{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T14:42:13Z","timestamp":1787755333497,"version":"build-2784847793"},"reference-count":11,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"4","content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,2,18]]},"abstract":"<jats:p>Good judgment remains fundamental to clinical decision-making, and yet it is increasingly augmented by data and artificial intelligence (AI). Although AI holds promise for real-time clinical-decision support, its impact on patient care has been modest. The principal limitation is not algorithmic capability but the quality, structure, and completeness of the data available for training and deployment. Most AI systems rely on electronic medical records (EMRs), which were designed primarily for billing rather than clinical insight. Consequently, important clinical information is fragmented, inconsistently documented, or absent altogether. Natural language processing and large language models (LLMs) improve data extraction, and yet they remain constrained by the underlying data quality and important privacy concerns. A critical gap persists in the acquisition of quantitative physiological data, particularly for the musculoskeletal system, where current practice relies on qualitative or semiquantitative assessments collected at single time points. In contrast, other industries\u2014such as the autonomous vehicle industry\u2014have advanced further by integrating continuous, multimodal sensor data to inform real-time decisions. Emerging multimodal wearable technologies offer a pathway toward similarly rich physiological data sets in medicine. Meaningful progress in AI-enabled health care will require such a transformation in data acquisition, enabling more accurate, continuous, and clinically relevant decision support.<\/jats:p>","DOI":"10.2106\/jbjs.25.01387","type":"journal-article","created":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T19:01:03Z","timestamp":1766170863000},"page":"266-268","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":2,"title":["AI-Based Medical Decision Support: Exploring the Data Gap"],"prefix":"10.2106","volume":"108","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2059-7559","authenticated-orcid":false,"given":"Joseph H.","family":"Schwab","sequence":"first","affiliation":[{"name":"Department of Orthopaedic Surgery, Cedars-Sinai Medical Center, Los Angeles, California"},{"name":"Center for Surgical Engineering and Innovation, Cedars-Sinai Medical Center, Los Angeles, California"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2025,12,19]]},"reference":[{"key":"bib2-20260218","first-page":"1","article-title":"The Real-Time Health System Architecture","author":"Pessin","year":"2023","journal-title":"Gartner"},{"issue":"10","key":"bib3-20260218","doi-asserted-by":"crossref","first-page":"1635","DOI":"10.1016\/j.spinee.2020.04.001","article-title":"Development of machine learning and natural language processing algorithms for preoperative prediction and automated identification of intraoperative vascular injury in anterior lumbar spine surgery","volume":"21","author":"Karhade","year":"2021","journal-title":"Spine J"},{"issue":"5","key":"bib4-20260218","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1016\/j.spinee.2019.12.006","article-title":"Natural language processing for automated detection of incidental durotomy","volume":"20","author":"Karhade","year":"2020","journal-title":"Spine J."},{"key":"bib5-20260218","article-title":"Scaling Laws for Neural Language Models","author":"Kaplan","year":"2020","journal-title":"arXiv."},{"issue":"6","key":"bib7-20260218","doi-asserted-by":"crossref","first-page":"e36","DOI":"10.2106\/JBJS.K.00518","article-title":"Assessment of musculoskeletal physical examination skills and attitudes of orthopaedic residents","volume":"94","author":"Beran","year":"2012","journal-title":"J Bone Joint Surg Am."},{"issue":"3","key":"bib8-20260218","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1055\/s-0039-1692402","article-title":"Copy-and-Paste in Medical Student Notes: Extent, Temporal Trends, and Relationship to Scholastic Performance","volume":"10","author":"Monahan","year":"2019","journal-title":"Appl Clin Inform."},{"issue":"6","key":"bib9-20260218","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1056\/NEJMp068013","article-title":"The demise of the physical exam","volume":"354","author":"Jauhar","year":"2006","journal-title":"N Engl J Med."},{"issue":"1","key":"bib10-20260218","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1038\/s41746-023-00969-7","article-title":"Association of accelerometer-measured physical activity intensity, sedentary time, and exercise time with incident Parkinson\u2019s disease","volume":"6","author":"Liu","year":"2023","journal-title":"NPJ Digit Med."},{"key":"bib11-20260218","first-page":"15563316251344945","article-title":"The Impact of AI on the Development of Multimodal Wearable Devices in Musculoskeletal Medicine","author":"Olson","year":"2025","journal-title":"HSS J."},{"key":"bib12-20260218","article-title":"A Novel Acoustic Wearable for Assessment of Tendon Health and Loading Condition","author":"Yazdkhasti","year":"2024","journal-title":"arXiv."},{"key":"bib13-20260218","article-title":"The Required Spatial Resolution to Assess Imbalance Using Plantar Pressure Mapping","author":"Detels","year":"2024","journal-title":"arXiv."}],"container-title":["Journal of Bone and Joint Surgery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ovid.com\/10.2106\/JBJS.25.01387","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T13:41:26Z","timestamp":1787751686000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ovid.com\/10.2106\/JBJS.25.01387"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,19]]},"references-count":11,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026]]}},"URL":"https:\/\/doi.org\/10.2106\/jbjs.25.01387","relation":{},"ISSN":["0021-9355","1535-1386"],"issn-type":[{"value":"0021-9355","type":"print"},{"value":"1535-1386","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,19]]}}}