Abstract
PURPOSE OF REVIEW: 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. RECENT FINDINGS: 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.