AI Article Synopsis
- This study developed a natural language processing (NLP) system to identify social risk factors in home health care clinical notes and analyzed their link to hospitalizations or emergency department visits.
- The research involved a retrospective cohort study of over 86,000 care episodes for nearly 66,000 patients, using expert-guided vocabulary to pinpoint relevant social risks documented in clinical notes.
- Results showed the NLP system performed well, identifying key risk factors like Social and Physical Environment and highlighting their association with increased hospitalization and ED visits, emphasizing the importance of addressing these factors in patient care.
Article Abstract
Objective: This study aimed to develop a natural language processing (NLP) system that identified social risk factors in home health care (HHC) clinical notes and to examine the association between social risk factors and hospitalization or an emergency department (ED) visit.
Design: Retrospective cohort study.
Setting And Participants: We used standardized assessments and clinical notes from one HHC agency located in the northeastern United States. This included 86,866 episodes of care for 65,593 unique patients. Patients received HHC services between 2015 and 2017.
Methods: Guided by HHC experts, we created a vocabulary of social risk factors that influence hospitalization or ED visit risk in the HHC setting. We then developed an NLP system to automatically identify social risk factors documented in clinical notes. We used an adjusted logistic regression model to examine the association between the NLP-based social risk factors and hospitalization or an ED visit.
Results: On the basis of expert consensus, the following social risk factors emerged: Social Environment, Physical Environment, Education and Literacy, Food Insecurity, Access to Care, and Housing and Economic Circumstances. Our NLP system performed "very good" with an F score of 0.91. Approximately 4% of clinical notes (33% episodes of care) documented a social risk factor. The most frequently documented social risk factors were Physical Environment and Social Environment. Except for Housing and Economic Circumstances, all NLP-based social risk factors were associated with higher odds of hospitalization and ED visits.
Conclusions And Implications: HHC clinicians assess and document social risk factors associated with hospitalizations and ED visits in their clinical notes. Future studies can explore the social risk factors documented in HHC to improve communication across the health care system and to predict patients at risk for being hospitalized or visiting the ED.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10839109 | PMC |
| http://dx.doi.org/10.1016/j.jamda.2023.06.031 | DOI Listing |
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