2021
Leveraging Remote Physiologic Monitoring in the COVID-19 Pandemic to Improve Care After Cardiovascular Hospitalizations
Dey P, Jarrin R, Mori M, Geirsson A, Krumholz HM. Leveraging Remote Physiologic Monitoring in the COVID-19 Pandemic to Improve Care After Cardiovascular Hospitalizations. Circulation Cardiovascular Quality And Outcomes 2021, 14: e007618-e007618. PMID: 33820445, PMCID: PMC8059759, DOI: 10.1161/circoutcomes.120.007618.Peer-Reviewed Original Research
2020
Stroke Code Presentations, Interventions, and Outcomes Before and During the COVID-19 Pandemic
Jasne AS, Chojecka P, Maran I, Mageid R, Eldokmak M, Zhang Q, Nystrom K, Vlieks K, Askenase M, Petersen N, Falcone GJ, Wira CR, Lleva P, Zeevi N, Narula R, Amin H, Navaratnam D, Loomis C, Hwang DY, Schindler J, Hebert R, Matouk C, Krumholz HM, Spudich S, Sheth KN, Sansing LH, Sharma R. Stroke Code Presentations, Interventions, and Outcomes Before and During the COVID-19 Pandemic. Stroke 2020, 51: 2664-2673. PMID: 32755347, PMCID: PMC7446978, DOI: 10.1161/str.0000000000000347.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overBetacoronavirusBrain IschemiaCohort StudiesComorbidityConnecticutCoronary Artery DiseaseCoronavirus InfectionsCOVID-19DyslipidemiasEmergency Medical ServicesEthnicityFemaleHumansHypertensionIncomeInsurance, HealthIntracranial HemorrhagesMaleMedically UninsuredMiddle AgedOutcome and Process Assessment, Health CarePandemicsPneumonia, ViralRetrospective StudiesSARS-CoV-2Severity of Illness IndexStrokeSubstance-Related DisordersTelemedicineThrombectomyThrombolytic TherapyTime-to-TreatmentConceptsComprehensive stroke centerStroke codePatient characteristicsStroke severityStroke code patientsHistory of hypertensionStroke-like symptomsCoronary artery diseaseCoronavirus disease 2019 (COVID-19) pandemicPatient-level dataLower median household incomePublic health initiativesDisease 2019 pandemicCOVID-19 pandemicRace/ethnicityCode patientsHospital presentationPublic health insuranceRankin ScaleStroke centersArtery diseaseReperfusion timeStroke symptomsEarly outcomesConnecticut hospitalsTrends and Predictors of Use of Digital Health Technology in the United States
Mahajan S, Lu Y, Spatz ES, Nasir K, Krumholz HM. Trends and Predictors of Use of Digital Health Technology in the United States. The American Journal Of Medicine 2020, 134: 129-134. PMID: 32717188, DOI: 10.1016/j.amjmed.2020.06.033.Peer-Reviewed Original ResearchAvailability of Telemedicine Services Across Hospitals in the United States in 2018: A Cross-sectional Study
Jain S, Khera R, Lin Z, Ross JS, Krumholz HM. Availability of Telemedicine Services Across Hospitals in the United States in 2018: A Cross-sectional Study. Annals Of Internal Medicine 2020, 173: m20-1201. PMID: 32353106, PMCID: PMC7212823, DOI: 10.7326/m20-1201.Commentaries, Editorials and LettersMeSH KeywordsCross-Sectional StudiesHealth Services AccessibilityHospitalsHumansTelemedicineUnited States
2019
Effects of Mobile Text Messaging on Glycemic Control in Patients With Coronary Heart Disease and Diabetes Mellitus
Huo X, Krumholz HM, Bai X, Spatz ES, Ding Q, Horak P, Zhao W, Gong Q, Zhang H, Yan X, Sun Y, Liu J, Wu X, Guan W, Wang X, Li J, Li X, Spertus JA, Masoudi FA, Zheng X. Effects of Mobile Text Messaging on Glycemic Control in Patients With Coronary Heart Disease and Diabetes Mellitus. Circulation Cardiovascular Quality And Outcomes 2019, 12: e005805. PMID: 31474119, DOI: 10.1161/circoutcomes.119.005805.Peer-Reviewed Original ResearchMeSH KeywordsAgedAsian PeopleBiomarkersBlood GlucoseChinaCoronary DiseaseCulturally Competent CareDiabetes MellitusExerciseFemaleGlycated HemoglobinHealth CommunicationHealthy LifestyleHumansHypoglycemic AgentsMaleMedication AdherenceMiddle AgedMotivationPatient Education as TopicRisk Reduction BehaviorSelf CareSingle-Blind MethodTelemedicineText MessagingTime FactorsTreatment OutcomeConceptsCoronary heart diseaseHeart diseaseGlycemic controlIntervention groupUsual careDiabetes mellitusBlood glucosePhysical activityControl groupText message-based interventionBlood pressure controlProportion of patientsRisk factor managementGood glycemic controlSystolic blood pressureBody mass indexText messaging programsText message interventionMobile health interventionsSecondary outcomesBlood pressurePrimary outcomeLDL cholesterolMass indexMedication adherenceEffect of Text Messaging on Risk Factor Management in Patients With Coronary Heart Disease
