Consumer background and composition on state medical boards: Who are these citizen members and do they adequately protect the public?

The composition and background of members of state medical boards, including public or citizen members, can impact the functionality and public perception of medical boards in the United States. This study analyzed the number of public members on each state medical board and their professional backgrounds or expertise to regulate the medical profession. The findings show that for nearly half of state medical boards public members comprise at least a quarter of their voting members; however, more than half of public members for all state medical boards have no measurable medical experience or background, including in patient safety. The need for public members to have medical expertise or background – especially in patient safety -- is discussed along with potential policy recommendations.

What Disease Does This Patient Have? A Large-Scale Open Domain Question Answering Dataset from Medical Exams

Open domain question answering (OpenQA) tasks have been recently attracting more and more attention from the natural language processing (NLP) community. In this work, we present the first free-form multiple-choice OpenQA dataset for solving medical problems, MedQA, collected from the professional medical board exams. It covers three languages: English, simplified Chinese, and traditional Chinese, and contains 12,723, 34,251, and 14,123 questions for the three languages, respectively. We implement both rule-based and popular neural methods by sequentially combining a document retriever and a machine comprehension model. Through experiments, we find that even the current best method can only achieve 36.7%, 42.0%, and 70.1% of test accuracy on the English, traditional Chinese, and simplified Chinese questions, respectively. We expect MedQA to present great challenges to existing OpenQA systems and hope that it can serve as a platform to promote much stronger OpenQA models from the NLP community in the future.

Longitudinal study of medical downgrades in the Royal Air Force

IntroductionAs the focus of the Royal Air Force (RAF) shifts from sustained to contingency operations and the number of personnel is reduced, the burden of retained, medically downgraded personnel may affect operational readiness. The main aims were: to define the prevalence of morbidity leading to permanent medical downgrading; to determine at risk populations and identify areas for improvement.MethodDatabase of personnel referred to the RAF Medical Board was analysed from January 2012 to October 2013 and January 2017 to December 2019. Patients were excluded if they did not require a formal medical board; incomplete and duplicate entries were also excluded. The primary reason for medical downgrade was categorised with an ICD-10 code. Further subanalysis compared musculoskeletal disease with age, individual trade groups and anatomic region.Results2% of RAF service personnel were permanently downgraded annually. Musculoskeletal disease was the leading cause for permanent downgrade across both periods: 58% and 49%. Female personnel were at a greater risk of musculoskeletal downgrade compared with males. Spinal and knee pathology were the leading cause for downgrading among ‘high risk’ personnel. Personnel downgraded due to musculoskeletal pathology were often retained in a limited role with 10% and 5% retained as medically fully deployable. 14% and 12% of personnel downgraded due to musculoskeletal pathology were medically discharged.ConclusionMusculoskeletal disease was the leading cause for permanent medical downgrades in the RAF. A greater proportion of downgraded personnel with musculoskeletal conditions were retained in service with medical limitations rather than medically discharged.