2015
Development of a Hospital Outcome Measure Intended for Use With Electronic Health Records
McNamara RL, Wang Y, Partovian C, Montague J, Mody P, Eddy E, Krumholz HM, Bernheim SM. Development of a Hospital Outcome Measure Intended for Use With Electronic Health Records. Medical Care 2015, 53: 818-826. PMID: 26225445, DOI: 10.1097/mlr.0000000000000402.Peer-Reviewed Original ResearchConceptsElectronic health recordsOutcome measuresClinical dataMortality rateClinical practiceFuture quality improvement measuresRisk-standardized mortality ratesHospital risk-standardized mortality ratesLow-mortality hospitalsHealth recordsSystolic blood pressureOdds of mortalityClinical registry dataAcute myocardial infarctionHigh-mortality hospitalsHospital outcome measuresEHR dataFinal risk modelCurrent clinical practiceStandard clinical practiceFirst outcome measureNational Quality ForumCurrent electronic health recordsQuality improvement measuresChart abstraction
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
Development of 2 Registry-Based Risk Models Suitable for Characterizing Hospital Performance on 30-Day All-Cause Mortality Rates Among Patients Undergoing Percutaneous Coronary Intervention
Curtis JP, Geary LL, Wang Y, Chen J, Drye EE, Grosso LM, Spertus JA, Rumsfeld JS, Weintraub WS, Masoudi FA, Brindis RG, Krumholz HM. Development of 2 Registry-Based Risk Models Suitable for Characterizing Hospital Performance on 30-Day All-Cause Mortality Rates Among Patients Undergoing Percutaneous Coronary Intervention. Circulation Cardiovascular Quality And Outcomes 2012, 5: 628-637. PMID: 22949491, DOI: 10.1161/circoutcomes.111.964569.Peer-Reviewed Original ResearchMeSH KeywordsAcute Coronary SyndromeAgedAged, 80 and overAngina PectorisChi-Square DistributionComorbidityFemaleHeart DiseasesHospital MortalityHospitalsHumansLogistic ModelsMaleMyocardial InfarctionOdds RatioOutcome and Process Assessment, Health CarePercutaneous Coronary InterventionQuality Indicators, Health CareRegistriesRisk AssessmentRisk FactorsShock, CardiogenicTime FactorsTreatment OutcomeUnited StatesConceptsST-segment elevation myocardial infarctionPercutaneous coronary interventionRisk-standardized mortality ratesElevation myocardial infarctionPatient mortality ratesMyocardial infarctionMortality rateCardiogenic shockCoronary interventionDerivation cohortHospital risk-standardized mortality ratesCause mortality ratesAdministrative claims dataQuality of careHierarchical logistic regression modelsNational Quality ForumLogistic regression modelsObserved mortality rateCathPCI RegistryNational HospitalClaims dataInfarctionPatientsQuality ForumFinal model
2009
Recent National Trends in Readmission Rates After Heart Failure Hospitalization
Ross JS, Chen J, Lin Z, Bueno H, Curtis JP, Keenan PS, Normand SL, Schreiner G, Spertus JA, Vidán MT, Wang Y, Wang Y, Krumholz HM. Recent National Trends in Readmission Rates After Heart Failure Hospitalization. Circulation Heart Failure 2009, 3: 97-103. PMID: 19903931, PMCID: PMC2830811, DOI: 10.1161/circheartfailure.109.885210.Peer-Reviewed Original ResearchConceptsCause readmission rateReadmission ratesHeart failureRecent national trendsHospital variationService beneficiariesAcute-care nonfederal hospitalsUS acute care hospitalsHeart failure hospitalizationHospital readmission ratesAcute care hospitalsNational trendsNational Quality ForumMedicare administrative dataDistinct hospitalizationsFailure hospitalizationMultiple comorbiditiesCare hospitalNonfederal hospitalsMedicare beneficiariesHospitalizationHospitalQuality ForumStudy periodAdministrative data
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