Zheng X, Spatz ES, Bai X, Huo X, Ding Q, Horak P, Wu X, Guan W, Chow CK, Yan X, Sun Y, Wang X, Zhang H, Liu J, Li J, Li X, Spertus JA, Masoudi FA, Krumholz HM. Effect of Text Messaging on Risk Factor Management in Patients With Coronary Heart Disease. Circulation Cardiovascular Quality And Outcomes 2019, 12: e005616. PMID: 30998400, DOI: 10.1161/circoutcomes.119.005616.Peer-Reviewed Original ResearchMeSH KeywordsAgedAsian PeopleBlood PressureChinaCoronary DiseaseCulturally Competent CareFemaleHealth Knowledge, Attitudes, PracticeHumansMaleMiddle AgedPatient Education as TopicRisk AssessmentRisk FactorsSecondary PreventionSingle-Blind MethodTelemedicineText MessagingTime FactorsTreatment OutcomeConceptsCoronary heart diseaseSystolic blood pressureBody mass indexBlood pressureHeart diseaseSecondary preventionIntervention groupPhysical activityEnd pointSmoking statusMass indexControl groupPrimary end pointRisk factor controlSecondary end pointsRisk factor managementLDL-C levelsDisease-specific knowledgeMobile phone textMobile health technologyUsual careDiabetes mellitusMedication adherenceRisk factorsFactor management
2017
Design and rationale of the Cardiovascular Health and Text Messaging (CHAT) Study and the CHAT-Diabetes Mellitus (CHAT-DM) Study: two randomised controlled trials of text messaging to improve secondary prevention for coronary heart disease and diabetes
Huo X, Spatz ES, Ding Q, Horak P, Zheng X, Masters C, Zhang H, Irwin ML, Yan X, Guan W, Li J, Li X, Spertus JA, Masoudi FA, Krumholz HM, Jiang L. Design and rationale of the Cardiovascular Health and Text Messaging (CHAT) Study and the CHAT-Diabetes Mellitus (CHAT-DM) Study: two randomised controlled trials of text messaging to improve secondary prevention for coronary heart disease and diabetes. BMJ Open 2017, 7: e018302. PMID: 29273661, PMCID: PMC5778311, DOI: 10.1136/bmjopen-2017-018302.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overBlood PressureChinaCoronary DiseaseDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2ExerciseFemaleGlycated HemoglobinHumansLife StyleMaleMedication AdherenceMiddle AgedMotivationResearch DesignRisk FactorsSecondary PreventionSelf CareSingle-Blind MethodTelemedicineText MessagingYoung AdultConceptsSystolic blood pressureBody mass indexTrials of textProportion of patientsMedication adherencePhysical activitySecondary outcomesPrimary outcomeSmoking cessationCardiovascular healthMellitus StudySecondary coronary heart disease preventionCoronary heart disease preventionLow-density lipoprotein cholesterolUsual scientific forumsBlood pressure controlRisk factor managementHeart disease preventionCoronary heart diseaseMobile health interventionsInstitutional review boardUniversity Institutional Review BoardBehavioral skills modelText messagingBehavioral change techniquesImpact of Telemonitoring on Health Status
Jayaram NM, Khariton Y, Krumholz HM, Chaudhry SI, Mattera J, Tang F, Herrin J, Hodshon B, Spertus JA. Impact of Telemonitoring on Health Status. Circulation Cardiovascular Quality And Outcomes 2017, 10: e004148. PMID: 29237746, PMCID: PMC5776725, DOI: 10.1161/circoutcomes.117.004148.Peer-Reviewed Original ResearchConceptsKansas City Cardiomyopathy QuestionnaireUsual careHealth statusHeart failureKCCQ overall summary scoreRecent heart failure hospitalizationDisease-specific health statusKCCQ overall summaryHeart failure hospitalizationWeeks of dischargeRandomized clinical trialsOverall summary scoreKCCQ scoresNoninvasive TelemonitoringFailure hospitalizationBaseline characteristicsSecondary outcomesTreatment armsClinical trialsSummary scoresPatientsSubscale scoresCareHospitalizationScoresAssessing the reliability of self-reported weight for the management of heart failure: application of fraud detection methods to a randomised trial of telemonitoring
