2021
Incorporating Present-on-Admission Indicators in Medicare Claims to Inform Hospital Quality Measure Risk Adjustment Models
Triche EW, Xin X, Stackland S, Purvis D, Harris A, Yu H, Grady JN, Li SX, Bernheim SM, Krumholz HM, Poyer J, Dorsey K. Incorporating Present-on-Admission Indicators in Medicare Claims to Inform Hospital Quality Measure Risk Adjustment Models. JAMA Network Open 2021, 4: e218512. PMID: 33978722, PMCID: PMC8116982, DOI: 10.1001/jamanetworkopen.2021.8512.Peer-Reviewed Original ResearchConceptsPOA indicatorRisk factorsOutcome measuresQuality outcome measuresRisk-adjustment modelsClaims dataAdmission indicatorsPatient risk factorsAcute myocardial infarctionPatient-level outcomesAdministrative claims dataQuality improvement studyClaims-based measuresComparative effectiveness studiesPatient claims dataInternational Statistical ClassificationMortality outcome measuresRelated Health ProblemsHospital quality measuresRisk model performanceHospital stayIndex admissionCare algorithmHeart failureMortality outcomes
2020
Quality Measure Public Reporting Is Associated with Improved Outcomes Following Hip and Knee Replacement.
Bozic K, Yu H, Zywiel MG, Li L, Lin Z, Simoes JL, Dorsey Sheares K, Grady J, Bernheim SM, Suter LG. Quality Measure Public Reporting Is Associated with Improved Outcomes Following Hip and Knee Replacement. Journal Of Bone And Joint Surgery 2020, 102: 1799-1806. PMID: 33086347, DOI: 10.2106/jbjs.19.00964.Peer-Reviewed Original ResearchConceptsRisk-standardized readmission ratesTotal hip arthroplastyReadmission ratesPublic reportingFiscal year 2010Hospital-level outcomesPrognostic Level IIIHospital-level ratesFiscal year 2016Hospital-level performanceHospital coding practicesHospital-level risk-standardized readmission ratesTKA patientsComplication rateClinical outcomesReadmission modelsImproved outcomesHip arthroplastyKnee replacementMedicare beneficiariesLevel IIIComplicationsReplacement proceduresInterquartile rangeOutcomesImpact of left ventricular assist devices and heart transplants on acute myocardial infarction and heart failure mortality and readmission measures
Brandt EJ, Ross JS, Grady JN, Ahmad T, Pawar S, Bernheim SM, Desai NR. Impact of left ventricular assist devices and heart transplants on acute myocardial infarction and heart failure mortality and readmission measures. PLOS ONE 2020, 15: e0230734. PMID: 32214363, PMCID: PMC7098556, DOI: 10.1371/journal.pone.0230734.Peer-Reviewed Original ResearchConceptsLeft ventricular assist deviceHeart transplantation patientsRisk-standardized mortalityHeart transplantationTransplantation patientsAMI cohortReadmission cohortHF cohortVentricular assist deviceAMI mortalityAssist deviceHeart failure mortalityAcute myocardial infarctionHF mortalityLVAD indicationHF patientsLVAD patientsReadmission ratesHeart transplantMyocardial infarctionPrimary diagnosisReadmission measuresMedicare feeChronic supportPatients
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 OUTCOMEComparative 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 infarctionTrends in Hospital Readmission of Medicare-Covered Patients With Heart Failure
