Enrichment of a Data Lake to Support Population Health Outcomes Studies Using Social Determinants Linked EHR Data.
Journal
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
ISSN: 2153-4063
Titre abrégé: AMIA Jt Summits Transl Sci Proc
Pays: United States
ID NLM: 101539486
Informations de publication
Date de publication:
2023
2023
Historique:
medline:
23
6
2023
pubmed:
23
6
2023
entrez:
23
6
2023
Statut:
epublish
Résumé
The integration of electronic health records (EHRs) with social determinants of health (SDoH) is crucial for population health outcome research, but it requires the collection of identifiable information and poses security risks. This study presents a framework for facilitating de-identified clinical data with privacy-preserved geocoded linked SDoH data in a Data Lake. A reidentification risk detection algorithm was also developed to evaluate the transmission risk of the data. The utility of this framework was demonstrated through one population health outcomes research analyzing the correlation between socioeconomic status and the risk of having chronic conditions. The results of this study inform the development of evidence-based interventions and support the use of this framework in understanding the complex relationships between SDoH and health outcomes. This framework reduces computational and administrative workload and security risks for researchers and preserves data privacy and enables rapid and reliable research on SDoH-connected clinical data for research institutes.
Types de publication
Journal Article
Langues
eng
Pagination
448-457Subventions
Organisme : Patient-Centered Outcomes Research Institute
ID : RI-MISSOURI-01-PS1
Pays : United States
Informations de copyright
©2023 AMIA - All rights reserved.
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