Featured Publications
Population well-being and electoral shifts
Herrin J, Witters D, Roy B, Riley C, Liu D, Krumholz HM. Population well-being and electoral shifts. PLOS ONE 2018, 13: e0193401. PMID: 29529049, PMCID: PMC5846778, DOI: 10.1371/journal.pone.0193401.Peer-Reviewed Original ResearchMeSH KeywordsAdultHealth StatusHealth SurveysHumansMental HealthPoliticsSocioeconomic FactorsUnited States
2019
Income disparities in needle biopsy patients prior to breast cancer surgery across physician peer groups
Killelea BK, Herrin J, Soulos PR, Pollack CE, Forman HP, Yu J, Xu X, Tannenbaum S, Wang SY, Gross CP. Income disparities in needle biopsy patients prior to breast cancer surgery across physician peer groups. Breast Cancer 2019, 27: 381-388. PMID: 31792804, PMCID: PMC7512133, DOI: 10.1007/s12282-019-01028-4.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overBiopsy, NeedleBreast NeoplasmsFemaleFollow-Up StudiesHumansIncomeMastectomyPhysiciansPrognosisSEER ProgramSocioeconomic FactorsConceptsPhysician peer groupsLow-income patientsNeedle biopsyOdds ratioHigh-income patientsBreast cancer surgeryMethodsThe SurveillanceCancer surgeryIncome patientsMedicare databaseBiopsy patientsMedicare beneficiariesPatientsBiopsyLow incomeGroupDisparitiesReceiptEnd resultHigher incomeSurgeryPeer groupEpidemiologyFurther workGroup-level effectsAssociations between community well-being and hospitalisation rates: results from a cross-sectional study within six US states
Roy B, Riley C, Herrin J, Spatz E, Hamar B, Kell KP, Rula EY, Krumholz H. Associations between community well-being and hospitalisation rates: results from a cross-sectional study within six US states. BMJ Open 2019, 9: e030017. PMID: 31780588, PMCID: PMC6886944, DOI: 10.1136/bmjopen-2019-030017.Peer-Reviewed Original ResearchMeSH KeywordsAge FactorsAgedCross-Sectional StudiesFemaleHealth StatusHospitalizationHumansMaleMiddle AgedQuality of LifeSocioeconomic FactorsUnited StatesConceptsHospitalisation ratesZip codesPrimary care physician densityCross-sectional study SETTINGCancer-related admissionsRespiratory-related admissionsCross-sectional studyQuality of lifeRace/ethnicityCause hospitalisationSecondary outcomesPrimary outcomeHighest quintileUnnecessary hospitalisationAdmission ratesSD increaseHospitalisationLife benefitsPhysician densityStudy settingMain independent variableBeing IndexHospital bedsAdmissionGallup-Sharecare WellThe Value of Interracial Contact for Reducing Anti-Black Bias Among Non-Black Physicians: A Cognitive Habits and Growth Evaluation (CHANGE) Study Report
Onyeador IN, Wittlin NM, Burke SE, Dovidio JF, Perry SP, Hardeman RR, Dyrbye LN, Herrin J, Phelan SM, van Ryn M. The Value of Interracial Contact for Reducing Anti-Black Bias Among Non-Black Physicians: A Cognitive Habits and Growth Evaluation (CHANGE) Study Report. Psychological Science 2019, 31: 18-30. PMID: 31743078, PMCID: PMC6966250, DOI: 10.1177/0956797619879139.Peer-Reviewed Original ResearchMeSH KeywordsBlack or African AmericanCurriculumEducation, Medical, GraduateFemaleHealthcare DisparitiesHumansInternship and ResidencyInterprofessional RelationsLongitudinal StudiesMalePhysician-Patient RelationsPrejudiceRacismRegression AnalysisSchools, MedicalSocioeconomic FactorsStudents, MedicalUnited StatesConceptsAnti-Black biasNon-Black physiciansInterracial contactImplicit biasDiversity trainingImplicit racial biasQuality of contactPrejudice reductionBaseline biasCognitive habitsRacial biasLongitudinal studyRacial climateImpactful experiencesTrainingMedical school environmentBiasPrevious contactMedical residencySchoolsPrejudiceExperienceMedical schoolsInquiryDisparities in Socioeconomic Context and Association With Blood Pressure Control and Cardiovascular Outcomes in ALLHAT
