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.Commentaries, Editorials and LettersConceptsLearning health systemLearning systemCommon data modelDynamic learning systemAdvanced analyticsBig dataData assetsData modelDigital solutionsCustomer interactionContinuous learningKnowledge generationEffective useConceptual modelAnalyticsSystemGoogleHealth systemLearningComparable scaleModelDataCompanies