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Documentation and review of social determinants of health data in the EHR: measures and associated insights

Documentation and review of social determinants of health data in the EHR: measures and... ObjectiveElectronic Health Records (EHRs) increasingly include designated fields to capture social determinants of health (SDOH). We developed measures to characterize their use, and use of other SDOH data types, to optimize SDOH data integration.Materials and MethodsWe developed 3 measures that accommodate different EHR data types on an encounter or patient-year basis. We implemented these measures—documented during encounter (DDE) captures documentation occurring during the encounter; documented by discharge (DBD) includes DDE plus documentation occurring any time prior to admission; and reviewed during encounter (RDE) captures whether anyone reviewed documented data—for the newly available structured SDOH fields and 4 other comparator SDOH data types (problem list, inpatient nursing question, social history free text, and social work notes) on a hospital encounter basis (with patient-year metrics in the Supplementary Appendix). Our sample included all patients (n = 27 127) with at least one hospitalization at UCSF Health (a large, urban, tertiary medical center) over a 1-year period.ResultsWe observed substantial variation in the use of different SDOH EHR data types. Notably, social history question fields (newly added at study period start) were rarely used (DDE: 0.03% of encounters, DBD: 0.26%, RDE: 0.03%). Free-text patient social history fields had higher use (DDE: 12.1%, DBD: 49.0%, RDE: 14.4%).DiscussionOur measures of real-world SDOH data use can guide current efforts to capture and leverage these data. For our institution, measures revealed substantial variation across data types, suggesting the need to engage in efforts such as EHR-user education and targeted workflow integration.ConclusionMeasures revealed opportunities to optimize SDOH data documentation and review. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the American Medical Informatics Association Oxford University Press

Documentation and review of social determinants of health data in the EHR: measures and associated insights

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References (21)

Publisher
Oxford University Press
Copyright
© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com
ISSN
1067-5027
eISSN
1527-974X
DOI
10.1093/jamia/ocab194
Publisher site
See Article on Publisher Site

Abstract

ObjectiveElectronic Health Records (EHRs) increasingly include designated fields to capture social determinants of health (SDOH). We developed measures to characterize their use, and use of other SDOH data types, to optimize SDOH data integration.Materials and MethodsWe developed 3 measures that accommodate different EHR data types on an encounter or patient-year basis. We implemented these measures—documented during encounter (DDE) captures documentation occurring during the encounter; documented by discharge (DBD) includes DDE plus documentation occurring any time prior to admission; and reviewed during encounter (RDE) captures whether anyone reviewed documented data—for the newly available structured SDOH fields and 4 other comparator SDOH data types (problem list, inpatient nursing question, social history free text, and social work notes) on a hospital encounter basis (with patient-year metrics in the Supplementary Appendix). Our sample included all patients (n = 27 127) with at least one hospitalization at UCSF Health (a large, urban, tertiary medical center) over a 1-year period.ResultsWe observed substantial variation in the use of different SDOH EHR data types. Notably, social history question fields (newly added at study period start) were rarely used (DDE: 0.03% of encounters, DBD: 0.26%, RDE: 0.03%). Free-text patient social history fields had higher use (DDE: 12.1%, DBD: 49.0%, RDE: 14.4%).DiscussionOur measures of real-world SDOH data use can guide current efforts to capture and leverage these data. For our institution, measures revealed substantial variation across data types, suggesting the need to engage in efforts such as EHR-user education and targeted workflow integration.ConclusionMeasures revealed opportunities to optimize SDOH data documentation and review.

Journal

Journal of the American Medical Informatics Association – Oxford University Press

Published: Sep 21, 2021

Keywords: social informatics; SDOH; EHR

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