second step. The study was a multi-center study with data provided by three hospitals. The SPI (Self Care Index = sum score of 10 functional\/cognitive items of the epaAC) was identified as a strong predictor of nursing workload. The SPI alone explains the variance in workload minutes with an adjusted R2 of 40% to 66%. With the addition of further predictors such as \u201cfatigue\u201d or \u201cpain intensity\u201d, the adjusted R2 can be increased by up to 17%. The resulting model can be used as a foundation for data-based personnel controlling using AI-based prediction models.<\/jats:p>","DOI":"10.3233\/shti240142","type":"book-chapter","created":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T11:02:30Z","timestamp":1721818950000},"source":"Crossref","is-referenced-by-count":2,"title":["Staff Management with AI: Predicting the Nursing Workload"],"prefix":"10.3233","author":[{"given":"Dirk","family":"Hunstein","sequence":"first","affiliation":[{"name":"CEO, ePA-CC GmbH, Wiesbaden"}]},{"given":"Madlen","family":"Fiebig","sequence":"additional","affiliation":[{"name":"Lead Unit Products & Science, ePA-CC GmbH, Wiesbaden"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Innovation in Applied Nursing Informatics"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI240142","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T11:02:31Z","timestamp":1721818951000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI240142"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,24]]},"ISBN":["9781643685274"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti240142","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,24]]}}}