Featured Publications
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
2024
Racial and Ethnic Disparities in Age-Specific All-Cause Mortality During the COVID-19 Pandemic
Faust J, Renton B, Bongiovanni T, Chen A, Sheares K, Du C, Essien U, Fuentes-Afflick E, Haywood T, Khera R, King T, Li S, Lin Z, Lu Y, Marshall A, Ndumele C, Opara I, Loarte-Rodriguez T, Sawano M, Taparra K, Taylor H, Watson K, Yancy C, Krumholz H. Racial and Ethnic Disparities in Age-Specific All-Cause Mortality During the COVID-19 Pandemic. JAMA Network Open 2024, 7: e2438918. PMID: 39392630, PMCID: PMC11581672, DOI: 10.1001/jamanetworkopen.2024.38918.Peer-Reviewed Original ResearchConceptsCOVID-19 public health emergencyNon-HispanicPublic health emergencyOther Pacific IslanderExcess mortalityAlaska NativesUS populationExcess deathsRates of excess mortalityCross-sectional study analyzed dataYears of potential lifeMortality relative riskNon-Hispanic whitesCross-sectional studyPacific IslandersStudy analyzed dataAll-cause mortalityEthnic groupsMortality disparitiesMortality ratioTotal populationDeath certificatesEthnic disparitiesMain OutcomesDecedent ageProcedure Volume and Outcomes With WATCHMAN Left Atrial Appendage Occlusion
Friedman D, Du C, Zimmerman S, Tan Z, Lin Z, Vemulapalli S, Kosinski A, Piccini J, Pereira L, Minges K, Faridi K, Masoudi F, Curtis J, Freeman J. Procedure Volume and Outcomes With WATCHMAN Left Atrial Appendage Occlusion. Circulation Cardiovascular Interventions 2024, 17: e013466. PMID: 38889251, PMCID: PMC11189610, DOI: 10.1161/circinterventions.123.013466.Peer-Reviewed Original ResearchConceptsVolume-outcome relationshipLikelihood of procedural successLeft atrial appendage occlusionProcedural successProcedure volumeAppendage occlusionNational Cardiovascular Data Registry LAAO RegistryVolume quartilesLeft atrial appendage occlusion devicesThree-level hierarchical generalized linear modelsMinimum volume thresholdsWatchman FLX deviceProcedural success rateHierarchical generalized linear modelsAssociated with outcomePhysician volumeWATCHMAN procedureFLX deviceOcclusion deviceVolume thresholdCardiovascular proceduresPhysiciansHospitalNational analysisSuccess rate
2020
Post-discharge acute care and outcomes following readmission reduction initiatives: national retrospective cohort study of Medicare beneficiaries in the United States
Khera R, Wang Y, Bernheim SM, Lin Z, Krumholz HM. Post-discharge acute care and outcomes following readmission reduction initiatives: national retrospective cohort study of Medicare beneficiaries in the United States. The BMJ 2020, 368: l6831. PMID: 31941686, PMCID: PMC7190056, DOI: 10.1136/bmj.l6831.Peer-Reviewed Original ResearchConceptsAcute care utilizationAcute myocardial infarctionRetrospective cohort studyHeart failureCare utilizationPost-discharge periodEmergency departmentMyocardial infarctionDay mortalityCohort studyHospital admissionObservation unitAcute careNational retrospective cohort studyPost-acute care utilizationHospital Readmissions Reduction ProgramObservation unit carePost-discharge mortalityDay readmission rateRisk of deathReadmissions Reduction ProgramReadmission reduction initiativesReadmission ratesUnit careInpatient unit
2019
Comparative Effectiveness of New Approaches to Improve Mortality Risk Models From Medicare Claims Data
Krumholz HM, Coppi AC, Warner F, Triche EW, Li SX, Mahajan S, Li Y, Bernheim SM, Grady J, Dorsey K, Lin Z, Normand ST. Comparative Effectiveness of New Approaches to Improve Mortality Risk Models From Medicare Claims Data. JAMA Network Open 2019, 2: e197314. PMID: 31314120, PMCID: PMC6647547, DOI: 10.1001/jamanetworkopen.2019.7314.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionICD-9-CM codesMortality risk modelHeart failureHospital admissionC-statisticMAIN OUTCOMEMortality rateRisk-standardized mortality ratesHospital risk-standardized mortality ratesIndex admission diagnosisPatients 65 yearsDays of hospitalizationComparative effectiveness studiesClaims-based dataHospital-level performance measuresMedicare claims dataPatient-level modelsCMS modelRisk-adjustment modelsRisk modelHospital performance measuresAdmission diagnosisNinth RevisionMyocardial infarction
2018
The influence of sociodemographic factors on operative decision-making in small bowel obstruction