Blecker S, Herrin J, Li L, Yu H, Grady JN, Horwitz LI. Trends in Hospital Readmission of Medicare-Covered Patients With Heart Failure. Journal Of The American College Of Cardiology 2019, 73: 1004-1012. PMID: 30846093, PMCID: PMC7011858, DOI: 10.1016/j.jacc.2018.12.040.Peer-Reviewed Original ResearchConceptsHospital Readmissions Reduction ProgramSecondary heart failureReadmission ratesHeart failureReadmissions Reduction ProgramHF hospitalizationAffordable Care ActMedicare's Hospital Readmissions Reduction ProgramRisk-adjusted readmission ratesCause readmission rateHigher readmission ratesAcute myocardial infarctionCare ActReduction programsLinear spline regression modelsPneumonia hospitalizationsHospital readmissionMedicare hospitalizationsRetrospective studySecondary diagnosisMyocardial infarctionPrincipal diagnosisHospitalizationSpline regression modelsPatients
2018
Effect of Hospital Readmission Reduction on Patients at Low, Medium, and High Risk of Readmission in the Medicare Population
Blecker S, Herrin J, Kwon JY, Grady JN, Jones S, Horwitz LI. Effect of Hospital Readmission Reduction on Patients at Low, Medium, and High Risk of Readmission in the Medicare Population. Journal Of Hospital Medicine 2018, 13: 537-543. PMID: 29455229, PMCID: PMC6063766, DOI: 10.12788/jhm.2936.Peer-Reviewed Original ResearchVariation in the Diagnosis of Aspiration Pneumonia and Association with Hospital Pneumonia Outcomes
Lindenauer PK, Strait KM, Grady JN, Ngo CK, Parisi ML, Metersky M, Ross JS, Bernheim SM, Dorsey K. Variation in the Diagnosis of Aspiration Pneumonia and Association with Hospital Pneumonia Outcomes. Annals Of The American Thoracic Society 2018, 15: 562-569. PMID: 29298090, DOI: 10.1513/annalsats.201709-728oc.Peer-Reviewed Original ResearchConceptsAspiration pneumoniaHospital mortalityHospital patientsMortality rateLower risk-standardized mortality ratesRisk-standardized mortality ratesRisk-standardized ratesPatients 65 yearsHospital readmission ratesNational mortality ratesPneumonia cohortPneumonia outcomesHospital outcomesReadmission ratesHospital differencesPrincipal diagnosisOutcome measuresReadmission measuresHospital codingMedicare feePneumoniaService claimsPatientsMedian proportionMortality
2017
Trends in readmission rates for safety net hospitals and non-safety net hospitals in the era of the US Hospital Readmission Reduction Program: a retrospective time series analysis using Medicare administrative claims data from 2008 to 2015
Salerno AM, Horwitz LI, Kwon JY, Herrin J, Grady JN, Lin Z, Ross JS, Bernheim SM. Trends in readmission rates for safety net hospitals and non-safety net hospitals in the era of the US Hospital Readmission Reduction Program: a retrospective time series analysis using Medicare administrative claims data from 2008 to 2015. BMJ Open 2017, 7: e016149. PMID: 28710221, PMCID: PMC5541519, DOI: 10.1136/bmjopen-2017-016149.Peer-Reviewed Original ResearchConceptsHospital Readmissions Reduction ProgramNon-safety net hospitalsSafety-net hospitalMedicare administrative claims dataReadmission ratesAdministrative claims dataNet hospitalReadmissions Reduction ProgramRetrospective time series analysisSafety netClaims dataTime series analysisSocioeconomic statusUnplanned readmission ratePrincipal discharge diagnosisLow socioeconomic statusInterrupted time seriesReduction programsFive-digit zip codeSeries analysisHRRP penaltiesIndex admissionHospital proportionDischarge diagnosisService patientsHospital 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 Research
2014
Development and use of an administrative claims measure for profiling hospital-wide performance on 30-day unplanned readmission.
