Characteristics Associated with Persistent Versus Transient Food Insecurity Among US Veterans Screened in the Veterans Health Administration
Abstract: Awareness of negative health impacts associated with food insecurity among US veterans is growing. Yet, little research has examined characteristics associated with persistent vs transient food insecurity. Our aim was to investigate characteristics associated with persistent vs transient food insecurity among US veterans. The study used a retrospective, observational design to examine data from Veterans Health Administration electronic medical records. The sample consisted of veterans (n = 64,789) who screened positive for food insecurity in Veterans Health Administration primary care during fiscal years 2018-2020 and were rescreened within 3 to 5 months. Food insecurity was operationalized using the Veterans Health Administration food insecurity screening question. Transient food insecurity was a positive screen followed by a consecutive negative screen within 3 to 15 months. Persistent food insecurity was a positive screen followed by a consecutive positive screen within 3 to 15 months. A multivariable logistic regression model was used to assess characteristics (eg, demographic characteristics, disability rating, homelessness, and physical and mental health conditions) associated with persistent vs transient food insecurity. Veterans with increased odds of persistent vs transient food insecurity included men (adjusted odds ratio [AOR] 1.08; 95% CI 1.01 to 1.15) and those from Hispanic (AOR 1.27; 95% CI 1.18 to 1.37) or Native American (AOR 1.30; 95% CI 1.11 to 1.53) racial and ethnic groups. Psychosis (AOR 1.16; 95% CI 1.06 to 1.26); substance use disorder, excluding tobacco and alcohol (AOR 1.11; 95% CI 1.03 to 1.20); and homelessness (AOR 1.32; 95% CI 1.26 to 1.39) were associated with increased odds of persistent vs transient food insecurity. Veterans who were married (AOR 0.87; 95% CI 0.83 to 0.92) or had a service-connected disability rating of 70% to 99% (AOR 0.85; 95% CI 0.79 to 0.90) or 100% (AOR 0.77; 95% CI 0.71 to 0.83) had lower odds of persistent vs transient food insecurity. Veterans at risk for persistent vs transient food insecurity may struggle with underlying issues like psychosis, substance use, and homelessness in addition to racial and ethnic inequities and gender differences. More research is needed to understand the characteristics and mechanisms that increase risk for persistent vs transient food insecurity among 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.