Journal article
Advancing Interoperability of Patient-level Social Determinants of Health Data to Support COVID-19 Research
AMIA Summits on Translational Science proceedings, Vol.2022, pp.396-405
2022
PMCID: PMC9285174
PMID: 35854720
Abstract
Including social determinants of health (SDoH) data in health outcomes research is essential for studying the sources of healthcare disparities and developing strategies to mitigate stressors. In this report, we describe a pragmatic design and approach to explore the encoding needs for transmitting SDoH screening tool responses from a large safety-net hospital into the National Covid Cohort Collaborative (N3C) OMOP dataset. We provide a stepwise account of designing data mapping and ingestion for patient-level SDoH and summarize the results of screening. Our approach demonstrates that sharing of these important data - typically stored as non-standard, EHR vendor specific codes - is feasible. As SDoH screening gains broader use nationally, the approach described in this paper could be used for other screening instruments and improve the interoperability of these important data.
Details
- Title: Subtitle
- Advancing Interoperability of Patient-level Social Determinants of Health Data to Support COVID-19 Research
- Creators
- Jimmy Phuong - University of WashingtonStephanie Hong - Johns Hopkins University School of MedicineMatvey B Palchuk - TriNetXJuan Espinoza - Children's Hospital of Los AngelesDaniella Meeker - Department of Preventive Medicine, University of Southern California, Los Angeles, CaliforniaDavid A Dorr - Oregon Health & Science UniversityGalina Lozinski - Department of Pediatrics, Boston Medical Center/Boston University School of MedicineCharisse Madlock-Brown - University of Tennessee Health Science CenterWilliam G Adams - Department of Pediatrics, Boston Medical Center/Boston University School of Medicine
- Resource Type
- Journal article
- Publication Details
- AMIA Summits on Translational Science proceedings, Vol.2022, pp.396-405
- PMID
- 35854720
- PMCID
- PMC9285174
- eISSN
- 2153-4063
- Grant note
- U24 TR002306 / NCATS NIH HHS UL1 TR001430 / NCATS NIH HHS UL1 TR001855 / NCATS NIH HHS
- Language
- English
- Date published
- 2022
- Academic Unit
- Nursing
- Record Identifier
- 9984446984302771
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