Featured Publications
Temporal relationship of computed and structured diagnoses in electronic health record data
Schulz WL, Young HP, Coppi A, Mortazavi BJ, Lin Z, Jean RA, Krumholz HM. Temporal relationship of computed and structured diagnoses in electronic health record data. BMC Medical Informatics And Decision Making 2021, 21: 61. PMID: 33596898, PMCID: PMC7890604, DOI: 10.1186/s12911-021-01416-x.Peer-Reviewed Original ResearchConceptsElectronic health recordsStructured diagnosisOutpatient blood pressureElectronic health record dataAcademic health systemLow-density lipoproteinHealth record dataBlood pressureStructured data elementsAdministrative claimsHypertensionClinical informationHyperlipidemiaClinical phenotypeEquivalent diagnosisVital signsHealth systemDiagnosisProblem listAdditional studiesHealth recordsRecord dataTimely accessEHR dataPatients
2024
Use of electronic health records to characterize patients with uncontrolled hypertension in two large health system networks
Lu Y, Keeley E, Barrette E, Cooper-DeHoff R, Dhruva S, Gaffney J, Gamble G, Handke B, Huang C, Krumholz H, McDonough C, Schulz W, Shaw K, Smith M, Woodard J, Young P, Ervin K, Ross J. Use of electronic health records to characterize patients with uncontrolled hypertension in two large health system networks. BMC Cardiovascular Disorders 2024, 24: 497. PMID: 39289597, PMCID: PMC11409735, DOI: 10.1186/s12872-024-04161-x.Peer-Reviewed Original ResearchConceptsElectronic health recordsHealth recordsHealth systemUncontrolled hypertensionUse of electronic health recordsHypertension managementElectronic health record systemsOneFlorida Clinical Research ConsortiumElectronic health record dataYale New Haven Health SystemBP measurementsICD-10-CM codesHealth system networkPublic health priorityICD-10-CMIncidence rate of deathElevated BP measurementsElevated blood pressure measurementsHealthcare visitsAmbulatory careHealth priorityRetrospective cohort studyEHR dataOneFloridaBlood pressure measurementsSOFA score performs worse than age for predicting mortality in patients with COVID-19
Sherak R, Sajjadi H, Khimani N, Tolchin B, Jubanyik K, Taylor R, Schulz W, Mortazavi B, Haimovich A. SOFA score performs worse than age for predicting mortality in patients with COVID-19. PLOS ONE 2024, 19: e0301013. PMID: 38758942, PMCID: PMC11101117, DOI: 10.1371/journal.pone.0301013.Peer-Reviewed Original ResearchConceptsCrisis standards of careIn-hospital mortalityIntensive care unitAcademic health systemSequential Organ Failure Assessment scoreCohort of intensive care unitSequential Organ Failure AssessmentStandard of careLogistic regression modelsMortality predictionPredicting in-hospital mortalityHealth systemUnivariate logistic regression modelCrisis standardsDisease morbidityCOVID-19Hypertension Trends and Disparities Over 12 Years in a Large Health System: Leveraging the Electronic Health Records
Brush J, Lu Y, Liu Y, Asher J, Li S, Sawano M, Young P, Schulz W, Anderson M, Burrows J, Krumholz H. Hypertension Trends and Disparities Over 12 Years in a Large Health System: Leveraging the Electronic Health Records. Journal Of The American Heart Association 2024, 13: e033253. PMID: 38686864, PMCID: PMC11179912, DOI: 10.1161/jaha.123.033253.Peer-Reviewed Original ResearchConceptsElectronic health recordsRegional health systemImprove hypertension careHealth systemHealth recordsHypertension careDiastolic blood pressureAge-adjusted prevalence ratesNon-Hispanic Black patientsPrevalence ratesLarger health systemCross-sectional analysisTransformation of medical dataLeveraging real-world dataHigh prevalence rateHypertension trendsHypertension prevalenceBlood pressureBlood pressure measurementsHypertension diagnosisPrimary outcomeNational trendsProportion of patientsAntihypertensive medicationsBlack patients
2021
Feasibility of using real-world data in the evaluation of cardiac ablation catheters: a test-case of the National Evaluation System for Health Technology Coordinating Center
Dhruva SS, Jiang G, Doshi AA, Friedman DJ, Brandt E, Chen J, Akar JG, Ross JS, Ervin KR, Farr K, Shah ND, Coplan P, Noseworthy PA, Zhang S, Forsyth T, Schulz WL, Yu Y, Drozda JP. Feasibility of using real-world data in the evaluation of cardiac ablation catheters: a test-case of the National Evaluation System for Health Technology Coordinating Center. BMJ Surgery Interventions & Health Technologies 2021, 3: e000089. PMID: 35047806, PMCID: PMC8749235, DOI: 10.1136/bmjsit-2021-000089.Peer-Reviewed Original ResearchPositive predictive valuePersistent atrial fibrillationIschemic ventricular tachycardiaAblation catheterHealth systemAtrial fibrillationVentricular tachycardiaCardiac ablation catheterAcute heart failureDuration of patientsHealth system dataCardiac tamponadeIschemic strokeRetrospective cohortHeart failureClinical outcomesEndpoint ascertainmentPredictive valueCatheterChart validationCoordinating CenterTachycardiaPatientsFibrillationParticipant population
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 scaleModelDataCompaniesAgile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform
Schulz WL, Durant T, Torre CJ, Hsiao AL, Krumholz HM. Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform. Journal Of Medical Internet Research 2020, 22: e18707. PMID: 32442130, PMCID: PMC7257473, DOI: 10.2196/18707.Peer-Reviewed Original ResearchConceptsReal-time dataHealth information technologyReal-world dataHealth platformInformation technologyCombination of technologiesReal timeSevere acute respiratory syndrome coronavirus 2Acute respiratory syndrome coronavirus 2Timely informationRespiratory syndrome coronavirus 2PlatformRespiratory tract infectionsSyndrome coronavirus 2Health care systemTract infectionsCoronavirus disease (COVID-19) outbreakIncident casesCoronavirus 2Novel applicationTechnologyAnalyticsHealth systemCare systemSpecific pathogensLeveraging the Electronic Health Records for Population Health: A Case Study of Patients With Markedly Elevated Blood Pressure
Lu Y, Huang C, Mahajan S, Schulz WL, Nasir K, Spatz ES, Krumholz HM. Leveraging the Electronic Health Records for Population Health: A Case Study of Patients With Markedly Elevated Blood Pressure. Journal Of The American Heart Association 2020, 9: e015033. PMID: 32200730, PMCID: PMC7428633, DOI: 10.1161/jaha.119.015033.Peer-Reviewed Original ResearchConceptsDiastolic blood pressureSystolic blood pressureElevated blood pressureBlood pressureElectronic health recordsPopulation health surveillanceHealth recordsYale New Haven Health SystemHealth surveillanceHealth systemPatterns of patientsLarge health systemUsual careOutpatient encountersControl ratePatientsCare patternsPopulation healthMonthsHgSurveillancePrevalenceRecordsVisitsCare