{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T18:39:48Z","timestamp":1792435188868,"version":"4.5.0"},"reference-count":46,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"10","content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"abstract":"<jats:sec>\n                    <jats:title\/>\n                    <jats:p>\n                      <jats:list list-type=\"plain\">\n                        <jats:list-item>\n                          <jats:p>Technical performance alone does not establish clinical readiness; strong accuracy or discrimination does not demonstrate that an artificial intelligence (AI) tool will generalize, improve clinical care, or remain safe after deployment.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Existing AI frameworks provide important guidance for reporting, risk of bias, model evaluation, and clinical trials, but they do not provide a single longitudinal stage describing a technology's progression from development through monitored clinical deployment.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>We propose the Orthopaedic Surgery Clinical AI Readiness (OSCAR) scale as a 6-stage conceptual framework spanning model development, internal and external validation, early clinical evaluation, comparative clinical validation, and monitored deployment.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Illustrative applications of OSCAR demonstrate how technically strong models may remain at stage 1, external validation advances a tool to stage 2, live workflow evaluation represents stage 3, and comparative clinical evidence is required for stage 4.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>OSCAR is intended to complement, not replace, established reporting and risk-of-bias standards. The framework remains unvalidated and requires stakeholder consensus, explicit decision criteria, inter-rater reliability testing, and prospective evaluation.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.2106\/jbjs.rvw.26.00182","type":"journal-article","created":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T18:00:23Z","timestamp":1792432823000},"update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["From Accuracy to Adoption: A Clinical Readiness Framework for Artificial Intelligence in Orthopaedic Surgery (OSCAR)"],"prefix":"10.2106","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-8211-3162","authenticated-orcid":false,"given":"Audrey R.","family":"Byrne","sequence":"first","affiliation":[{"name":"Department of Orthopedic Surgery, Columbia University Irving Medical Center\/NewYork-Presbyterian Hospital, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4574-8966","authenticated-orcid":false,"given":"Nana O.","family":"Sarpong","sequence":"additional","affiliation":[{"name":"Department of Orthopedic Surgery, Columbia University Irving Medical Center\/NewYork-Presbyterian Hospital, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,10]]},"reference":[{"issue":"7","key":"r1-20261019","doi-asserted-by":"crossref","first-page":"e70260","DOI":"10.1002\/mco2.70260","article-title":"Artificial intelligence in orthopedic surgery: current applications, challenges, and future directions","volume":"6","author":"Han","year":"2025","journal-title":"MedComm (2020)"},{"issue":"1","key":"r2-20261019","doi-asserted-by":"crossref","first-page":"10225536261424038","DOI":"10.1177\/10225536261424038","article-title":"Big data 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