Hunter Jefferson, Dentino Philippe, Jayakumar Prakash
Department of Surgery and Perioperative Care, Dell Medical School, University of Texas at Austin, Austin, TX, USA.
Curr Rev Musculoskelet Med. 2025 Jun 14. doi: 10.1007/s12178-025-09982-7.
To establish the state-of-the-art in applied artificial intelligence (A.I) related to value-based musculoskeletal health care. We performed a literature review of A.I applications in orthopaedics and contextualized these studies based on their alignment with allocative value, technical value, and personal value. We synthesized our findings using descriptive analysis and the Gartner Hype Cycle.
82% of research activity involving A.I and its applications in musculoskeletal care is dominantly focused on technical value, which can be divided into three main sub-groups: imaging and diagnostics, prognostic outcomes and risk factors, and A.I integration within medical devices and care pathways. A.I advancing personal value (18% of studies) is rapidly gaining traction. Relatively few studies (< 1%) focused on allocative value. Emerging applications of A.I in orthopaedics providing 'technical value' include machine learning algorithms for predicting risk and prognosis, diagnostic computer vision algorithms, models advancing surgical robotics; 'personal value' include ambient listening technology, A.I scribes, triage of clinical messages, patient engagement via LLM chatbots, pre-charting applications; and emotional intelligence. Application of these technologies to Gartner's Hype Cycle suggests big data analytics and robotic surgery applications are approaching the plateau of productivity while multiagent / autonomous systems, emotional intelligence, and AI-enabled decision intelligence serve as innovation triggers but are in their infancy. A.I offers the opportunity to improve medical diagnosis, processes, practices and patient experiences and outcomes within musculoskeletal care delivery. While applications enhancing technical value and personal value are being actively researched and rapidly developed in the digital health industry, studies on how A.I provides value through equitable and fair allocation of resources at a population level should be promoted.
确立与基于价值的肌肉骨骼保健相关的应用人工智能（A.I）的最新技术水平。我们对人工智能在骨科领域的应用进行了文献综述，并根据这些研究与分配价值、技术价值和个人价值的契合度对其进行了背景分析。我们使用描述性分析和高德纳技术成熟度曲线对研究结果进行了综合分析。
涉及人工智能及其在肌肉骨骼保健中的应用的研究活动中，82%主要集中在技术价值上，这可分为三个主要子类别：成像与诊断、预后结果与风险因素，以及人工智能在医疗设备和护理路径中的整合。提升个人价值的人工智能（占研究的18%）正在迅速获得关注。相对较少的研究（<1%）关注分配价值。人工智能在骨科领域提供“技术价值”的新兴应用包括用于预测风险和预后的机器学习算法、诊断计算机视觉算法、推动手术机器人发展的模型；“个人价值”包括环境监听技术、人工智能抄写员、临床信息分类、通过大型语言模型聊天机器人促进患者参与、预图表应用程序；以及情商。将这些技术应用于高德纳技术成熟度曲线表明，大数据分析和机器人手术应用正接近生产力高原，而多智能体/自主系统、情商和人工智能驱动的决策智能作为创新触发因素，但仍处于起步阶段。人工智能为改善肌肉骨骼保健服务中的医疗诊断、流程、实践以及患者体验和结果提供了机会。虽然数字健康行业正在积极研究和快速开发提升技术价值和个人价值的应用，但应推动关于人工智能如何通过在人群层面公平公正地分配资源来提供价值的研究。
