Reducing barriers to post-9/11 veterans’ use of programs and services as they transition to civilian life
Abstract: Background: Numerous programs exist to support veterans in their transitions to civilian life. Programs are offered by a host of governmental and non-governmental stakeholders. Veterans report encountering many barriers to program participation. This study identified barrier reduction strategies offered by programs that new post-9/11 veterans reported using, determined which strategies veterans use and value, and examined veteran characteristics that impact their odds of using programs that offer barrier reduction strategies. Method: This study reflects findings from the first wave of data collection of The Veterans Metrics Initiative (TVMI), a longitudinal study examining the military-to-civilian reintegration of new post-9/11 veterans. The websites of programs used by respondents were coded for barrier reduction components. Veterans also indicated which barrier reduction components they found most helpful in meeting their reintegration goals. Results: Of 9566 veterans who participated in Wave 1 data collection, 84% reported using a program that offered at least one barrier reduction component. Barrier reduction components included tangible supports (e.g., scholarships, cash), increased access to programs, decreased stigma, and encouraged motivation to change. Although only 4% of programs that were used by veterans focused on helping them obtain Veterans Administration benefits, nearly 60% of veterans reported that this component was helpful in reaching their goals. Access assistance to other resources and supports was also reported as a helpful barrier reduction component. For instance, approximately 20% of veterans nominated programs that offered transportation. The study also found evidence of a misalignment between the kinds of barrier reduction components veterans valued and those which programs offered. Veterans from the most junior enlisted ranks, who are at most risk, were less likely than those from other ranks to use barrier reduction components. Study limitations and ideas for future research are discussed. Conclusions: Despite the evidence that barrier reduction components enhance access to programs and contribute to program sustainability, many programs used by post-9/11 veterans do not offer them. There was also a misalignment between the barrier reduction strategies that veterans value and the strategies offered by programs. Veteran serving organizations should increasingly implement barrier reduction strategies valued by veterans.
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.