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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 3 of 3 Research Studies DisplayedAngier H, Gold R, Crawford C
Linkage methods for connecting children with parents in electronic health record and state public health insurance data.
The purpose of this study was to develop ways to create child-parent links in two healthcare-related data sources: Oregon clinics sharing an electronic health record (EHR) and Oregon Health Plan’s (OHP) administrative data. To create the child-parent links, researchers used the child’s emergency contact information from the EHR and household identification numbers from the OHP.
AHRQ-funded; HS018569
Citation: Angier H, Gold R, Crawford C .
Linkage methods for connecting children with parents in electronic health record and state public health insurance data.
Matern Child Health J. 2014 Nov;18(9):2025-33. doi: 10.1007/s10995-014-1453-8..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Data
Holmes JH, Elliott TE, Brown JS
Clinical research data warehouse governance for distributed research networks in the USA: a systematic review of the literature.
The researchers reviewed the published, peer-reviewed literature on clinical research data warehouse governance in distributed research networks (DRNs). They determined that a peer-reviewed literature on data warehouse governance is emerging but is still sparse. Understanding of DRN data governance policies and procedures is limited but expected to change as more DRN projects disseminate their governance approaches.
AHRQ-funded; HS019912
Citation: Holmes JH, Elliott TE, Brown JS .
Clinical research data warehouse governance for distributed research networks in the USA: a systematic review of the literature.
J Am Med Inform Assoc. 2014 Jul-Aug;21(4):730-6. doi: 10.1136/amiajnl-2013-002370..
Keywords: Comparative Effectiveness, Data, Health Information Technology (HIT)
Ji Z, Jiang X, Wang S
Differentially private distributed logistic regression using private and public data.
The purpose of this study was to develop hybrid data mining models using both public and private data sets in a differentially private and distributed manner to achieve improved utility of the disclosed data. The researchers concluded that the logistic regression models built with their new algorithm based on both private and public datasets demonstrate better utility than models that trained on private or public datasets alone without sacrificing the rigorous privacy guarantee.
AHRQ-funded; HS019913
Citation: Ji Z, Jiang X, Wang S .
Differentially private distributed logistic regression using private and public data.
BMC Med Genomics 2014;7 Suppl 1:S14. doi: 10.1186/1755-8794-7-s1-s14.
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Keywords: Comparative Effectiveness, Data, Health Information Technology (HIT)