Armed Forces and Veteran Housing Policies: The United Kingdom 2021 Vision
Abstract: Accessing suitable accommodation post transition into civilian life from the military is one of the key markers for future success and wellbeing. For many this process can and does start during their military career. Some veterans struggle to find appropriate housing, often complicated by other difficulties associated with employment, physical and mental injuries, or difficulties with relationships. Over the past two years the position of veterans, veterans’ families, and service people in transition in the United Kingdom (UK) has gained increased national and international visibility through the establishment of the Office for Veterans’ Affairs. The Ministry of Defence’s 2018 Strategy for Our Veterans’ report contains a key theme that veterans in the UK should have a secure place to live either through buying, renting or social housing. However, the National Audit Office (NAO) recently reported that the Ministry of Defence (MOD) is not meeting its commitment to provide high-quality, subsidised accommodation to all service personnel. Satisfaction with single living accommodation has declined in recent years and can impact on the retention of military personnel, risking the MOD’s ability to deliver defence capabilities. This review looks at the policy changes made in the past two years to support quality UK service accommodation, aid, sustain successful post-military transitions, and ensure veterans do not want for adequate housing.
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.