Background/Objectives: Wearable activity monitors and sensor-based devices are increasingly used to quantify mobility, load, and recovery in orthopaedic patients, yet clinicians lack practical guidance on selection, implementation, and interpretation. This qualitative expert consensus study synthesized real-world experiences from leaders in orthopaedics, rehabilitation, biomechanics, and digital health who implemented wearables at scale. Methods: Semi-structured interviews were conducted with 16 experts (64% response rate) recruited via hybrid purposive and snowball sampling. Participants included orthopaedic surgeons and research scientists with 124 cumulative years of wearable experience across over 9000 monitored patients. Interviews addressed device selection, clinical workflow, data management, and adoption barriers. Data were charted into a structured extraction matrix and analyzed using Inductive Thematic Analysis and a Framework Approach, reported per COREQ guidelines. Results: Experts utilized diverse sensor platforms across arthroplasty, trauma, spine, and sports medicine. Four key themes emerged: (1) device selection prioritized usability and patient compliance over technical sophistication; (2) workflow required defined team roles to manage data volume and avoid clinical burden; (3) patient engagement favored simplified, actionable feedback amid divergent views on data transparency; (4) future outlook anticipated AI-driven proactive risk prediction. Conclusions: No single wearable suits all orthopaedic practices; success hinges on aligning sensor placement with clinical questions, rigorous data quality checks, and integration into care plans. This study offers a practical checklist and roadmap for point-of-care adoption.

Introduction: Racial and ethnic disparities have been reported in the treatment of hip fractures; however, American Indian and Alaska Native (AI/AN) patients are often excluded. No existing racial disparity studies have evaluated the management and outcomes of hip fractures among AI/AN patients. We aim to assess whether there are disparities in risk factors, management, and complications in the surgical treatment of hip fractures among AI/AN patients. Methods: This retrospective cohort study used the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database to analyze AI/AN and White patients undergoing surgical treatment of hip fractures between 2016 and 2022. Descriptive statistics, t -tests, chi-squared tests, and multiple regression models were used to assess differences in patient demographics, preoperative comorbidities, time to surgery (TTS), and postoperative complications. Results: AI/AN patients were significantly younger than White patients yet had higher rates of preoperative comorbidities (diabetes [ P < 0.001], smoking [ P < 0.001], dialysis [ P < 0.001], anemia [ P = 0.007], and delirium [ P < 0.001]). When controlling for patient characteristics, TTS and mortality were similar between AI/AN and White patients ( P = 0.31, P = 0.38, respectively). However, AI/AN patients had significantly more postoperative complications including stroke ( P = 0.04) and pneumonia ( P < 0.01), had a shorter length of stay (LOS) ( P < 0.001), and were less likely to be discharged to a facility ( P < 0.001). Discussion: AI/AN patients with hip fractures had a higher burden of preoperative comorbidities and postoperative complications when compared with White patients. Reassuringly, AI/AN and White patients had similar TTS and 30-day mortality. When controlling for patient characteristics, AI/AN patients had a shorter LOS and were more likely to be discharged home. This may be inferred as a lack of access to rehabilitation facilities on discharge or more support from patient families and communities at home. Overall, AI/AN patients should be included in current and future research to better assess disparities in orthopaedic care.