Adaptation of an NLP system to a new healthcare environment to identify social determinants of health.

J Biomed Inform

Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, United States; Centre for Clinical and Public Health Informatics, University of Melbourne, Melbourne, Australia.

Published: August 2021

Social determinants of health (SDoH) are increasingly important factors for population health, healthcare outcomes, and care delivery. However, many of these factors are not reliably captured within structured electronic health record (EHR) data. In this work, we evaluated and adapted a previously published NLP tool to include additional social risk factors for deployment at Vanderbilt University Medical Center in an Acute Myocardial Infarction cohort. We developed a transformation of the SDoH outputs of the tool into the OMOP common data model (CDM) for re-use across many potential use cases, yielding performance measures across 8 SDoH classes of precision 0.83 recall 0.74 and F-measure of 0.78.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386129PMC
http://dx.doi.org/10.1016/j.jbi.2021.103851DOI Listing

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