2023
An explainable machine learning-based phenomapping strategy for adaptive predictive enrichment in randomized clinical trials
Oikonomou E, Thangaraj P, Bhatt D, Ross J, Young L, Krumholz H, Suchard M, Khera R. An explainable machine learning-based phenomapping strategy for adaptive predictive enrichment in randomized clinical trials. Npj Digital Medicine 2023, 6: 217. PMID: 38001154, PMCID: PMC10673945, DOI: 10.1038/s41746-023-00963-z.Peer-Reviewed Original ResearchMultinational patterns of second line antihyperglycaemic drug initiation across cardiovascular risk groups: federated pharmacoepidemiological evaluation in LEGEND-T2DM
Khera R, Dhingra L, Aminorroaya A, Li K, Zhou J, Arshad F, Blacketer C, Bowring M, Bu F, Cook M, Dorr D, Duarte-Salles T, DuVall S, Falconer T, French T, Hanchrow E, Horban S, Lau W, Li J, Liu Y, Lu Y, Man K, Matheny M, Mathioudakis N, McLemore M, Minty E, Morales D, Nagy P, Nishimura A, Ostropolets A, Pistillo A, Posada J, Pratt N, Reyes C, Ross J, Seager S, Shah N, Simon K, Wan E, Yang J, Yin C, You S, Schuemie M, Ryan P, Hripcsak G, Krumholz H, Suchard M. Multinational patterns of second line antihyperglycaemic drug initiation across cardiovascular risk groups: federated pharmacoepidemiological evaluation in LEGEND-T2DM. BMJ Medicine 2023, 2: e000651. PMID: 37829182, PMCID: PMC10565313, DOI: 10.1136/bmjmed-2023-000651.Peer-Reviewed Original ResearchType 2 diabetes mellitusSecond-line treatmentCardiovascular risk groupsDiabetes mellitusCardiovascular diseaseAntihyperglycaemic drugsLine treatmentRisk groupsObservational Health Data SciencesGlucagon-like peptide-1 receptor agonistsElectronic health recordsSodium-glucose cotransporter 2 inhibitorsCalendar year trendsPeptide-1 receptor agonistsUS databaseOutcomes of patientsCotransporter 2 inhibitorsAdministrative claims databaseSecond-line drugsHealth recordsSodium-glucose cotransporter-2 inhibitorsMedication useMetformin monotherapyGuideline recommendationsOutcome measuresAdding device identifiers to claims forms—a key step to advance medical device safety
Kadakia K, Dhruva S, Ross J, Krumholz H. Adding device identifiers to claims forms—a key step to advance medical device safety. The BMJ 2023, 380: p82. PMID: 36631149, DOI: 10.1136/bmj.p82.Commentaries, Editorials and LettersUse of Recalled Devices in New Device Authorizations Under the US Food and Drug Administration’s 510(k) Pathway and Risk of Subsequent Recalls
Kadakia K, Dhruva S, Caraballo C, Ross J, Krumholz H. Use of Recalled Devices in New Device Authorizations Under the US Food and Drug Administration’s 510(k) Pathway and Risk of Subsequent Recalls. JAMA 2023, 329: 136-143. PMID: 36625810, PMCID: PMC9857464, DOI: 10.1001/jama.2022.23279.Peer-Reviewed Original ResearchPrimary care institutional characteristics associated with hypertension awareness, treatment, and control in the China PEACE-Million Persons Project and primary health-care survey: a cross-sectional study
Group C, Zhou T, Wang Y, Zhang H, Wu C, Tian N, Cui J, Bai X, Yang Y, Zhang X, Lu Y, Spatz E, Ross J, Krumholz H, Lu J, Li X, Hu S. Primary care institutional characteristics associated with hypertension awareness, treatment, and control in the China PEACE-Million Persons Project and primary health-care survey: a cross-sectional study. The Lancet Global Health 2023, 11: e83-e94. PMID: 36521957, DOI: 10.1016/s2214-109x(22)00428-4.Peer-Reviewed Original ResearchConceptsProportion of participantsPrimary care institutionsHypertension awarenessPrimary care systemBlood pressureCare institutionsCardiac Events Million Persons ProjectAverage diastolic blood pressureMedical Sciences (CAMS) Innovation FundAverage systolic blood pressureCare systemMillion Persons ProjectHistory of hypertensionDiastolic blood pressurePrimary care surveySystolic blood pressureCardiovascular disease riskBlood pressure measurementsCross-sectional studyParticipant-level dataProportion of physiciansRoutine service deliveryPrimary care roleHealth Care SurveyPublic health services
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 definitionsA Different Case of Penumbra—Reply
Kadakia KT, Ross JS, Krumholz HM. A Different Case of Penumbra—Reply. JAMA Internal Medicine 2022, 182: 570-571. PMID: 35285863, DOI: 10.1001/jamainternmed.2022.0105.Commentaries, Editorials and LettersSensible regulation and clinical implementation of clinical decision support software as a medical device
Mori M, Jarrin R, Lu Y, Kadakia K, Huang C, Ross JS, Krumholz HM. Sensible regulation and clinical implementation of clinical decision support software as a medical device. The BMJ 2022, 376: o525. PMID: 35228206, DOI: 10.1136/bmj.o525.Commentaries, Editorials and LettersRenewing the Call for Reforms to Medical Device Safety—The Case of Penumbra
Kadakia KT, Beckman AL, Ross JS, Krumholz HM. Renewing the Call for Reforms to Medical Device Safety—The Case of Penumbra. JAMA Internal Medicine 2022, 182: 59-65. PMID: 34842892, DOI: 10.1001/jamainternmed.2021.6626.Commentaries, Editorials and LettersConceptsReperfusion catheterClinical evidenceClass IPenumbra reperfusion catheterSingle-arm trialUser Facility Device Experience (MAUDE) databaseAdverse event reportsPostmarket surveillanceHealth policy makersMedical device reportsPenumbra deviceClinical evaluationPatient deathDevice safetyMedicine recommendationsAnimal dataCatheterFDA databaseFDA medical device regulationsClinical literatureSmall sample sizeDevice reportsEvent reportsPublic healthExperience database
2017
Hospital-Readmission Risk — Isolating Hospital Effects from Patient Effects
Krumholz HM, Wang K, Lin Z, Dharmarajan K, Horwitz LI, Ross JS, Drye EE, Bernheim SM, Normand ST. Hospital-Readmission Risk — Isolating Hospital Effects from Patient Effects. New England Journal Of Medicine 2017, 377: 1055-1064. PMID: 28902587, PMCID: PMC5671772, DOI: 10.1056/nejmsa1702321.Peer-Reviewed Original ResearchConceptsRisk-standardized readmission ratesReadmission ratesObserved readmission ratesSimilar diagnosesHospital effectsDifferent hospitalsHospital readmission performanceRate of readmissionHospital readmission ratesLower readmission ratesStudy sampleYears of ageSignificant differencesMultiple admissionsReadmission outcomesOnly significant differencePatient effectsSame patientMedicare recipientsPatientsReadmission performanceRisk-standardized hospital readmission ratesHospitalHospital qualityQuartileAssociation of Changing Hospital Readmission Rates With Mortality Rates After Hospital Discharge
Dharmarajan K, Wang Y, Lin Z, Normand ST, Ross JS, Horwitz LI, Desai NR, Suter LG, Drye EE, Bernheim SM, Krumholz HM. Association of Changing Hospital Readmission Rates With Mortality Rates After Hospital Discharge. JAMA 2017, 318: 270-278. PMID: 28719692, PMCID: PMC5817448, DOI: 10.1001/jama.2017.8444.Peer-Reviewed Original ResearchConceptsRisk-adjusted readmission ratesRisk-adjusted mortality ratesAcute myocardial infarctionHeart failureReadmission ratesMortality rateMyocardial infarctionMedicare feeService beneficiariesHospital readmission ratesMean hospitalHospital mortalityPostdischarge mortalityHospital dischargeHospital readmissionRetrospective studyAffordable Care ActReadmission reductionMAIN OUTCOMEPneumoniaHospitalSecondary analysisWeighted Pearson correlation coefficientMortalityCare Act
2016
Accounting For Patients’ Socioeconomic Status Does Not Change Hospital Readmission Rates
Bernheim SM, Parzynski CS, Horwitz L, Lin Z, Araas MJ, Ross JS, Drye EE, Suter LG, Normand SL, Krumholz HM. Accounting For Patients’ Socioeconomic Status Does Not Change Hospital Readmission Rates. Health Affairs 2016, 35: 1461-1470. PMID: 27503972, PMCID: PMC7664840, DOI: 10.1377/hlthaff.2015.0394.Peer-Reviewed Original ResearchConceptsHospital Readmissions Reduction ProgramPatients' socioeconomic statusMedicare's Hospital Readmissions Reduction ProgramLow socioeconomic statusReadmission ratesSocioeconomic statusRisk-standardized readmission ratesHospital readmission ratesReadmissions Reduction ProgramMedicaid Services methodologyReadmission measuresHospital resultsPatientsHospitalSuch hospitalsPayment penaltiesReduction programsStatusCurrent CentersLower proportionLarge proportionPercentAdjustmentProportion
2013
Relationship Between Hospital Readmission and Mortality Rates for Patients Hospitalized With Acute Myocardial Infarction, Heart Failure, or Pneumonia
Krumholz HM, Lin Z, Keenan PS, Chen J, Ross JS, Drye EE, Bernheim SM, Wang Y, Bradley EH, Han LF, Normand SL. Relationship Between Hospital Readmission and Mortality Rates for Patients Hospitalized With Acute Myocardial Infarction, Heart Failure, or Pneumonia. JAMA 2013, 309: 587-593. PMID: 23403683, PMCID: PMC3621028, DOI: 10.1001/jama.2013.333.Peer-Reviewed Original ResearchConceptsRisk-standardized mortality ratesAcute myocardial infarctionRisk-standardized readmission ratesHospital risk-standardized mortality ratesHeart failureMyocardial infarctionHospital characteristicsMortality rateReadmission ratesProportion of hospitalsHospital readmissionMedicare feePneumoniaInfarctionService beneficiariesHospitalPatientsMedicaid ServicesHospital performanceSubgroupsFailureCauseReadmissionSignificant negative linear relationship
2008
An Administrative Claims Measure Suitable for Profiling Hospital Performance on the Basis of 30-Day All-Cause Readmission Rates Among Patients With Heart Failure
Keenan PS, Normand SL, Lin Z, Drye EE, Bhat KR, Ross JS, Schuur JD, Stauffer BD, Bernheim SM, Epstein AJ, Wang Y, Herrin J, Chen J, Federer JJ, Mattera JA, Wang Y, Krumholz HM. An Administrative Claims Measure Suitable for Profiling Hospital Performance on the Basis of 30-Day All-Cause Readmission Rates Among Patients With Heart Failure. Circulation Cardiovascular Quality And Outcomes 2008, 1: 29-37. PMID: 20031785, DOI: 10.1161/circoutcomes.108.802686.Peer-Reviewed Original ResearchConceptsRisk-standardized readmission ratesCause readmission rateReadmission ratesHeart failureHospital-level readmission ratesAdjusted readmission ratesAdministrative Claims MeasureUnadjusted readmission ratesHeart failure patientsHospital risk-standardized readmission ratesMedical record dataProfiling Hospital PerformanceHierarchical logistic regression modelsUse of MedicareMedical record modelNational Quality ForumLogistic regression modelsCause readmissionClaims-based modelsHospital dischargeFailure patientsC-statisticPreventable eventsPatientsQuality Forum
2024
Modernizing Medical Device Regulation: Challenges and Opportunities for the 510(k) Clearance Process.
Kadakia K, Rathi V, Dhruva S, Ross J, Krumholz H. Modernizing Medical Device Regulation: Challenges and Opportunities for the 510(k) Clearance Process. Annals Of Internal Medicine 2024, 177: 1558-1565. PMID: 39374526, DOI: 10.7326/annals-24-00728.Peer-Reviewed Original ResearchUse 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 measurementsClass I Recalls of Cardiovascular Devices Between 2013 and 2022 : A Cross-Sectional Analysis.
See C, Mooghali M, Dhruva S, Ross J, Krumholz H, Kadakia K. Class I Recalls of Cardiovascular Devices Between 2013 and 2022 : A Cross-Sectional Analysis. Annals Of Internal Medicine 2024, 177: 1499-1508. PMID: 39284187, DOI: 10.7326/annals-24-00724.Peer-Reviewed Original ResearchCross-sectional studyCross-sectional analysisAdverse health consequencesPatient safetyClinical testingClass IHealth consequencesClinical evidenceFDA summariesPostapproval studiesDecision summariesFood and Drug AdministrationU.S. Food and Drug AdministrationEnd-point selectionPremarket approvalMultiple class IClinical studiesPostmarketing surveillanceSummaryDrug AdministrationMedical device recall databaseRecallPatientsFDAPostmarketingComparative Effectiveness of Second-Line Antihyperglycemic Agents for Cardiovascular Outcomes A Multinational, Federated Analysis of LEGEND-T2DM
Khera R, Aminorroaya A, Dhingra L, Thangaraj P, Pedroso Camargos A, Bu F, Ding X, Nishimura A, Anand T, Arshad F, Blacketer C, Chai Y, Chattopadhyay S, Cook M, Dorr D, Duarte-Salles T, DuVall S, Falconer T, French T, Hanchrow E, Kaur G, Lau W, Li J, Li K, Liu Y, Lu Y, Man K, Matheny M, Mathioudakis N, McLeggon J, McLemore M, Minty E, Morales D, Nagy P, Ostropolets A, Pistillo A, Phan T, Pratt N, Reyes C, Richter L, Ross J, Ruan E, Seager S, Simon K, Viernes B, Yang J, Yin C, You S, Zhou J, Ryan P, Schuemie M, Krumholz H, Hripcsak G, Suchard M. Comparative Effectiveness of Second-Line Antihyperglycemic Agents for Cardiovascular Outcomes A Multinational, Federated Analysis of LEGEND-T2DM. Journal Of The American College Of Cardiology 2024, 84: 904-917. PMID: 39197980, DOI: 10.1016/j.jacc.2024.05.069.Peer-Reviewed Original ResearchConceptsGLP-1 RAsSecond-line agentsGLP-1Antihyperglycemic agentsCardiovascular diseaseMACE riskGlucagon-like peptide-1 receptor agonistsSodium-glucose cotransporter 2 inhibitorsPeptide-1 receptor agonistsDipeptidyl peptidase-4 inhibitorsEffects of SGLT2isType 2 diabetes mellitusPeptidase-4 inhibitorsAdverse cardiovascular eventsCox proportional hazards modelsRandom-effects meta-analysisCardiovascular risk reductionTarget trial emulationProportional hazards modelFloods and cause-specific mortality in the United States during 2001-2020
Chu L, Warren J, Spatz E, Lowe S, Lu Y, Ma X, Ross J, Krumholz H, Chen K. Floods and cause-specific mortality in the United States during 2001-2020. ISEE Conference Abstracts 2024, 2024 DOI: 10.1289/isee.2024.1705.Peer-Reviewed Original ResearchAltmetric Attention Scores and Citations of Published Research With or Without Preprints
Zissette S, Gautam A, Krumholz H, Ross J, Wallach J. Altmetric Attention Scores and Citations of Published Research With or Without Preprints. JAMA Network Open 2024, 7: e2424732. PMID: 39058492, PMCID: PMC11282438, DOI: 10.1001/jamanetworkopen.2024.24732.Peer-Reviewed Original Research