2023
Integrating real-world data to assess cardiac ablation device outcomes in a multicenter study using the OMOP common data model for regulatory decisions: implementation and evaluation
Yu Y, Jiang G, Brandt E, Forsyth T, Dhruva S, Zhang S, Chen J, Noseworthy P, Doshi A, Collison-Farr K, Kim D, Ross J, Coplan P, Drozda J. Integrating real-world data to assess cardiac ablation device outcomes in a multicenter study using the OMOP common data model for regulatory decisions: implementation and evaluation. JAMIA Open 2023, 6: ooac108. PMID: 36632328, PMCID: PMC9831049, DOI: 10.1093/jamiaopen/ooac108.Peer-Reviewed Original ResearchOMOP Common Data ModelCommon data modelData modelMedical device dataObservational Medical Outcomes Partnership Common Data ModelReal-world dataReal-world evaluationData integrationMultiple healthcare systemsData transformationHealthcare systemElectronic health record dataDevice dataData sourcesChain databaseLoad processHealth record dataTest casesMercy HealthQA analysisMulticenter studyMayo ClinicPatient outcomesPatient encountersDevice outcomes
2021
Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report
Jiang G, Dhruva SS, Chen J, Schulz WL, Doshi AA, Noseworthy PA, Zhang S, Yu Y, Young H, Brandt E, Ervin KR, Shah ND, Ross JS, Coplan P, Drozda JP. Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report. Journal Of The American Medical Informatics Association 2021, 28: 2241-2250. PMID: 34313748, PMCID: PMC8449615, DOI: 10.1093/jamia/ocab117.Peer-Reviewed Original ResearchConceptsReal-world dataHealth information technology systemsInformation technology systemsUnique device identifiersMaturity modelNatural language processing toolsTechnology systemsUnstructured data elementsNatural language processingCommon data modelData quality frameworkLanguage processing toolsComputable phenotypeInformatics approachElectronic health recordsClinical data systemsData modelLanguage processingDevice identifiersStandardized codesData elementsProcessing toolsInformatics technologiesData captureHealth records
2020
The Promise of Big Data and Digital Solutions in Building a Cardiovascular Learning System: Opportunities and Barriers.
Mori M, Khera R, Lin Z, Ross JS, Schulz W, Krumholz HM. The Promise of Big Data and Digital Solutions in Building a Cardiovascular Learning System: Opportunities and Barriers. Methodist DeBakey Cardiovascular Journal 2020, 16: 212-219. PMID: 33133357, PMCID: PMC7587314, DOI: 10.14797/mdcj-16-3-212.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsLearning health systemLearning systemCommon data modelDynamic learning systemAdvanced analyticsBig dataData assetsData modelDigital solutionsCustomer interactionContinuous learningKnowledge generationEffective useConceptual modelAnalyticsSystemGoogleHealth systemLearningComparable scaleModelDataCompanies