2021
Out‐of‐pocket Annual Health Expenditures and Financial Toxicity from Healthcare Costs in Patients with Heart Failure in the United States
Wang SY, Valero‐Elizondo J, Ali H, Pandey A, Cainzos‐Achirica M, Krumholz HM, Nasir K, Khera R. Out‐of‐pocket Annual Health Expenditures and Financial Toxicity from Healthcare Costs in Patients with Heart Failure in the United States. Journal Of The American Heart Association 2021, 10: e022164. PMID: 33998273, PMCID: PMC8483501, DOI: 10.1161/jaha.121.022164.Peer-Reviewed Original ResearchConceptsGreater risk-adjusted oddsRisk-adjusted oddsHeart failureMedical Expenditure Panel SurveyCatastrophic financial burdenPocket healthcare expensesHigh financial burdenFinancial toxicityHealthcare expensesFinancial burdenHealthcare costsCatastrophic burdenMajor public health burdenLow-income familiesBackground Heart failurePublic health burdenInsurance premiumsPanel SurveyPocket healthcare costsAnnual health expenditureWorld Health OrganizationConclusions PatientsHealth insurance premiumsPocket healthcare expenditureHealth burden
2020
Identifying characteristics of high-poverty counties in the United States with high well-being: an observational cross-sectional study
Arora A, Spatz ES, Herrin J, Riley C, Roy B, Rula EY, Kell KP, Krumholz HM. Identifying characteristics of high-poverty counties in the United States with high well-being: an observational cross-sectional study. BMJ Open 2020, 10: e035645. PMID: 32948545, PMCID: PMC7500307, DOI: 10.1136/bmjopen-2019-035645.Peer-Reviewed Original ResearchConceptsObservational cross-sectional studyCross-sectional studyHigh-poverty countiesMean wellRobert Wood Johnson Foundation County Health RankingsLow physical inactivityPrimary care physiciansCounty characteristicsPopulation health modelCounty Health RankingsPreventable hospital staysHospital stayCare physiciansHighest quartilePhysical inactivityHigh percentageMAIN OUTCOMELow prevalenceIndex scoreHeavy drinkersHealth RankingsPopulation-level measuresHealth modelBottom quintileTop quintile
2018
Association of Out-of-Pocket Annual Health Expenditures With Financial Hardship in Low-Income Adults With Atherosclerotic Cardiovascular Disease in the United States
Khera R, Valero-Elizondo J, Okunrintemi V, Saxena A, Das SR, de Lemos JA, Krumholz HM, Nasir K. Association of Out-of-Pocket Annual Health Expenditures With Financial Hardship in Low-Income Adults With Atherosclerotic Cardiovascular Disease in the United States. JAMA Cardiology 2018, 3: 729-738. PMID: 29971325, PMCID: PMC6143078, DOI: 10.1001/jamacardio.2018.1813.Peer-Reviewed Original ResearchConceptsCatastrophic financial burdenLow-income familiesPocket health care expensesHigh financial burdenMedical Expenditure Panel SurveyHealth care expensesFamily incomeFinancial burdenPanel SurveyHealth expensesMean annual family incomePocket expensesCare expensesFinancial hardshipAtherosclerotic cardiovascular diseaseLow incomePocket health expensesAssociation of OutAnnual family incomeFederal poverty limitHigh-income familiesAnnual health expenditureLow-income adultsInsurance premiumsHealth expenditureIdentifying 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 equivalentsAssessmentFactorsCohort
2016
Population Well-Being Measures Help Explain Geographic Disparities In Life Expectancy At The County Level
Arora A, Spatz E, Herrin J, Riley C, Roy B, Kell K, Coberley C, Rula E, Krumholz HM. Population Well-Being Measures Help Explain Geographic Disparities In Life Expectancy At The County Level. Health Affairs 2016, 35: 2075-2082. PMID: 27834249, PMCID: PMC5150263, DOI: 10.1377/hlthaff.2016.0715.Peer-Reviewed Original Research
2015
Race, Socioeconomic Status, and Life Expectancy After Acute Myocardial Infarction
Bucholz EM, Ma S, Normand SL, Krumholz HM. Race, Socioeconomic Status, and Life Expectancy After Acute Myocardial Infarction. Circulation 2015, 132: 1338-1346. PMID: 26369354, PMCID: PMC5097251, DOI: 10.1161/circulationaha.115.017009.Peer-Reviewed Original Research
2014
STEMI Care in LMIC Obstacles and Opportunities
Murugiah K, Nuti SV, Krumholz HM. STEMI Care in LMIC Obstacles and Opportunities. Global Heart 2014, 9: 429-430. PMID: 25592797, PMCID: PMC5459383, DOI: 10.1016/j.gheart.2014.08.010.Commentaries, Editorials and Letters
2013
Income 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
2005
The impact of socioeconomic status and race on trial participation for older women with breast cancer
Gross CP, Filardo G, Mayne ST, Krumholz HM. The impact of socioeconomic status and race on trial participation for older women with breast cancer. Cancer 2005, 103: 483-491. PMID: 15597407, DOI: 10.1002/cncr.20792.Peer-Reviewed Original ResearchMeSH KeywordsAgedAsianBlack or African AmericanBreast NeoplasmsCase-Control StudiesClinical Trials as TopicFemaleHispanic or LatinoHumansLogistic ModelsMedicaidMultivariate AnalysisNational Institutes of Health (U.S.)Odds RatioPatient SelectionPovertySEER ProgramUnemploymentUnited StatesWhite PeopleConceptsBreast cancer trialsTrial participationOlder womenBreast cancerSocioeconomic statusMedicaid insuranceTrial enrollmentCancer patientsCancer trialsMultivariable logistic regression modelBreast cancer patientsMedicaid insurance coverageAssociation of SESHigh-poverty zip codesCase-control studyPopulation-based sampleLow socioeconomic statusLogistic regression modelsImpact of SESWhite patientsBlack patientsSEER areasBlack raceElderly womenTrial participants