Aims. Physician burnout and its consequences have been recognized as increasingly prevalent and important issues for both organizations and individuals involved in healthcare delivery. The purpose of this study was to describe and compare the patterns of self-reported wellness in orthopaedic surgeons and trainees from multiple nations with varying health systems. Methods. A cross-sectional survey of 774 orthopaedic surgeons and trainees in five countries (Australia, Canada, New Zealand, UK, and USA) was conducted in 2019. Respondents were asked to complete the Mayo Clinic Well-Being Index and the Stanford Professional Fulfillment Index in addition to 31 personal/demographic questions and 27 employment-related questions via an anonymous online survey. Results. A total of 684 participants from five countries (Australia (n = 74), Canada (n = 90), New Zealand (n = 69), UK (n = 105), and USA (n = 346)) completed both of the risk assessment questionnaires (Mayo and Stanford). Of these, 42.8% (n = 293) were trainees and 57.2% (n = 391) were attending surgeons. On the Mayo Clinic Well-Being Index, 58.6% of the overall sample reported feeling burned out (n = 401). Significant differences were found between nations with regards to the proportion categorized as being at risk for poor outcomes (27.5% for New Zealand (19/69) vs 54.4% for Canada (49/90) ; p = 0.001). On the Stanford Professional Fulfillment Index, 38.9% of the respondents were classified as being burned out (266/684). Prevalence of burnout ranged from 27% for Australia (20/74 up to 47.8% for Canadian respondents (43/90; p = 0.010). Younger age groups (20 to 29: RR 2.52 (95% confidence interval (CI) 1.39 to 4.58; p = 0.002); 30 to 39: RR 2.40 (95% CI 1.36 to 4.24; p = 0.003); 40 to 49: RR 2.30 (95% CI 1.35 to 3.9; p = 0.002)) and trainee status (RR 1.53 (95% CI 1.15 to 2.03 p = 0.004)) were independently associated with increased relative risk of having a ‘at-risk’ or ‘burnout’ score. Conclusions. The rate of self-reported burnout and risk for poor outcomes among orthopaedic surgeons and trainees varies between countries but remains unacceptably high throughout. Both individual and health system characteristics contribute to physician wellness and should be considered in the development of strategies to improve surgeon wellbeing. Level of Evidence: III. Cite this article: Bone Jt Open 2021;2(11):932–939

The October 2024 Wrist & Hand Roundup360 looks at: Circumferential casting versus plaster splinting in preventing redisplacement of distal radial fractures; Comparable outcomes for operative versus nonoperative treatment of scapholunate ligament injuries in distal radius fractures; Perceived pain during the reduction of Colles fracture without anaesthesia; Diagnostic delays and physician training are key to reducing scaphoid fracture nonunion; Necrotizing fasciitis originating in the hand: a systematic review and meta-analysis; Study design influences outcomes in distal radial fracture research; Long-term results of index finger pollicization for congenital thumb anomalies: a systematic review; Enhancing nerve injury diagnosis: the evolving role of imaging and electrodiagnostic tools

Cite this article: Bone Joint Res 2023;12(6):372–374.

The OpenAI chatbot ChatGPT is an artificial intelligence (AI) application that uses state-of-the-art language processing AI. It can perform a vast number of tasks, from writing poetry and explaining complex quantum mechanics, to translating language and writing research articles with a human-like understanding and legitimacy. Since its initial release to the public in November 2022, ChatGPT has garnered considerable attention due to its ability to mimic the patterns of human language, and it has attracted billion-dollar investments from Microsoft and PricewaterhouseCoopers. The scope of ChatGPT and other large language models appears infinite, but there are several important limitations. This editorial provides an introduction to the basic functionality of ChatGPT and other large language models, their current applications and limitations, and the associated implications for clinical practice and research.

Cite this article: Bone Joint J 2023;105-B(6):587–589.

Aims. The aim of this study was to create artificial intelligence (AI) software with the purpose of providing a second opinion to physicians to support distal radius fracture (DRF) detection, and to compare the accuracy of fracture detection of physicians with and without software support. Methods. The dataset consisted of 26,121 anonymized anterior-posterior (AP) and lateral standard view radiographs of the wrist, with and without DRF. The convolutional neural network (CNN) model was trained to detect the presence of a DRF by comparing the radiographs containing a fracture to the inconspicuous ones. A total of 11 physicians (six surgeons in training and five hand surgeons) assessed 200 pairs of randomly selected digital radiographs of the wrist (AP and lateral) for the presence of a DRF. The same images were first evaluated without, and then with, the support of the CNN model, and the diagnostic accuracy of the two methods was compared. Results. At the time of the study, the CNN model showed an area under the receiver operating curve of 0.97. AI assistance improved the physician’s sensitivity (correct fracture detection) from 80% to 87%, and the specificity (correct fracture exclusion) from 91% to 95%. The overall error rate (combined false positive and false negative) was reduced from 14% without AI to 9% with AI. Conclusion. The use of a CNN model as a second opinion can improve the diagnostic accuracy of DRF detection in the study setting. Cite this article: Bone Joint Res 2024;13(10):588–595

Aims. There is concern that aggressive target pricing in the new Bundled Payment for Care Improvement Advanced (BPCI-A) penalizes high-performing groups that had achieved low costs through prior experience in bundled payments. We hypothesize that this methodology incorporates unsustainable downward trends on Target Prices and will lead to groups opting out of BPCI Advanced in favour of a traditional fee for service. Methods. Using the Centers for Medicare and Medicaid Services (CMS) data, we compared the Target Price factors for hospitals and physician groups that participated in both BPCI Classic and BPCI Advanced (legacy groups), with groups that only participated in BPCI Advanced (non-legacy). With rebasing of Target Prices in 2020 and opportunity for participants to drop out, we compared retention rates of hospitals and physician groups enrolled at the onset of BPCI Advanced with current enrolment in 2020. Results. At its peak in July 2015, 342 acute care hospitals and physician groups participated in Lower Extremity Joint Replacement (LEJR) in BPCI Classic. At its peak in March 2019, 534 acute care hospitals and physician groups participated in LEJR in BPCI Advanced. In January 2020, only 14.5% of legacy hospitals and physician groups opted to stay in BPCI Advanced for LEJR. Analysis of Target Price factors by legacy hospitals during both programmes demonstrates that participants in BPCI Classic received larger negative adjustments on the Target Price than non-legacy hospitals. Conclusion. BPCI Advanced provides little opportunity for a reduction in cost to offset a reduced Target Price for efficient providers, as made evident by the 85.5% withdrawal rate for BPCI Advanced. Efficient providers in BPCI Advanced are challenged by the programme’s application of trend and efficiency factors that presumes their cost reduction can continue to decline at the same rate as non-efficient providers. It remains to be seen if reverting back to Medicare fee for service will support the same level of care and quality achieved in historical bundled payment programmes. Cite this article: Bone Joint J 2021;103-B(6 Supple A):119–125