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Social Determinants of Health in EMS Records: A Mixed-methods Analysis Using Natural Language Processing and Qualitative Content Analysis
INTRODUCTION: Social determinants of health (SDoH) are known to impact the health and well-being of patients. However, information regarding them is not always collected in healthcare interactions, and healthcare professionals are not always well-trained or equipped to address them. Emergency medica...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Department of Emergency Medicine, University of California, Irvine School of Medicine
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10527846/ https://www.ncbi.nlm.nih.gov/pubmed/37788028 http://dx.doi.org/10.5811/westjem.59070 |
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author | Burnett, Susan J. Stemerman, Rachel Innes, Johanna C. Kaisler, Maria C. Crowe, Remle P. Clemency, Brian M. |
author_facet | Burnett, Susan J. Stemerman, Rachel Innes, Johanna C. Kaisler, Maria C. Crowe, Remle P. Clemency, Brian M. |
author_sort | Burnett, Susan J. |
collection | PubMed |
description | INTRODUCTION: Social determinants of health (SDoH) are known to impact the health and well-being of patients. However, information regarding them is not always collected in healthcare interactions, and healthcare professionals are not always well-trained or equipped to address them. Emergency medical services (EMS) professionals are uniquely positioned to observe and attend to SDoH because of their presence in patients’ environments; however, the transmission of that information may be lost during transitions of care. Documentation of SDoH in EMS records may be helpful in identifying and addressing patients’ insecurities and improving their health outcomes. Our objective in this study was to determine the presence of SDoH information in adult EMS records and understand how such information is referenced, appraised, and linked to other determinants by EMS personnel. METHODS: Using EMS records for adult patients in the 2019 ESO Data Collaborative public-use research dataset using a natural language processing (NLP) algorithm, we identified free-text narratives containing documentation of at least one SDoH from categories associated with food, housing, employment, insurance, financial, and social support insecurities. From the NLP corpus, we randomly selected 100 records from each of the SDoH categories for qualitative content analysis using grounded theory. RESULTS: Of the 5,665,229 records analyzed by the NLP algorithm, 175,378 (3.1%) were identified as containing at least one reference to SDoH. References to those SDoH were centered around the social topics of accessibility, mental health, physical health, and substance use. There were infrequent explicit references to other SDoH in the EMS records, but some relationships between categories could be inferred from contexts. Appraisals of patients’ employment, food, and housing insecurities were mostly negative. Narratives including social support and financial insecurities were less negatively appraised, while those regarding insurance insecurities were mostly neutral and related to EMS operations and procedures. CONCLUSION: The social determinants of health are infrequently documented in EMS records. When they are included, they are infrequently explicitly linked to other SDoH categories and are often negatively appraised by EMS professionals. Given their unique position to observe and share patients’ SDoH information, EMS professionals should be trained to understand, document, and address SDoH in their practice. |
format | Online Article Text |
id | pubmed-10527846 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Department of Emergency Medicine, University of California, Irvine School of Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-105278462023-09-28 Social Determinants of Health in EMS Records: A Mixed-methods Analysis Using Natural Language Processing and Qualitative Content Analysis Burnett, Susan J. Stemerman, Rachel Innes, Johanna C. Kaisler, Maria C. Crowe, Remle P. Clemency, Brian M. West J Emerg Med Health Equity INTRODUCTION: Social determinants of health (SDoH) are known to impact the health and well-being of patients. However, information regarding them is not always collected in healthcare interactions, and healthcare professionals are not always well-trained or equipped to address them. Emergency medical services (EMS) professionals are uniquely positioned to observe and attend to SDoH because of their presence in patients’ environments; however, the transmission of that information may be lost during transitions of care. Documentation of SDoH in EMS records may be helpful in identifying and addressing patients’ insecurities and improving their health outcomes. Our objective in this study was to determine the presence of SDoH information in adult EMS records and understand how such information is referenced, appraised, and linked to other determinants by EMS personnel. METHODS: Using EMS records for adult patients in the 2019 ESO Data Collaborative public-use research dataset using a natural language processing (NLP) algorithm, we identified free-text narratives containing documentation of at least one SDoH from categories associated with food, housing, employment, insurance, financial, and social support insecurities. From the NLP corpus, we randomly selected 100 records from each of the SDoH categories for qualitative content analysis using grounded theory. RESULTS: Of the 5,665,229 records analyzed by the NLP algorithm, 175,378 (3.1%) were identified as containing at least one reference to SDoH. References to those SDoH were centered around the social topics of accessibility, mental health, physical health, and substance use. There were infrequent explicit references to other SDoH in the EMS records, but some relationships between categories could be inferred from contexts. Appraisals of patients’ employment, food, and housing insecurities were mostly negative. Narratives including social support and financial insecurities were less negatively appraised, while those regarding insurance insecurities were mostly neutral and related to EMS operations and procedures. CONCLUSION: The social determinants of health are infrequently documented in EMS records. When they are included, they are infrequently explicitly linked to other SDoH categories and are often negatively appraised by EMS professionals. Given their unique position to observe and share patients’ SDoH information, EMS professionals should be trained to understand, document, and address SDoH in their practice. Department of Emergency Medicine, University of California, Irvine School of Medicine 2023-09 2023-08-08 /pmc/articles/PMC10527846/ /pubmed/37788028 http://dx.doi.org/10.5811/westjem.59070 Text en © 2023 Burnett et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) License. See: http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | Health Equity Burnett, Susan J. Stemerman, Rachel Innes, Johanna C. Kaisler, Maria C. Crowe, Remle P. Clemency, Brian M. Social Determinants of Health in EMS Records: A Mixed-methods Analysis Using Natural Language Processing and Qualitative Content Analysis |
title | Social Determinants of Health in EMS Records: A Mixed-methods Analysis Using Natural Language Processing and Qualitative Content Analysis |
title_full | Social Determinants of Health in EMS Records: A Mixed-methods Analysis Using Natural Language Processing and Qualitative Content Analysis |
title_fullStr | Social Determinants of Health in EMS Records: A Mixed-methods Analysis Using Natural Language Processing and Qualitative Content Analysis |
title_full_unstemmed | Social Determinants of Health in EMS Records: A Mixed-methods Analysis Using Natural Language Processing and Qualitative Content Analysis |
title_short | Social Determinants of Health in EMS Records: A Mixed-methods Analysis Using Natural Language Processing and Qualitative Content Analysis |
title_sort | social determinants of health in ems records: a mixed-methods analysis using natural language processing and qualitative content analysis |
topic | Health Equity |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10527846/ https://www.ncbi.nlm.nih.gov/pubmed/37788028 http://dx.doi.org/10.5811/westjem.59070 |
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