Journal of biomedical informatics · 2021
ReHouSED: A novel measurement of Veteran housing stability using natural language processing.
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Chapman Alec B, Jones Audrey, Kelley A Taylor, Jones Barbara, Gawron Lori, Montgomery Ann Elizabeth, Byrne Thomas, Suo Ying, Cook James, Pettey Warren, Peterson Kelly, Jones Makoto, Nelson Richard
Аннотация
Housing stability is an important determinant of health. The US Department of Veterans Affairs (VA) administers several programs to assist Veterans experiencing unstable housing. Measuring long-term housing stability of Veterans who receive assistance from VA is difficult due to a lack of standardized structured documentation in the Electronic Health Record (EHR). However, the text of clinical notes often contains detailed information about Veterans' housing situations that may be extracted using natural language processing (NLP). We present a novel NLP-based measurement of Veteran housing stability: Relative Housing Stability in Electronic Documentation (ReHouSED). We first develop and evaluate a system for classifying documents containing information about Veterans' housing situations. Next, we aggregate information from multiple documents to derive a patient-level measurement of housing stability. Finally, we demonstrate this method's ability to differentiate between Veterans who are stably and unstably housed. Thus, ReHouSED provides an important methodological framework for the study of long-term housing stability among Veterans receiving housing assistance.