Horwitz LI, Partovian C, Lin Z, Grady JN, Herrin J, Conover M, Montague J, Dillaway C, Bartczak K, Suter LG, Ross JS, Bernheim SM, Krumholz HM, Drye EE. Development and use of an administrative claims measure for profiling hospital-wide performance on 30-day unplanned readmission. Annals Of Internal Medicine 2014, 161: s66-75. PMID: 25402406, PMCID: PMC4235629, DOI: 10.7326/m13-3000.Peer-Reviewed Original ResearchConceptsUnplanned readmissionReadmission measuresReadmission ratesReadmission riskMedicare feeHospital-wide readmission measureRisk-standardized readmission ratesPayer dataAdministrative Claims MeasureRisk-standardized ratesAverage-risk patientsUnplanned readmission rateDays of dischargeHospital risk-standardized readmission ratesAdult hospitalizationsComorbid conditionsPrincipal diagnosisClaims dataService claimsService beneficiariesReadmissionMeasure development studiesMedicaid ServicesRisk adjustmentHospitalNational Patterns of Risk-Standardized Mortality and Readmission After Hospitalization for Acute Myocardial Infarction, Heart Failure, and Pneumonia: Update on Publicly Reported Outcomes Measures Based on the 2013 Release
Suter LG, Li SX, Grady JN, Lin Z, Wang Y, Bhat KR, Turkmani D, Spivack SB, Lindenauer PK, Merrill AR, Drye EE, Krumholz HM, Bernheim SM. National Patterns of Risk-Standardized Mortality and Readmission After Hospitalization for Acute Myocardial Infarction, Heart Failure, and Pneumonia: Update on Publicly Reported Outcomes Measures Based on the 2013 Release. Journal Of General Internal Medicine 2014, 29: 1333-1340. PMID: 24825244, PMCID: PMC4175654, DOI: 10.1007/s11606-014-2862-5.Peer-Reviewed Original ResearchConceptsRisk-standardized mortality ratesAcute myocardial infarctionHeart failurePneumonia mortalityMyocardial infarctionMedian risk-standardized mortality rateHospital-level mortalityUnplanned readmission ratePrincipal discharge diagnosisHospital performanceRisk-Standardized MortalityHF mortalityReadmission resultsReadmission ratesDischarge diagnosisOutcome measuresAMI mortalityReadmission measuresPneumoniaMortality rateService MedicareHierarchical logistic modelsMortalityMedicaid ServicesReadmission
2010
National Patterns of Risk-Standardized Mortality and Readmission for Acute Myocardial Infarction and Heart Failure
Bernheim SM, Grady JN, Lin Z, Wang Y, Wang Y, Savage SV, Bhat KR, Ross JS, Desai MM, Merrill AR, Han LF, Rapp MT, Drye EE, Normand SL, Krumholz HM. National Patterns of Risk-Standardized Mortality and Readmission for Acute Myocardial Infarction and Heart Failure. Circulation Cardiovascular Quality And Outcomes 2010, 3: 459-467. PMID: 20736442, PMCID: PMC3027304, DOI: 10.1161/circoutcomes.110.957613.Peer-Reviewed Original Research
2003
Burden of Illness Score for Elderly Persons
Inouye SK, Bogardus ST, Vitagliano G, Desai MM, Williams CS, Grady JN, Scinto JD. Burden of Illness Score for Elderly Persons. Medical Care 2003, 41: 70-83. PMID: 12544545, DOI: 10.1097/00005650-200301000-00010.Peer-Reviewed Original ResearchMeSH KeywordsAge FactorsAgedAged, 80 and overCohort StudiesComorbidityCost of IllnessFemaleFollow-Up StudiesForecastingGeriatric AssessmentHealth StatusHospitalizationHospitals, TeachingHumansMaleMortalityPneumoniaProbabilityProportional Hazards ModelsRisk AdjustmentRisk FactorsSeverity of Illness IndexSex FactorsSurvival AnalysisTime FactorsConceptsGroup IHazard ratioIllness scoresOverall mortalityC-statisticElderly personsHospitalized older personsHigh-risk diagnosesRisk adjustment indexProspective cohortValidation cohortDevelopment cohortUniversity HospitalPhysiologic abnormalitiesRisk factorsFunctional impairmentRisk groupsMedicine serviceMortality predictionMortality rateGroup IICohortOlder personsFinal modelGroup III
2001
Screening Mammography: Is It Suitably Targeted to Older Women Who are Most Likely to Benefit?
