The experiences of place: Veterans with dementia making meaning of their environments
Little research has examined how older veterans view the long-term care facility as place and how they make meaning of their experiences within specific places. This study examined seven older veterans’ meanings of place within the cognitive support unit of a veteran's hospital and in a summer camp setting. In the facility, the environment was interpreted as restrictive. At camp, the environment was interpreted as freeing. Each of the environments was experienced within the horizons of meaning of residents’ lives [Gubrium, J.F., 1993. Speaking of Life: Horizons of Meaning for Nursing Home Residents. Aldine de Gruyter, Hawthorne, NY.]. What was evident here was that the experiences in both places, both in the moment and through horizons of meaning, contributed to how residents created a sense of place in these two distinct environments.
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.