{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,13]],"date-time":"2026-11-13T04:15:18Z","timestamp":1794543318703,"version":"4.9.1"},"reference-count":46,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"3","content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:sec>\n                    <jats:title>Summary.<\/jats:title>\n                    <jats:p>Since their early development in the 1980s, Simulated Allocation Models (SAMs) have helped policymakers forecast the impact of proposed allocation policy changes on patient outcomes before implementation. In the United States, models like the Kidney-Pancreas Simulated Allocation Model, Liver Simulated Allocation Model, and Thoracic Simulated Allocation Model have been instrumental in shaping organ allocation policies. Analogous models have emerged globally, including the ETKidney and Eurotransplant Liver Allocation System simulators for the Eurotransplant region, to address country and region-specific allocation challenges. This review categorizes and compares SAMs based on their core assumptions, data, and modeling approaches. We highlight challenges in model validation, the use of synthetic data, and model transparency. While simplifying assumptions are often necessary because of limited data, their influence on results should be clearly communicated to ensure policymakers can interpret model predictions accurately. Furthermore, model validation using both retrospective and prospective data is essential to assess performance under evolving policies. Greater transparency through open-source models, detailed reporting of assumptions, and validation efforts can enhance collaboration, reproducibility, and confidence in transplant research. By providing a global perspective on SAMs, this review aims to inform future research and policy development, promoting evidence-based policy development in organ transplantation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1097\/tp.0000000000005595","type":"journal-article","created":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T05:00:18Z","timestamp":1770181218000},"page":"e573-e582","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":2,"title":["A Global Review of Organ Allocation Simulation Models"],"prefix":"10.1097","volume":"110","author":[{"given":"Roby","family":"Cremers","sequence":"first","affiliation":[{"name":"Econometric Institute, Erasmus University, Rotterdam, the Netherlands."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Darren","family":"Stewart","sequence":"additional","affiliation":[{"name":"Department of Surgery, NYU Grossman School of Medicine, New York, NY."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Allan B.","family":"Massie","sequence":"additional","affiliation":[{"name":"Department of Surgery, NYU Grossman School of Medicine, New York, NY."},{"name":"Department of Population Health, NYU Grossman School of Medicine, New York, NY."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dorry L.","family":"Segev","sequence":"additional","affiliation":[{"name":"Department of Surgery, NYU Grossman School of Medicine, New York, NY."},{"name":"Department of Population Health, NYU Grossman School of Medicine, New York, NY."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sommer E.","family":"Gentry","sequence":"additional","affiliation":[{"name":"Department of Surgery, NYU Grossman School of Medicine, New York, NY."},{"name":"Department of Population Health, NYU Grossman School of Medicine, New York, NY."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michal A.","family":"Mankowski","sequence":"additional","affiliation":[{"name":"Department of Surgery, NYU Grossman School of Medicine, New York, NY."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,2,4]]},"reference":[{"key":"R1-20260217","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1080\/01621459.1949.10483310","article-title":"The Monte Carlo method.","volume":"44","author":"Metropolis","year":"1949","journal-title":"J Am Stat Assoc"},{"key":"R2-20260217","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1057\/jos.2008.13","article-title":"The automatic programming of simulations.","volume":"2","author":"Tocher","year":"2008","journal-title":"J Simul"},{"key":"R4-20260217","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/S0377-2217(97)00240-3","article-title":"Capacity planning for intensive care units.","volume":"105","author":"Ridge","year":"1998","journal-title":"Eur J Oper 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