Shah Romil, Bozic Kevin J, Jayakumar Prakash
Department of Orthopedic Surgery, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Department of Surgery and Perioperative Care, Dell Medical School, The University of Texas at Austin, Austin, TX, USA.
HSS J. 2025 May 28:15563316251340074. doi: 10.1177/15563316251340074.
Artificial intelligence (AI) presents new opportunities to advance value-based healthcare in orthopedic surgery through 3 potential mechanisms: agency, automation, and augmentation. AI may enhance patient agency through improved health literacy and remote monitoring while reducing costs through triage and reduction in specialist visits. In automation, AI optimizes operating room scheduling and streamlines administrative tasks, with documented cost savings and improved efficiency. For augmentation, AI has been shown to be accurate in diagnostic imaging interpretation and surgical planning, while enabling more precise outcome predictions and personalized treatment approaches. However, implementation faces substantial challenges, including resistance from healthcare professionals, technical barriers to data quality and privacy, and significant financial investments required for infrastructure. Success in healthcare AI integration requires careful attention to regulatory frameworks, data privacy, and clinical validation.
人工智能（AI）通过三种潜在机制为推进骨科手术中基于价值的医疗保健带来了新机遇：代理、自动化和增强。人工智能可以通过提高健康素养和远程监测来增强患者的代理能力，同时通过分诊和减少专科就诊次数来降低成本。在自动化方面，人工智能优化手术室调度并简化行政任务，已证明可节省成本并提高效率。在增强方面，人工智能在诊断成像解读和手术规划中已被证明是准确的，同时能够进行更精确的结果预测和个性化治疗方法。然而，实施面临重大挑战，包括医疗保健专业人员的抵制、数据质量和隐私的技术障碍以及基础设施所需的大量资金投入。成功整合医疗保健人工智能需要密切关注监管框架、数据隐私和临床验证。