Jean RA, Chiu AS, O'Neill KM, Lin Z, Pei KY. The influence of sociodemographic factors on operative decision-making in small bowel obstruction. Journal Of Surgical Research 2018, 227: 137-144. PMID: 29804845, DOI: 10.1016/j.jss.2018.02.029.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overClinical Decision-MakingDigestive System Surgical ProceduresFemaleHealth Care CostsHealthcare DisparitiesHospitalizationHumansInpatientsInsurance CoverageIntestinal ObstructionIntestine, SmallLength of StayMaleMiddle AgedPractice Guidelines as TopicRacial GroupsRetrospective StudiesSocioeconomic FactorsTime-to-TreatmentUnited StatesYoung AdultConceptsSmall bowel obstructionOperative managementOperative delaySociodemographic factorsBowel obstructionHospital factorsInsurance statusMedicare patientsUtilization Project National Inpatient SampleMedicare insurance coverageOverall study populationNational Inpatient SampleHospital mortalityNonoperative therapyNonoperative managementHospital clusteringPrimary outcomeHispanic patientsBlack patientsPrimary diagnosisInpatient SampleCurrent guidelinesSociodemographic disparitiesStudy populationHealthcare costsDefining Multiple Chronic Conditions for Quality Measurement
Drye EE, Altaf FK, Lipska KJ, Spatz ES, Montague JA, Bao H, Parzynski CS, Ross JS, Bernheim SM, Krumholz HM, Lin Z. Defining Multiple Chronic Conditions for Quality Measurement. Medical Care 2018, 56: 193-201. PMID: 29271820, DOI: 10.1097/mlr.0000000000000853.Peer-Reviewed Original ResearchConceptsMultiple chronic conditionsChronic conditionsMedicare feeService beneficiariesMedicare Chronic Conditions WarehouseMCC cohortBroad cohortChronic Conditions WarehouseRisk-standardized ratesNational quality measuresUnplanned admissionsFinal cohortTotal admissionsAdmission riskAccountable care organizationsAdmission ratesOutcome measuresAdmissionCohortCohort conditionCare organizationsPatientsStakeholder inputNarrow cohortBeneficiaries
2017
Hospital Characteristics Associated With Risk-standardized Readmission Rates
Horwitz LI, Bernheim SM, Ross JS, Herrin J, Grady JN, Krumholz HM, Drye EE, Lin Z. Hospital Characteristics Associated With Risk-standardized Readmission Rates. Medical Care 2017, 55: 528-534. PMID: 28319580, PMCID: PMC5426655, DOI: 10.1097/mlr.0000000000000713.Peer-Reviewed Original ResearchIdentification of Emergency Department Visits in Medicare Administrative Claims: Approaches and Implications
Venkatesh AK, Mei H, Kocher KE, Granovsky M, Obermeyer Z, Spatz E, Rothenberg C, Krumholz H, Lin Z. Identification of Emergency Department Visits in Medicare Administrative Claims: Approaches and Implications. Academic Emergency Medicine 2017, 24: 422-431. PMID: 27864915, PMCID: PMC5905698, DOI: 10.1111/acem.13140.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overClinical CodingEmergency Service, HospitalFemaleHospitalizationHumansMaleMedicareUnited StatesConceptsED visitsEmergency department visitsClaims-based definitionED visitationAdministrative claimsDepartment visitsClaims dataAdministrative claims data setsHealthcare resource utilizationMore ED visitsAcute care practiceAdministrative claims dataQuality improvement interventionsEmergency care researchMedicare administrative claimsClaims data setsED useCritical careED servicesMedicare feeMedicare dataCare practicesService beneficiariesImprovement interventionsProvider definitions
2016
Declining Admission Rates And Thirty-Day Readmission Rates Positively Associated Even Though Patients Grew Sicker Over Time
Dharmarajan K, Qin L, Lin Z, Horwitz LI, Ross JS, Drye EE, Keshawarz A, Altaf F, Normand SL, Krumholz HM, Bernheim SM. Declining Admission Rates And Thirty-Day Readmission Rates Positively Associated Even Though Patients Grew Sicker Over Time. Health Affairs 2016, 35: 1294-1302. PMID: 27385247, DOI: 10.1377/hlthaff.2015.1614.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overCenters for Medicare and Medicaid Services, U.S.Chronic DiseaseDatabases, FactualDisease ProgressionFemaleGeriatric AssessmentHospital MortalityHumansIncidenceLength of StayMaleOutcome Assessment, Health CarePatient AdmissionPatient ReadmissionRetrospective StudiesRisk AssessmentSeverity of Illness IndexTime FactorsUnited States
2014
Variation in Hospital-Level Risk-Standardized Complication Rates Following Elective Primary Total Hip and Knee Arthroplasty