Shahu A, Herrin J, Dhruva SS, Desai NR, Davis BR, Krumholz HM, Spatz ES. Disparities in Socioeconomic Context and Association With Blood Pressure Control and Cardiovascular Outcomes in ALLHAT. Journal Of The American Heart Association 2019, 8: e012277. PMID: 31362591, PMCID: PMC6761647, DOI: 10.1161/jaha.119.012277.Peer-Reviewed Original ResearchConceptsBlood pressure controlLow-income sitesCardiovascular outcomesPressure controlALLHAT participantsPoor blood pressure controlEnd-stage renal diseaseHospitalization/mortalityAdverse cardiovascular eventsCardiovascular risk factorsWorse cardiovascular outcomesHigh blood pressureStandardized treatment protocolRandomized clinical trialsBackground Observational studiesLow socioeconomic statusHighest income quintileAngina hospitalizationCardiovascular eventsCause mortalityCoronary revascularizationClinical characteristicsBlood pressureRenal diseaseClinical outcomesDo pregnant women living in higher well-being populations in the USA experience lower risk of preterm delivery? A cross-sectional study
Riley C, Roy B, Herrin J, Spatz E, Silvestri MT, Arora A, Kell KP, Rula EY, Krumholz HM. Do pregnant women living in higher well-being populations in the USA experience lower risk of preterm delivery? A cross-sectional study. BMJ Open 2019, 9: e024143. PMID: 31048427, PMCID: PMC6501974, DOI: 10.1136/bmjopen-2018-024143.Peer-Reviewed Original ResearchMeSH KeywordsAdultCross-Sectional StudiesFemaleGestational AgeHumansPregnancyPremature BirthRisk FactorsSocioeconomic FactorsUnited StatesYoung AdultConceptsPreterm birthCross-sectional studyIndividual risk factorsPreterm deliveryRisk factorsPregnant womenLower riskMaternal risk factorsPrimary outcome measurePrimary independent variableGestational ageMaternal riskOutcome measuresUS birthsHealth StatisticsBirth dataBeing IndexWomenBirthGallup-Sharecare WellLower ratesQuintileRiskDeliveryPopulation
2018
Identifying county characteristics associated with resident well-being: A population based study
Roy B, Riley C, Herrin J, Spatz ES, Arora A, Kell KP, Welsh J, Rula EY, Krumholz HM. Identifying county characteristics associated with resident well-being: A population based study. PLOS ONE 2018, 13: e0196720. PMID: 29791476, PMCID: PMC5965855, DOI: 10.1371/journal.pone.0196720.Peer-Reviewed Original ResearchConceptsCounty-level factorsClinical careCross-sectional studyQuality of lifeBetter health outcomesMulti-dimensional assessmentHealth outcomesBeing IndexGallup-Sharecare WellUS residentsCareCounty characteristicsSurvey participantsResident wellUS countiesScoresCounty equivalentsAssessmentFactorsCohortPhysician peer group characteristics and timeliness of breast cancer surgery
Bachand J, Soulos PR, Herrin J, Pollack CE, Xu X, Ma X, Gross CP. Physician peer group characteristics and timeliness of breast cancer surgery. Breast Cancer Research And Treatment 2018, 170: 657-665. PMID: 29693229, PMCID: PMC6048589, DOI: 10.1007/s10549-018-4789-8.Peer-Reviewed Original ResearchConceptsPhysician peer groupsSurgical delayProvider densityPatient racial compositionBreast cancerEnd Results-Medicare dataBreast cancer patientsBreast cancer surgeryResultsThe study sampleConclusionsThe likelihoodBlack patientsCancer surgeryCancer patientsSurgeryPatientsStudy sampleWomenCancerAssociationGroupGroup characteristicsPurposeLittleInterdisciplinary groupPeer groupEpidemiology
2017
Regional Medicare Expenditures and Survival Among Older Women With Localized Breast Cancer
