Defence Medical Services: A review of the clinical governance of the Defence Medical Services in the UK and overseas
Abstract: This report is the product of a fruitful collaboration between the Department of Health and the Ministry of Defence, and between the Healthcare Commission and the Defence Medical Services. It owes much to the leadership and commitment of the Surgeon General, Lieutenant General Louis Lillywhite and his predecessor, the late Surgeon Vice-Admiral Ian Jenkins. They took the view that it would be beneficial to the Defence Medical Services if its services were exposed to the scrutiny that the Healthcare Commission applies to the performance of the NHS. The Healthcare Commission, in line with its primary statutory duty to encourage improvement in the provision of health and healthcare, was pleased to accept the invitation. The Defence Medical Services provides care for about 250,000 people – Service personnel and their families. All concerned felt it right that their healthcare should be subject to the same scrutiny as that of others in England. The picture that the report paints of the Defence Medical Services is varied. There are areas of outstanding performance that the NHS could profitably learn from, not least the organisation and operation of trauma services. There are other areas where improvements need to be made, for example, getting universal standards in place across all services, and addressing maintenance and cleanliness at some medical units providing services away from the front line. These needs for improvement are recognised and it is pleasing that actions are already being taken to address them. It is important that progress is monitored and reported on regularly.
Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate the extraction of opioid relapses, and the timing of these occurrences, from veteran patients' electronic medical record. We then demonstrated the utility of our NLP tool via analysis of pre-/post-COVID-19 opioid relapse trends among veterans with OUD. For this demonstration, we analyzed data from 107,606 veterans OUD enrolled in Veterans Health Administration, comparing a pandemic-exposed cohort (n = 53,803; January 2019-March 2021) to a matched prepandemic cohort (n = 53,803; October 2017-December 2019). The recall of our NLP tool was 75% and our precision was 94%, demonstrating moderate sensitivity and excellent specificity. Using the NLP tool, we found that the odds of opioid relapse postpandemic onset were proportionally higher compared to prepandemic trends, despite patients having fewer mental health encounters from which to derive instances of relapse postpandemic onset. In this research application of the tool, and as hypothesized, we found that opioid relapse risk was elevated postpandemic. The application of NLP Methods: to identify and monitor relapse risk holds promise for future surveillance, risk prevention, and clinical outcome research.