Bozic KJ, Grosso LM, Lin Z, Parzynski CS, Suter LG, Krumholz HM, Lieberman JR, Berry DJ, Bucholz R, Han L, Rapp MT, Bernheim S, Drye EE. Variation in Hospital-Level Risk-Standardized Complication Rates Following Elective Primary Total Hip and Knee Arthroplasty. Journal Of Bone And Joint Surgery 2014, 96: 640-647. PMID: 24740660, DOI: 10.2106/jbjs.l.01639.Peer-Reviewed Original ResearchConceptsElective total hip arthroplastyTotal hip arthroplastyComplication rateBlack patientsStudy cohortTKA proceduresMedicaid patientsU.S. hospitalsMedicare feeElective primary total hip arthroplastyPrimary total hip arthroplastyElective primary total hipTotal knee arthroplasty proceduresPrimary total hipPeriprosthetic joint infectionKnee arthroplasty proceduresNational Medicare feeHigher proportionHospital-level riskNational Quality ForumCross-sectional analysisHierarchical logistic regressionTKA patientsCommon complicationPatient comorbidities
2012
Skilled Nursing Facility Referral and Hospital Readmission Rates after Heart Failure or Myocardial Infarction
Chen J, Ross JS, Carlson MD, Lin Z, Normand SL, Bernheim SM, Drye EE, Ling SM, Han LF, Rapp MT, Krumholz HM. Skilled Nursing Facility Referral and Hospital Readmission Rates after Heart Failure or Myocardial Infarction. The American Journal Of Medicine 2012, 125: 100.e1-100.e9. PMID: 22195535, PMCID: PMC3246370, DOI: 10.1016/j.amjmed.2011.06.011.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionRisk-standardized readmission ratesSkilled nursing facilitiesHeart failureHospital-level variationReadmission ratesMyocardial infarctionRate of dischargeHospital-level readmission ratesSubstantial hospital-level variationService Medicare patientsCause readmission rateRisk of readmissionHospital readmission ratesHF admissionsRegression modelsAMI patientsFacility referralPrincipal diagnosisMedicare patientsMedicare claimsClaims dataAMI admissionsAMI hospitalizationNursing facilities
2011
An Administrative Claims Measure Suitable for Profiling Hospital Performance Based on 30-Day All-Cause Readmission Rates Among Patients With Acute Myocardial Infarction
Krumholz HM, Lin Z, Drye EE, Desai MM, Han LF, Rapp MT, Mattera JA, Normand SL. An Administrative Claims Measure Suitable for Profiling Hospital Performance Based on 30-Day All-Cause Readmission Rates Among Patients With Acute Myocardial Infarction. Circulation Cardiovascular Quality And Outcomes 2011, 4: 243-252. PMID: 21406673, PMCID: PMC3350811, DOI: 10.1161/circoutcomes.110.957498.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overCohort StudiesFemaleHumansInsurance Claim ReviewLogistic ModelsMaleMedicareModels, StatisticalMyocardial InfarctionOutcome and Process Assessment, Health CareOutcome Assessment, Health CarePatient ReadmissionQuality of Health CareReproducibility of ResultsRisk FactorsTime FactorsUnited States
2007
Changes in outcomes for internal medicine inpatients after work-hour regulations.
Horwitz LI, Kosiborod M, Lin Z, Krumholz HM. Changes in outcomes for internal medicine inpatients after work-hour regulations. Annals Of Internal Medicine 2007, 147: 97-103. PMID: 17548401, DOI: 10.7326/0003-4819-147-2-200707170-00163.Peer-Reviewed Original ResearchConceptsIntensive care unit utilizationLength of stayDrug-drug interactionsWork-hour regulationsNonteaching servicesHospital deathPharmacist interventionsReadmission ratesConsecutive patientsRetrospective cohort studyInternal medicine patientsInternal medicine inpatientsUnit utilizationAdverse drug-drug interactionsTeaching serviceAcademic medical centerCohort studyDischarge dispositionMedicine inpatientsMedicine patientsFatigue-related errorsMedical CenterRehabilitation facilityRate of dischargePatients
2003
Gender differences in recovery after coronary artery bypass surgery
Vaccarino V, Lin ZQ, Kasl SV, Mattera JA, Roumanis SA, Abramson JL, Krumholz HM. Gender differences in recovery after coronary artery bypass surgery. Journal Of The American College Of Cardiology 2003, 41: 307-314. PMID: 12535827, DOI: 10.1016/s0735-1097(02)02698-0.Peer-Reviewed Original ResearchConceptsPhysical functionCABG surgeryDepressive symptomsHospital readmissionCoronary artery bypass graft surgeryArtery bypass graft surgeryCoronary artery bypass surgeryBypass graft surgeryArtery bypass surgeryCongestive heart failureLow physical functionMore depressive symptomsFirst CABGGraft surgeryBaseline characteristicsBypass surgeryPatient characteristicsHeart failureIllness severityMedical recordsWorse outcomesClinical dataFemale genderHigh riskSide effects