Tannenbaum S, Soulos PR, Herrin J, Mougalian S, Long JB, Wang R, Ma X, Gross CP, Xu X. Regional Medicare Expenditures and Survival Among Older Women With Localized Breast Cancer. Medical Care 2017, 55: 1030-1038. PMID: 29068906, PMCID: PMC5863278, DOI: 10.1097/mlr.0000000000000822.Peer-Reviewed Original ResearchConceptsBreast cancer careHospital referral regionsNonmetastatic breast cancerBreast cancerCancer careMedicare beneficiariesMedicare expendituresCancer expendituresBetter survivalEnd Results-MedicareRetrospective cohort studyPatients 3 yearsClinical characteristicsCohort studyOverall survivalCancer stagePatient outcomesOutcome measuresReferral regionsOlder womenSignificant associationStage IIBivariate analysisCancerQuintileEffectiveness of a Decision Aid in Potentially Vulnerable Patients: A Secondary Analysis of the Chest Pain Choice Multicenter Randomized Trial
Rising K, Hollander J, Schaffer J, Kline J, Torres C, Diercks D, Jones R, Owen K, Meisel Z, Demers M, Leblanc A, Shah N, Inselman J, Herrin J, Montori V, Hess E. Effectiveness of a Decision Aid in Potentially Vulnerable Patients: A Secondary Analysis of the Chest Pain Choice Multicenter Randomized Trial. Medical Decision Making 2017, 38: 69-78. PMID: 28525723, DOI: 10.1177/0272989x17706363.Peer-Reviewed Original ResearchConceptsUsual careHealth literacySecondary analysisAcute coronary syndromeDecision aidOne-thirdChest painCoronary syndromePatient characteristicsSDM interventionsIntervention groupVulnerable patientsHigh school educationPatientsControl groupPhysician trustPatient trustSubgroup effectsArm assignmentVulnerable subgroupsSociodemographic groupsMulticenterTrialsSimilar extentPhysicians
2015
Do Non-Clinical Factors Improve Prediction of Readmission Risk? Results From the Tele-HF Study
Krumholz HM, Chaudhry SI, Spertus JA, Mattera JA, Hodshon B, Herrin J. Do Non-Clinical Factors Improve Prediction of Readmission Risk? Results From the Tele-HF Study. JACC Heart Failure 2015, 4: 12-20. PMID: 26656140, PMCID: PMC5459404, DOI: 10.1016/j.jchf.2015.07.017.Peer-Reviewed Original ResearchConceptsReadmission ratesPatient-reported informationHeart failureHealth statusReadmission riskC-statisticRisk scorePsychosocial variablesMedical record abstractionWeeks of dischargeReadmission risk modelNon-clinical factorsCandidate risk factorsReadmission risk predictionRecord abstractionClinical variablesPatient interviewsMedical recordsRisk factorsPatientsPsychosocial informationPsychosocial characteristicsTelephone interviewsRisk predictionScoresMedical School Experiences Associated with Change in Implicit Racial Bias Among 3547 Students: A Medical Student CHANGES Study Report
van Ryn M, Hardeman R, Phelan SM, PhD D, Dovidio JF, Herrin J, Burke SE, Nelson DB, Perry S, Yeazel M, Przedworski JM. Medical School Experiences Associated with Change in Implicit Racial Bias Among 3547 Students: A Medical Student CHANGES Study Report. Journal Of General Internal Medicine 2015, 30: 1748-1756. PMID: 26129779, PMCID: PMC4636581, DOI: 10.1007/s11606-015-3447-7.Peer-Reviewed Original ResearchMeSH KeywordsAdultAttitude of Health PersonnelBlack or African AmericanCurriculumEducation, Medical, UndergraduateFemaleHealthcare DisparitiesHumansInterprofessional RelationsLongitudinal StudiesMaleMiddle AgedPhysician-Patient RelationsRacismSchools, MedicalSocioeconomic FactorsStudents, MedicalYoung AdultConceptsMedical schoolsSelf-assessed skillsBlack-White Implicit Association TestSchool experiencesLast semesterMedical school experienceU.S. medical schoolsImplicit racial attitudesRole model behaviorsInformal curriculumRacial biasFormal curriculumStudent reportsFirst semesterMedical educationRacial attitudesRacial climateImplicit racial biasSchoolsAfrican American physiciansCultural competenceSemesterCurriculumNegative commentsStudentsThe Role of Patient Factors, Cancer Characteristics, and Treatment Patterns in the Cost of Care for Medicare Beneficiaries with Breast Cancer
