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Online databases were searched in June 2020 to identify all published studies in this area. Data were extracted based on the CHARMS checklist, and studies were evaluated based on predictor variables, validation, performance in validation, risk of bias, and applicability using the Prediction Model Risk of Bias Assessment Tool (PROBAST) tool.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The final sample contained 28 articles with 35 models for evaluation. Models focused on surgical (22), medical (5), or both (8) populations. Eighteen models were internally validated, 10 were externally validated, and 7 models underwent both types. Model performance varied within and across populations. Most models used retrospective data, the median number of predictors was 8.5, and most models demonstrated risk of bias.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion and Conclusion<\/jats:title>\n                  <jats:p>Prediction modeling studies for postacute care destinations are becoming more prolific in the literature, but model development and validation strategies are inconsistent, and performance is variable. Most models are developed using regression, but machine learning methods are increasing in frequency. Future studies should ensure the rigorous variable selection and follow TRIPOD guidelines. Only 14% of the models have been tested or implemented beyond original studies, so translation into practice requires further investigation.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocab197","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T11:36:27Z","timestamp":1631100987000},"page":"176-186","source":"Crossref","is-referenced-by-count":10,"title":["Systematic review of prediction models for postacute care destination decision-making"],"prefix":"10.1093","volume":"29","author":[{"given":"Erin E","family":"Kennedy","sequence":"first","affiliation":[{"name":"NewCourtland Center for Transitions and Health, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA"},{"name":"Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA"}]},{"given":"Kathryn H","family":"Bowles","sequence":"additional","affiliation":[{"name":"NewCourtland Center for Transitions and 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