Associations between Post-Traumatic Stress Disorder, Quality of Life and Alcohol Misuse among UK Veterans
Abstact: Prior research has shown that those with Post-Traumatic Stress Disorder (PTSD) have persistent reductions in quality of life (QoL), and higher rates of alcohol misuse. As such, it is important that we explore QoL and alcohol misuse on PTSD diagnosis. Therefore, the aim of this study was to assess the association between PTSD, QoL and alcohol misuse among United Kingdom (UK) veterans. 163 UK veterans who sought help for a mental health disorder were recruited to take part. Linear regressions were used to assess the association between probable PTSD, QoL and alcohol misuse. Pearson’s correlation analyses were used to assess the relationship between PTSD symptom clusters and QoL domains. We found unadjusted regressions showed evidence that, compared to those without PTSD, those with PTSD had lower QoL scores on physical health, psychosocial, social relationships and environment domains. Adjusting for age, sex, and outcome variables, only associations with the physical health domain and psychosocial domain remained statistically significant. Correlation analyses between PTSD and QoL domains showed the strongest negative correlations between the functional impairment and physical health domain, and between the functional impairment and psychosocial domain. We found that those with probable PTSD had lower QoL and higher alcohol misuse scores.
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.