Xu X, Herrin J, Soulos PR, Saraf A, Roberts KB, Killelea BK, Wang SY, Long JB, Wang R, Ma X, Gross CP. The Role of Patient Factors, Cancer Characteristics, and Treatment Patterns in the Cost of Care for Medicare Beneficiaries with Breast Cancer. Health Services Research 2015, 51: 167-186. PMID: 26119176, PMCID: PMC4722219, DOI: 10.1111/1475-6773.12328.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overBreast NeoplasmsComorbidityFemaleHealth ExpendituresHumansMedicareRetrospective StudiesSEER ProgramSocioeconomic FactorsUnited StatesConceptsBreast cancer careHospital referral regionsCancer careMedicare expendituresBreast cancerRadiation therapyTreatment factorsMean Medicare expendituresEnd Results-MedicareSpecific treatment modalitiesContribution of patientCost of careHighest spending quintilePatient factorsTreatment patternsTumor characteristicsCancer characteristicsTreatment modalitiesReferral regionsMedicare beneficiariesQuintilePatientsCancerCareTherapyAssessing Community Quality of Health Care
Herrin J, Kenward K, Joshi MS, Audet AM, Hines SJ. Assessing Community Quality of Health Care. Health Services Research 2015, 51: 98-116. PMID: 26096649, PMCID: PMC4722214, DOI: 10.1111/1475-6773.12322.Peer-Reviewed Original ResearchConceptsHospital service areasNursing homesHospital measuresHospital qualityHigh hospital qualityHealth system factorsAgreement of measuresHigh-quality careHigh-quality hospitalsHome health agenciesDimensions of careComposite quality measureGeneral practitionersCare settingsNH careHealth agenciesQuality hospitalsHospitalCareHealth careSystem factorsAvailable quality measuresQuality measuresHigh differSettingChanging trends in type 2 diabetes mellitus treatment intensification, 2002-2010.
McCoy RG, Zhang Y, Herrin J, Denton BT, Mason JE, Montori VM, Smith SA, Shah ND. Changing trends in type 2 diabetes mellitus treatment intensification, 2002-2010. The American Journal Of Managed Care 2015, 21: e288-96. PMID: 26167776.Peer-Reviewed Original ResearchMeSH KeywordsAdministration, OralAdolescentAdultAge FactorsAgedBlood GlucoseComorbidityDiabetes Mellitus, Type 2Drug Therapy, CombinationFemaleGlycated HemoglobinHumansHypoglycemic AgentsIncretinsInsurance Claim ReviewMaleMetforminMiddle AgedResidence CharacteristicsRetrospective StudiesSex FactorsSocioeconomic FactorsSulfonylurea CompoundsUnited StatesYoung AdultConceptsTreatment intensificationCox proportional hazards regression analysisNational administrative data setProportional hazards regression analysisRetrospective secondary data analysisDiabetes treatment intensificationOptimal diabetes careHazards regression analysisDiabetes-related complicationsAdults 18 yearsTreatment-naïve adultsNon-Hispanic whitesComorbidity burdenMetformin monotherapySulfonylurea useMetformin prescriptionThiazolidinedione useGlycemic controlKaplan-MeierMean ageDiabetes careSignificant confoundersSecondary data analysisAdministrative data setsDiabetes therapy
2014
Community Factors and Hospital Readmission Rates
Herrin J, St. Andre J, Kenward K, Joshi MS, Audet A, Hines SC. Community Factors and Hospital Readmission Rates. Health Services Research 2014, 50: 20-39. PMID: 24712374, PMCID: PMC4319869, DOI: 10.1111/1475-6773.12177.Peer-Reviewed Original ResearchConceptsHospital readmission ratesReadmission ratesAcute myocardial infarctionHeart failureRisk-standardized readmission ratesHigher readmission ratesCommunity factorsCounty characteristicsNursing Home CompareArea Resource FileMultivariable analysisMeasures of accessMyocardial infarctionCounty demographicsHospitalStrong associationStudy sampleResource FilePneumoniaInfarctionPatientsFactorsNational variationsCareRate