Scinto J, Gill T, Grady J, Holmboe E. Screening Mammography: Is It Suitably Targeted to Older Women Who are Most Likely to Benefit? Journal Of The American Geriatrics Society 2001, 49: 1101-1104. PMID: 11555074, DOI: 10.1046/j.1532-5415.2001.49216.x.Peer-Reviewed Original ResearchConceptsOlder womenPrognostic groupsPrognostic stageMammography useCommunity-dwelling older womenFavorable prognostic groupFive-year mortalityProspective cohort studyWorst prognostic groupMammography use ratesCause mortalityCohort studyElderly ProgramEpidemiologic studiesNew Haven CountyMedicare Part BScreening mammographyWomenMortalityMortality indexMammographyUse ratesNew HavenMammogramsPart BQuality of Care for Hospitalized Medicare Patients at Risk for Pressure Ulcers
Lyder C, Preston J, Grady J, Scinto J, Allman R, Bergstrom N, Rodeheaver G. Quality of Care for Hospitalized Medicare Patients at Risk for Pressure Ulcers. JAMA Internal Medicine 2001, 161: 1549-1554. PMID: 11427104, DOI: 10.1001/archinte.161.12.1549.Peer-Reviewed Original ResearchMeSH KeywordsAge DistributionAgedAged, 80 and overCase-Control StudiesCohort StudiesFemaleGuideline AdherenceHospital UnitsHumansIncidenceLength of StayMaleMedicarePressure UlcerProcess Assessment, Health CareQuality Indicators, Health CareRetrospective StudiesRisk AssessmentSex DistributionUnited StatesConceptsProcess of careDaily skin assessmentPressure ulcersPressure ulcer predictionNutritional consultationSkin assessmentMedicare patientsPressure-reducing devicesUS hospitalsMulticenter retrospective cohort studyStage 1 pressure ulcersState's peer review organizationKaplan-Meier survival analysisNutritional risk factorsRetrospective cohort studyCongestive heart failureMedical record abstractionAcute care hospitalsPressure ulcer developmentQuality of careCohort studyCare hospitalHeart failureRecord abstractionPeer review organizations
2000
The Effect of a Multifaceted Physician Office‐Based Intervention on Older Women's Mammography Use
Preston J, Scinto J, Grady J, Schulz A, Petrillo M. The Effect of a Multifaceted Physician Office‐Based Intervention on Older Women's Mammography Use. Journal Of The American Geriatrics Society 2000, 48: 1-7. PMID: 10642013, DOI: 10.1111/j.1532-5415.2000.tb03020.x.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsAgedAmbulatory CareConnecticutFemaleHealth Knowledge, Attitudes, PracticeHumansLogistic ModelsMaleMammographyMass ScreeningMedical AuditMedicare Part BMiddle AgedOffice VisitsPatient Acceptance of Health CarePatient Education as TopicProgram EvaluationReferral and ConsultationTotal Quality ManagementUnited StatesWomenConceptsHealth Care Quality Improvement ProgramMammography useMammography referralWomen's mammography useMammography ratesIntervention sampleMammography recommendationsPhysician's officeCommunity-based physician officesPhysician opinion leadersPhysicians' mammography recommendationsPrimary care visitsFemale Medicare beneficiariesIntervention programsLower mammography useQuality Improvement ProgramCommunity physician practicesProportion of womenPhysician remindersIntervention patientsCare visitsControl physiciansPatient adherenceAcademic detailingRestricted cohort
1998
The Impact of a Physician Intervention Program on Older Women's Mammography Use
Preston J, Grady J, Schulz A, Petrillo M, Scinto J. The Impact of a Physician Intervention Program on Older Women's Mammography Use. Evaluation & The Health Professions 1998, 21: 502-513. PMID: 10351562, DOI: 10.1177/016327879802100408.Peer-Reviewed Original ResearchConceptsConnecticut Peer Review OrganizationMammography useMammography ratesOlder womenMore interventionsAnnual mammography ratesConnecticut Tumor RegistryLower mammography ratesIntervention programsWomen's mammography usePeer review organizationsTumor RegistryScreening ratesPhysician interventionBreast cancerPrior historyReferral effortsAbsolute increaseWomenReview organizationsInterventionRelative increaseRegistryCancerPhysicians