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 measurements
2023
Developing an Actionable Taxonomy of Persistent Hypertension Using Electronic Health Records
Lu Y, Du C, Khidir H, Caraballo C, Mahajan S, Spatz E, Curry L, Krumholz H. Developing an Actionable Taxonomy of Persistent Hypertension Using Electronic Health Records. Circulation Cardiovascular Quality And Outcomes 2023, 16: e009453. PMID: 36727515, DOI: 10.1161/circoutcomes.122.009453.Peer-Reviewed Original ResearchConceptsPersistent hypertensionElectronic health recordsBlood pressureHealth recordsPharmacologic agentsPrescribed treatmentYale New Haven Health SystemTreatment planAdditional pharmacologic agentsAntihypertensive treatment intensificationConsecutive outpatient visitsElevated blood pressurePersistence of hypertensionElectronic health record dataHealth record dataEligible patientsTreatment intensificationChart reviewHispanic patientsOutpatient visitsMean agePharmacological treatmentConventional content analysisHypertensionClinician notes
2022
A multicenter evaluation of computable phenotyping approaches for SARS-CoV-2 infection and COVID-19 hospitalizations
Khera R, Mortazavi BJ, Sangha V, Warner F, Patrick Young H, Ross JS, Shah ND, Theel ES, Jenkinson WG, Knepper C, Wang K, Peaper D, Martinello RA, Brandt CA, Lin Z, Ko AI, Krumholz HM, Pollock BD, Schulz WL. A multicenter evaluation of computable phenotyping approaches for SARS-CoV-2 infection and COVID-19 hospitalizations. Npj Digital Medicine 2022, 5: 27. PMID: 35260762, PMCID: PMC8904579, DOI: 10.1038/s41746-022-00570-4.Peer-Reviewed Original ResearchCOVID-19 hospitalizationMayo ClinicDiagnosis codesCOVID-19 diagnosisPositive SARS-CoV-2 PCRYale New Haven Health SystemPositive SARS-CoV-2 testSARS-CoV-2 infectionSARS-CoV-2 PCRSARS-CoV-2 testCOVID-19Higher inhospital mortalitySARS-CoV2 infectionElectronic health record dataICD-10 diagnosisPositive laboratory testsHealth record dataInhospital mortalityAdditional patientsAntigen testSecondary diagnosisPrincipal diagnosisMulticenter evaluationPositive testComputable phenotype definitions
2021
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
2018
Prediction of ICU Readmissions Using Data at Patient Discharge
Pakbin A, Rafi P, Hurley N, Schulz W, Krumholz M, Mortazavi J. Prediction of ICU Readmissions Using Data at Patient Discharge. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2018, 00: 4932-4935. PMID: 30441449, DOI: 10.1109/embc.2018.8513181.Peer-Reviewed Original ResearchConceptsICU readmissionHigher health care costsSame hospital admissionElectronic health record dataPoor patient outcomesHealth record dataLong-term riskHealth care costsICU dischargeUnplanned readmissionHospital admissionPatient dischargePatient outcomesICU casesClinical careReadmissionCare costsRecord data
2017
Incorporating Stroke Severity Into Hospital Measures of 30-Day Mortality After Ischemic Stroke Hospitalization
Schwartz J, Wang Y, Qin L, Schwamm LH, Fonarow GC, Cormier N, Dorsey K, McNamara RL, Suter LG, Krumholz HM, Bernheim SM. Incorporating Stroke Severity Into Hospital Measures of 30-Day Mortality After Ischemic Stroke Hospitalization. Stroke 2017, 48: 3101-3107. PMID: 28954922, DOI: 10.1161/strokeaha.117.017960.Peer-Reviewed Original ResearchConceptsRisk-standardized mortality ratesElectronic health record dataHealth record dataStroke severityClaims dataMortality rateAmerican Heart Association/American Stroke AssociationHealth Stroke Scale scoreRisk variablesMedicaid ServicesRisk adjustmentMedian risk-standardized mortality rateGuidelines-Stroke registryLow-mortality hospitalsStroke Scale scoreAcute ischemic strokeAmerican Stroke AssociationOdds of mortalityMortality measuresRecord dataIschemic stroke hospitalizationsHigh-mortality hospitalsService claims dataRisk-adjustment variablesHospital admission