2012
The Adoption of New Adjuvant Radiation Therapy Modalities Among Medicare Beneficiaries With Breast Cancer: Clinical Correlates and Cost Implications
Roberts KB, Soulos PR, Herrin J, Yu JB, Long JB, Dostaler E, Gross CP. The Adoption of New Adjuvant Radiation Therapy Modalities Among Medicare Beneficiaries With Breast Cancer: Clinical Correlates and Cost Implications. International Journal Of Radiation Oncology • Biology • Physics 2012, 85: 1186-1192. PMID: 23182396, PMCID: PMC3606652, DOI: 10.1016/j.ijrobp.2012.10.009.Peer-Reviewed Original ResearchConceptsExternal beam radiation therapyRadiation therapy modalitiesRadiation therapy costsBreast cancerRadiation therapyTherapy modalitiesTherapy costsBrachytherapy useRadiation oncologistsEnd Results-Medicare databaseConventional external beam radiation therapyAdoption of intensityBreast-conserving surgeryRadiation therapy useUse of IMRTBeam radiation therapyNewer radiation therapy modalitiesHierarchical logistic regressionHospital-based facilitiesTherapy useClinical factorsClinical correlatesTreatment optionsTreatment choicePhysician preference
2004
Racial and Ethnic Differences in Time to Acute Reperfusion Therapy for Patients Hospitalized With Myocardial Infarction
Bradley EH, Herrin J, Wang Y, McNamara RL, Webster TR, Magid DJ, Blaney M, Peterson ED, Canto JG, Pollack CV, Krumholz HM. Racial and Ethnic Differences in Time to Acute Reperfusion Therapy for Patients Hospitalized With Myocardial Infarction. JAMA 2004, 292: 1563-1572. PMID: 15467058, DOI: 10.1001/jama.292.13.1563.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAngioplasty, Balloon, CoronaryAsian PeopleBlack PeopleFemaleHispanic or LatinoHospitalsHumansInsurance, HospitalizationMaleMiddle AgedMyocardial InfarctionOutcome Assessment, Health CarePatient AdmissionRetrospective StudiesSocioeconomic FactorsThrombolytic TherapyTime and Motion StudiesTime FactorsUnited StatesWhite PeopleConceptsST-segment elevation myocardial infarctionAcute reperfusion therapyElevation myocardial infarctionMyocardial infarctionReperfusion therapyAfrican American/BlackBalloon timeInsurance statusAmerican/BlackEthnic differencesPercutaneous coronary interventionBundle branch blockAsian/Pacific IslandersHealth care disparitiesRace/ethnicity differencesRace/ethnicityClinical characteristicsCoronary interventionFibrinolytic therapyHospital arrivalNonwhite patientsPrimary reperfusionWhite patientsUS cohortHospital characteristicsHospital-Level Performance Improvement
Bradley EH, Herrin J, Mattera JA, Holmboe ES, Wang Y, Frederick P, Roumanis SA, Radford MJ, Krumholz HM. Hospital-Level Performance Improvement. Medical Care 2004, 42: 591-599. PMID: 15167327, DOI: 10.1097/01.mlr.0000128006.27364.a9.Peer-Reviewed Original ResearchMeSH KeywordsAdrenergic beta-AntagonistsAgedAmerican Hospital AssociationCardiology Service, HospitalComorbidityDrug Utilization ReviewFemaleGeographyGuideline AdherenceHealth Care SurveysHumansLogistic ModelsMaleMiddle AgedMyocardial InfarctionPatient DischargeQuality Assurance, Health CareRegistriesSocioeconomic FactorsUnited StatesConceptsBeta-blocker useAcute myocardial infarctionHospital-level variationHospital characteristicsMyocardial infarctionBeta-blocker prescription ratesHospital-level changesHospital-level ratesAmerican Hospital Association Annual SurveyClinical characteristicsPrescription ratesNational registryAMI volumeHospital ratesRate of improvementImprovement rateTeaching statusIndividual hospitalsInfarctionHospitalNational surveyPercentage pointsTime periodUse ratesWeak predictor