Assessing longitudinal housing status using Electronic Health Record data: a comparison of natural language processing, structured data, and patient-reported history.

ABSTRACT:

Introduction

Measuring long-term housing outcomes is important for evaluating the impacts of services for individuals with homeless experience. However, assessing long-term housing status using traditional methods is challenging. The Veterans Affairs (VA) Electronic Health Record (EHR) provides detailed data for a large population of patients with homeless experiences and contains several indicators of housing instability, including structured data elements (e.g., diagnosis codes) and free-text clinical narratives. However, the validity of each of these data elements for measuring housing stability over time is not well-studied.

Methods

We compared VA EHR indicators of housing instability, including information extracted from clinical notes using natural language processing

SUBMITTER: Chapman AB 

PROVIDER: S-EPMC10244644 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature