2024
Hospital COVID-19 Burden and Adverse Event Rates
Metersky M, Rodrick D, Ho S, Galusha D, Timashenka A, Grace E, Marshall D, Eckenrode S, Krumholz H. Hospital COVID-19 Burden and Adverse Event Rates. JAMA Network Open 2024, 7: e2442936. PMID: 39495512, PMCID: PMC11581512, DOI: 10.1001/jamanetworkopen.2024.42936.Peer-Reviewed Original ResearchConceptsCOVID-19 burdenHospital admissionPatient safetyRelative riskCohort studyStudy of hospital admissionsAcute care hospitalsRisk-adjustment variablesRisk-adjusted ratesMedicare hospital admissionsCOVID-19 pandemicStaffing shortagesHospital characteristicsMain OutcomesHospital resilienceSurge capacityMedicare patientsCare hospitalHighest burdenPrevent declinesPatient admissionsStudy sampleElixhauser comorbiditiesCOVID-19Low burden
2022
Trends in Adverse Event Rates in Hospitalized Patients, 2010-2019
Eldridge N, Wang Y, Metersky M, Eckenrode S, Mathew J, Sonnenfeld N, Perdue-Puli J, Hunt D, Brady PJ, McGann P, Grace E, Rodrick D, Drye E, Krumholz HM. Trends in Adverse Event Rates in Hospitalized Patients, 2010-2019. JAMA 2022, 328: 173-183. PMID: 35819424, PMCID: PMC9277501, DOI: 10.1001/jama.2022.9600.Peer-Reviewed Original ResearchMeSH KeywordsAccidental FallsAdultAgedAged, 80 and overCross InfectionCross-Sectional StudiesDrug-Related Side Effects and Adverse ReactionsFemaleHeart FailureHospitalizationHumansMaleMedicareMiddle AgedMyocardial InfarctionPatient SafetyPneumoniaPostoperative ComplicationsPressure UlcerRisk AssessmentSurgical Procedures, OperativeUnited StatesConceptsMajor surgical proceduresAcute myocardial infarctionAdverse event ratesGeneral adverse eventsAdverse eventsHeart failureAdverse drug eventsAcute care hospitalsMyocardial infarctionHospital-acquired infectionsSurgical proceduresEvent ratesHospital dischargeCare hospitalDrug eventsMedicare Patient Safety Monitoring SystemSerial cross-sectional studyPatient safetyUS acute care hospitalsHospital adverse eventsSignificant decreaseSurgical procedure groupsCross-sectional studyRisk-adjusted ratesAdult patients
2020
Association Between Medicare Expenditures and Adverse Events for Patients With Acute Myocardial Infarction, Heart Failure, or Pneumonia in the United States
Wang Y, Eldridge N, Metersky ML, Sonnenfeld N, Rodrick D, Fine JM, Eckenrode S, Galusha DH, Tasimi A, Hunt DR, Bernheim SM, Normand ST, Krumholz HM. Association Between Medicare Expenditures and Adverse Events for Patients With Acute Myocardial Infarction, Heart Failure, or Pneumonia in the United States. JAMA Network Open 2020, 3: e202142. PMID: 32259263, PMCID: PMC7139276, DOI: 10.1001/jamanetworkopen.2020.2142.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionMedicare Patient Safety Monitoring SystemAdverse event ratesAdverse eventsHeart failureMedicare expendituresService patientsMyocardial infarctionMedicare feeEvent ratesHigher adverse event ratesCare expendituresRisk-standardized ratesPatients 65 yearsAdverse event dataAcute care hospitalsCross-sectional studyFinal study sampleInpatient care expendituresRate of occurrenceDates of analysisPatient characteristicsCare hospitalMean ageInpatient careAssociation Between Subsequent Hospitalizations and Recurrent Acute Myocardial Infarction Within 1 Year After Acute Myocardial Infarction
Wang Y, Leifheit E, Normand S, Krumholz HM. Association Between Subsequent Hospitalizations and Recurrent Acute Myocardial Infarction Within 1 Year After Acute Myocardial Infarction. Journal Of The American Heart Association 2020, 9: e014907. PMID: 32172654, PMCID: PMC7335517, DOI: 10.1161/jaha.119.014907.Peer-Reviewed Original ResearchConceptsRecurrent acute myocardial infarctionAcute myocardial infarctionIndex acute myocardial infarctionClinical Classification SoftwareMyocardial infarctionDisease categoriesRisk of deathCox regression modelPost-acute careAcute care hospitalsOccurrence of hospitalizationLow recurrence riskUnplanned rehospitalizationSubsequent hospitalizationBackground PatientsHazard ratioPatient characteristicsSecondary preventionMedian timeService patientsChronic diseasesPatient riskOutcome measuresRehospitalizationHigh risk
2019
Development and Testing of Improved Models to Predict Payment Using Centers for Medicare & Medicaid Services Claims Data
Krumholz HM, Warner F, Coppi A, Triche EW, Li SX, Mahajan S, Li Y, Bernheim SM, Grady J, Dorsey K, Desai NR, Lin Z, Normand ST. Development and Testing of Improved Models to Predict Payment Using Centers for Medicare & Medicaid Services Claims Data. JAMA Network Open 2019, 2: e198406. PMID: 31411709, PMCID: PMC6694388, DOI: 10.1001/jamanetworkopen.2019.8406.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionHeart failurePopulation-based programsPOA codesSingle diagnostic codeDiagnostic codesComparative effectiveness research studyPublic reportingIndex admission diagnosisDays of hospitalizationClinical Modification codesService claims dataAcute care hospitalsMultiple care settingsPatient-level modelsAdmission diagnosisTotal hospitalizationsCare hospitalPrevious diagnosisNinth RevisionMyocardial infarctionCandidate variablesCare settingsClaims dataMAIN OUTCOME
2018
Variation in and Hospital Characteristics Associated With the Value of Care for Medicare Beneficiaries With Acute Myocardial Infarction, Heart Failure, and Pneumonia
Desai NR, Ott LS, George EJ, Xu X, Kim N, Zhou S, Hsieh A, Nuti SV, Lin Z, Bernheim SM, Krumholz HM. Variation in and Hospital Characteristics Associated With the Value of Care for Medicare Beneficiaries With Acute Myocardial Infarction, Heart Failure, and Pneumonia. JAMA Network Open 2018, 1: e183519. PMID: 30646247, PMCID: PMC6324438, DOI: 10.1001/jamanetworkopen.2018.3519.Peer-Reviewed Original ResearchConceptsRisk-standardized mortality ratesAcute myocardial infarctionHeart failureHigh-value careHospital characteristicsValue of careMyocardial infarctionNational cross-sectional studyHospital risk-standardized mortality ratesMedian risk-standardized mortality rateProportion of patientsSafety-net statusAcute care hospitalsCross-sectional studyLow socioeconomic statusCharacteristics of hospitalsValue-based payment modelsWeak inverse correlationCare hospitalHospital variationHospital typeHospitalizationMAIN OUTCOMEPneumoniaMedicare beneficiariesRisk Factors Associated With Major Cardiovascular Events 1 Year After Acute Myocardial Infarction
Wang Y, Li J, Zheng X, Jiang Z, Hu S, Wadhera RK, Bai X, Lu J, Wang Q, Li Y, Wu C, Xing C, Normand SL, Krumholz HM, Jiang L. Risk Factors Associated With Major Cardiovascular Events 1 Year After Acute Myocardial Infarction. JAMA Network Open 2018, 1: e181079-e181079. PMID: 30646102, PMCID: PMC6324290, DOI: 10.1001/jamanetworkopen.2018.1079.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionMajor cardiovascular eventsCardiovascular eventsRisk factorsC-statisticMyocardial infarctionAggressive risk factor reductionOne-year event ratesSubsequent major cardiovascular eventsRecurrent acute myocardial infarctionIndex AMI hospitalizationRisk factor reductionHigh-risk patientsProspective cohort studyCoronary heart diseaseLow-risk groupAcute care hospitalsCohort studyCommon comorbiditiesHeart failureMean ageRisk modelHeart diseaseMAIN OUTCOMEHigh risk
2017
Associations between nursing home performance and hospital 30‐day readmissions for acute myocardial infarction, heart failure and pneumonia at the healthcare community level in the United States
Pandolfi MM, Wang Y, Spenard A, Johnson F, Bonner A, Ho S, Elwell T, Bakullari A, Galusha D, Leifheit‐Limson E, Lichtman JH, Krumholz HM. Associations between nursing home performance and hospital 30‐day readmissions for acute myocardial infarction, heart failure and pneumonia at the healthcare community level in the United States. International Journal Of Older People Nursing 2017, 12 PMID: 28516505, DOI: 10.1111/opn.12154.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionReadmission ratesHeart failureNursing homesService patientsMyocardial infarctionMedicare feeLower hospital readmission ratesHospital readmission ratesNurse staffing measuresAcute care hospitalsCross-sectional studyHospital service areasFive-Star Quality Rating SystemNursing home performanceUnplanned readmissionCare hospitalReadmission dataCommunity-based service providersCare teamMedicare patientsReadmissionStaffing measuresPatientsPneumonia
2016
Association Between Hospital Performance on Patient Safety and 30‐Day Mortality and Unplanned Readmission for Medicare Fee‐for‐Service Patients With Acute Myocardial Infarction
Wang Y, Eldridge N, Metersky ML, Sonnenfeld N, Fine JM, Pandolfi MM, Eckenrode S, Bakullari A, Galusha DH, Jaser L, Verzier NR, Nuti SV, Hunt D, Normand S, Krumholz HM. Association Between Hospital Performance on Patient Safety and 30‐Day Mortality and Unplanned Readmission for Medicare Fee‐for‐Service Patients With Acute Myocardial Infarction. Journal Of The American Heart Association 2016, 5: e003731. PMID: 27405808, PMCID: PMC5015406, DOI: 10.1161/jaha.116.003731.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overCause of DeathCenters for Medicare and Medicaid Services, U.S.Fee-for-Service PlansFemaleHospitalsHospitals, RuralHospitals, VoluntaryHumansMaleMedicareMortalityMyocardial InfarctionPatient ReadmissionPatient SafetyPrognosisUnited StatesUnited States Agency for Healthcare Research and QualityConceptsAcute myocardial infarctionUnplanned readmission rateMedicare Patient Safety Monitoring SystemRisk-standardized mortalityAdverse eventsReadmission ratesService patientsMedicare feeUnplanned readmissionMyocardial infarctionMedicare patientsPatient safetyHospital performanceMore adverse eventsAdverse event ratesAcute care hospitalsPatient safety dataHospital mortalityAdverse event measuresCause mortalityOccurrence rateCare hospitalHospital characteristicsReadmission dataPatient safety performanceAssociation of Admission to Veterans Affairs Hospitals vs Non–Veterans Affairs Hospitals With Mortality and Readmission Rates Among Older Men Hospitalized With Acute Myocardial Infarction, Heart Failure, or Pneumonia
Nuti SV, Qin L, Rumsfeld JS, Ross JS, Masoudi FA, Normand SL, Murugiah K, Bernheim SM, Suter LG, Krumholz HM. Association of Admission to Veterans Affairs Hospitals vs Non–Veterans Affairs Hospitals With Mortality and Readmission Rates Among Older Men Hospitalized With Acute Myocardial Infarction, Heart Failure, or Pneumonia. JAMA 2016, 315: 582-592. PMID: 26864412, PMCID: PMC5459395, DOI: 10.1001/jama.2016.0278.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionNon-VA hospitalsReadmission ratesHeart failureVA hospitalsMortality rateVeterans AffairsMyocardial infarctionOlder menMedicare Standard Analytic FilesRisk-standardized mortality ratesCause readmission rateCause mortality ratesHigher readmission ratesStandard Analytic FilesVeterans Affairs hospitalRisk-standardized readmission ratesAdministrative claims dataAcute care hospitalsAssociation of admissionLittle contemporary informationLower mortality rateCross-sectional analysisAnalysis cohortCare hospital
2015
Predictors of warfarin‐associated adverse events in hospitalized patients: Opportunities to prevent patient harm
Metersky ML, Eldridge N, Wang Y, Jaser L, Bona R, Eckenrode S, Bakullari A, Andrawis M, Classen D, Krumholz HM. Predictors of warfarin‐associated adverse events in hospitalized patients: Opportunities to prevent patient harm. Journal Of Hospital Medicine 2015, 11: 276-282. PMID: 26662851, DOI: 10.1002/jhm.2528.Peer-Reviewed Original ResearchConceptsAdverse eventsWarfarin-related adverse eventsHospitalized patientsOdds ratioINR monitoringPneumonia patientsINR measurementsFrequent INR monitoringPredictors of warfarinRetrospective cohort studyAcute cardiac diseaseAcute care hospitalsFrequency of warfarinCohort studyCare hospitalSurgical patientsCardiac patientsCardiac diseasePatientsPatient harmWarfarinSignificant associationINRMore daysMonitoring System dataDevelopment and Validation of an Algorithm to Identify Planned Readmissions From Claims Data
Horwitz LI, Grady JN, Cohen DB, Lin Z, Volpe M, Ngo CK, Masica AL, Long T, Wang J, Keenan M, Montague J, Suter LG, Ross JS, Drye EE, Krumholz HM, Bernheim SM. Development and Validation of an Algorithm to Identify Planned Readmissions From Claims Data. Journal Of Hospital Medicine 2015, 10: 670-677. PMID: 26149225, PMCID: PMC5459369, DOI: 10.1002/jhm.2416.Peer-Reviewed Original ResearchConceptsSame-hospital readmissionsNegative predictive valuePositive predictive valuePredictive valueReadmission measuresHospital-wide readmission measureGold standard chart reviewAdministrative claims-based algorithmDiagnostic cardiac catheterizationClaims-based algorithmLarge teaching centersAcute care hospitalsSmall community hospitalUnplanned readmissionChart reviewCardiac catheterizationScheduled careSpecificity 96.5Community hospitalReadmissionClaims dataCardiac devicesHealth systemTeaching centerPublic reportingAssociation of hospital volume with readmission rates: a retrospective cross-sectional study
Horwitz LI, Lin Z, Herrin J, Bernheim S, Drye EE, Krumholz HM, Hines HJ, Ross JS. Association of hospital volume with readmission rates: a retrospective cross-sectional study. The BMJ 2015, 350: h447. PMID: 25665806, PMCID: PMC4353286, DOI: 10.1136/bmj.h447.Peer-Reviewed Original ResearchConceptsReadmission ratesHospital volumeRetrospective cross-sectional studyUS acute care hospitalsHospital readmission ratesAcute care hospitalsCross-sectional studyMedical cancer treatmentCare hospitalAdult dischargesHospital characteristicsMedicare feeCancer treatmentHospitalAssociationDaysService dataPatientsCardiovascularGynecologyQuintileNeurology
2013
Trends in Intracranial Stenting Among Medicare Beneficiaries in the United States, 2006–2010
Gupta A, Desai MM, Kim N, Bulsara KR, Wang Y, Krumholz HM. Trends in Intracranial Stenting Among Medicare Beneficiaries in the United States, 2006–2010. Journal Of The American Heart Association 2013, 2: e000084. PMID: 23588099, PMCID: PMC3647283, DOI: 10.1161/jaha.113.000084.Peer-Reviewed Original ResearchConceptsIntracranial stentingMortality rateService beneficiariesICD-9-CM procedure codesPrincipal discharge diagnosis codeOverall hospitalization rateDischarge diagnosis codesHumanitarian Device Exemption approvalAcute care hospitalsHumanitarian Device ExemptionCare hospitalIntracranial angioplastyHospitalization ratesICS useSubarachnoid hemorrhageDiagnosis codesOperative rateProcedure ratesMedicare feeMedicare beneficiariesInsufficient evidenceICS procedureDrug AdministrationCerebral aneurysmsMedicaid ServicesIncome inequality and 30 day outcomes after acute myocardial infarction, heart failure, and pneumonia: retrospective cohort study
Lindenauer PK, Lagu T, Rothberg MB, Avrunin J, Pekow PS, Wang Y, Krumholz HM. Income inequality and 30 day outcomes after acute myocardial infarction, heart failure, and pneumonia: retrospective cohort study. The BMJ 2013, 346: f521. PMID: 23412830, PMCID: PMC3573180, DOI: 10.1136/bmj.f521.Peer-Reviewed Original ResearchConceptsIncome inequalityAcute myocardial infarctionUS statesRetrospective cohort studyDay of admissionHeart failureMyocardial infarctionCohort studyInequality levelsIndividual incomeGini coefficientUS acute care hospitalsHighest quarterDays of dischargeDays of hospitalizationRisk of readmissionRisk of deathPatient socioeconomic characteristicsRisk of mortalityAcute care hospitalsSocioeconomic characteristicsInequalityLogistic regression modelsCare hospitalReadmission analysis
2012
Hospital strategies for reducing risk-standardized mortality rates in acute myocardial infarction.
Bradley EH, Curry LA, Spatz ES, Herrin J, Cherlin EJ, Curtis JP, Thompson JW, Ting HH, Wang Y, Krumholz HM. Hospital strategies for reducing risk-standardized mortality rates in acute myocardial infarction. Annals Of Internal Medicine 2012, 156: 618-26. PMID: 22547471, PMCID: PMC3386642, DOI: 10.7326/0003-4819-156-9-201205010-00003.Peer-Reviewed Original ResearchConceptsRisk-standardized mortality ratesAcute myocardial infarctionLower risk-standardized mortality ratesMyocardial infarctionNurse championsMortality rateHospital strategiesHospital risk-standardized mortality ratesHospital-level factorsIntensive care unitAcute care hospitalsCardiac catheterization laboratoryCross-sectional surveyUnited Health FoundationCare hospitalCare unitCross-sectional designAMI casesAMI volumeCatheterization laboratoryHospital cliniciansHospitalMultivariate analysisPatientsHealth FoundationComparison of hospital risk-standardized mortality rates calculated by using in-hospital and 30-day models: an observational study with implications for hospital profiling.
Drye EE, Normand SL, Wang Y, Ross JS, Schreiner GC, Han L, Rapp M, Krumholz HM. Comparison of hospital risk-standardized mortality rates calculated by using in-hospital and 30-day models: an observational study with implications for hospital profiling. Annals Of Internal Medicine 2012, 156: 19-26. PMID: 22213491, PMCID: PMC3319769, DOI: 10.7326/0003-4819-156-1-201201030-00004.Peer-Reviewed Original ResearchConceptsRisk-standardized mortality ratesAcute myocardial infarctionHospital risk-standardized mortality ratesHospital mortality measuresHeart failureMortality rateObservational studyNonfederal acute care hospitalsMortality measuresAcute care hospitalsMean LOSPrimary outcomeStandardized followCare hospitalBlood InstituteService patientsMyocardial infarctionNational HeartPatient LOSMedicare feePneumoniaHospitalAdmissionHospital qualityHospital profiling
2011
National and Regional Trends in Heart Failure Hospitalization and Mortality Rates for Medicare Beneficiaries, 1998-2008
Chen J, Normand SL, Wang Y, Krumholz HM. National and Regional Trends in Heart Failure Hospitalization and Mortality Rates for Medicare Beneficiaries, 1998-2008. JAMA 2011, 306: 1669-1678. PMID: 22009099, PMCID: PMC3688069, DOI: 10.1001/jama.2011.1474.Peer-Reviewed Original ResearchConceptsHF hospitalization ratesHeart failure hospitalizationHospitalization ratesMortality rateFailure hospitalizationHeart failure hospitalization ratesPrincipal discharge diagnosis codeOne-year mortality rateDischarge diagnosis codesIschemic heart diseaseAcute care hospitalsService Medicare beneficiariesLower ratesBlack menHF hospitalizationPatient demographicsCare hospitalDiagnosis codesHeart diseaseRisk factorsMedicare beneficiariesHospitalizationStudy periodMortalityNational mean
2010
The performance of US hospitals as reflected in risk‐standardized 30‐day mortality and readmission rates for medicare beneficiaries with pneumonia
Lindenauer PK, Bernheim SM, Grady JN, Lin Z, Wang Y, Wang Y, Merrill AR, Han LF, Rapp MT, Drye EE, Normand S, Krumholz HM. The performance of US hospitals as reflected in risk‐standardized 30‐day mortality and readmission rates for medicare beneficiaries with pneumonia. Journal Of Hospital Medicine 2010, 5: e12-e18. PMID: 20665626, DOI: 10.1002/jhm.822.Peer-Reviewed Original ResearchConceptsRisk-standardized mortality ratesReadmission ratesHospital referral regionsReferral regionsMedicare beneficiariesMortality rateRisk-standardized readmission ratesNonfederal acute care hospitalsNational quality improvement effortsPattern of hospitalAcute care hospitalsCross-sectional studyService Medicare beneficiariesQuality improvement effortsMedian hospitalHospital dischargeElderly patientsHospital admissionCare hospitalReadmission analysisOutpatient MedicareLeading causePrincipal diagnosisPneumoniaPatientsIs Same-Hospital Readmission Rate a Good Surrogate for All-Hospital Readmission Rate?
Nasir K, Lin Z, Bueno H, Normand SL, Drye EE, Keenan PS, Krumholz HM. Is Same-Hospital Readmission Rate a Good Surrogate for All-Hospital Readmission Rate? Medical Care 2010, 48: 477-481. PMID: 20393366, DOI: 10.1097/mlr.0b013e3181d5fb24.Peer-Reviewed Original ResearchConceptsRisk-standardized readmission ratesHospital readmission ratesSame-hospital readmissionsSame-hospital readmission ratesDays of dischargeReadmission ratesHeart failureUS acute care hospitalsThirty-day readmissionStandard Analytic FilesAcute care hospitalsHierarchical logistic regression modelsLogistic regression modelsCause readmissionHF readmissionIndex hospitalizationCare hospitalHospital readmissionAnalytic FilesMedicare inpatientReadmissionStudy populationHospital measuresReadmission measuresHospitalization