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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.
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1 to 4 of 4 Research Studies DisplayedJalbert JJ, Ritchey ME, Mi X
Methodological considerations in observational comparative effectiveness research for implantable medical devices: an epidemiologic perspective.
This article discusses some of the most salient issues encountered in conducting comparative effectiveness research on implantable devices. Included in this discussion are special methodological considerations regarding the use of data sources, exposure and outcome definitions, timing of exposure, and sources of bias.
AHRQ-funded; 29020050016; HS017731
Citation: Jalbert JJ, Ritchey ME, Mi X .
Methodological considerations in observational comparative effectiveness research for implantable medical devices: an epidemiologic perspective.
Am J Epidemiol. 2014 Nov 1;180(9):949-58. doi: 10.1093/aje/kwu206..
Keywords: Comparative Effectiveness, Research Methodologies, 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)
Schmid CH, Trikalinos Olkin, I
Bayesian network meta-analysis for unordered categorical outcomes with incomplete data.
The researchers developed a Bayesian multinomial network meta-analysis model for unordered (nominal) categorical outcomes that allows for partially observed data in which exact event counts may not be known for each category. Their model properly accounts for correlations of counts in mutually exclusive categories and enables proper comparison and ranking of treatment effects across multiple treatments and multiple outcomes categories.
AHRQ-funded; HS018574.
Citation: Schmid CH, Trikalinos Olkin, I .
Bayesian network meta-analysis for unordered categorical outcomes with incomplete data.
Res Synth Methods 2014 Jun;5(2):162-85. doi: 10.1002/jrsm.1103..
Keywords: Comparative Effectiveness, Outcomes, Data
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)