Steventon A, Chaudhry SI, Lin Z, Mattera JA, Krumholz HM. Assessing the reliability of self-reported weight for the management of heart failure: application of fraud detection methods to a randomised trial of telemonitoring. BMC Medical Informatics And Decision Making 2017, 17: 43. PMID: 28420352, PMCID: PMC5395848, DOI: 10.1186/s12911-017-0426-4.Peer-Reviewed Original ResearchConceptsEnd-digit preferenceHeart failureHeart Failure Outcomes trialEffective preventive careCharacteristics of patientsSelf-reported weightHealth care professionalsSix-month trial periodIntervention patientsMore medicationsAccuracy of reportingOutcome trialsTrial enrollmentPreventive careClinical managementUnnecessary treatmentDesign of initiativesCare professionalsPatientsRegistration numberAlert fatigueElectronic medical dataTrial periodTrialsNumber of days
2016
Analysis of Machine Learning Techniques for Heart Failure Readmissions
Mortazavi BJ, Downing NS, Bucholz EM, Dharmarajan K, Manhapra A, Li SX, Negahban SN, Krumholz HM. Analysis of Machine Learning Techniques for Heart Failure Readmissions. Circulation Cardiovascular Quality And Outcomes 2016, 9: 629-640. PMID: 28263938, PMCID: PMC5459389, DOI: 10.1161/circoutcomes.116.003039.Peer-Reviewed Original ResearchChampioning Effectiveness Before Cost-Effectiveness∗
Dhruva SS, Krumholz HM. Championing Effectiveness Before Cost-Effectiveness∗. JACC Heart Failure 2016, 4: 376-379. PMID: 27039130, PMCID: PMC5459398, DOI: 10.1016/j.jchf.2016.02.001.Peer-Reviewed Original Research
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 predictionScoresHospital Variation in Quality of Discharge Summaries for Patients Hospitalized With Heart Failure Exacerbation
Al-Damluji MS, Dzara K, Hodshon B, Punnanithinont N, Krumholz HM, Chaudhry SI, Horwitz LI. Hospital Variation in Quality of Discharge Summaries for Patients Hospitalized With Heart Failure Exacerbation. Circulation Cardiovascular Quality And Outcomes 2015, 8: 77-86. PMID: 25587091, PMCID: PMC4303507, DOI: 10.1161/circoutcomes.114.001227.Peer-Reviewed Original ResearchConceptsDays of dischargeDischarge summary qualityDischarge summariesHeart failureHeart Failure Outcome StudyHeart failure exacerbationHospital-level variationHospital-level performanceSingle-site studyMedian hospitalHospital courseDischarge weightHospital variationVolume statusAdverse outcomesOutcome studiesConsensus conferencePatientsHospitalCare toolsPhysiciansInadequate qualityDaysExacerbationSummaryAssociation of Discharge Summary Quality With Readmission Risk for Patients Hospitalized With Heart Failure Exacerbation
Salim Al-Damluji M, Dzara K, Hodshon B, Punnanithinont N, Krumholz HM, Chaudhry SI, Horwitz LI. Association of Discharge Summary Quality With Readmission Risk for Patients Hospitalized With Heart Failure Exacerbation. Circulation Cardiovascular Quality And Outcomes 2015, 8: 109-111. PMID: 25587092, PMCID: PMC4303529, DOI: 10.1161/circoutcomes.114.001476.Peer-Reviewed Original Research
2010
Telemonitoring in Patients with Heart Failure
Chaudhry SI, Mattera JA, Curtis JP, Spertus JA, Herrin J, Lin Z, Phillips CO, Hodshon BV, Cooper LS, Krumholz HM. Telemonitoring in Patients with Heart Failure. New England Journal Of Medicine 2010, 363: 2301-2309. PMID: 21080835, PMCID: PMC3237394, DOI: 10.1056/nejmoa1010029.Peer-Reviewed Original ResearchConceptsPrimary end pointUsual care groupSecondary end pointsHeart failureEnd pointHeart failure outcomesNumber of hospitalizationsTelephone-based interactive voice response systemUsual careAdverse eventsPatient's clinicianMedian ageCare groupLarge trialsInteractive voice response systemPatientsSmall studyVoice response systemNumber of daysHospitalizationReadmissionTelemonitoringSignificant differencesCliniciansDeath
2007
Randomized Trial of Telemonitoring to Improve Heart Failure Outcomes (Tele-HF): Study Design
Chaudhry SI, Barton B, Mattera J, Spertus J, Krumholz HM. Randomized Trial of Telemonitoring to Improve Heart Failure Outcomes (Tele-HF): Study Design. Journal Of Cardiac Failure 2007, 13: 709-714. PMID: 17996818, PMCID: PMC2702538, DOI: 10.1016/j.cardfail.2007.06.720.Peer-Reviewed Case Reports and Technical NotesConceptsHeart failure outcomesHeart failureClinical statusFailure outcomesDecompensated heart failureHeart failure decompensationCare of patientsPrimary care practicesSelf-reported weightUsual careHospital readmissionDaily symptomsRandomized trialsGeneral cardiologyPatient participationHealth behaviorsCare practicesPatientsFrequent monitoringFavorable effectInterventionOutcomesSymptomsTrialsCareTelemonitoring for Patients With Chronic Heart Failure: A Systematic Review
Chaudhry SI, Phillips CO, Stewart SS, Riegel B, Mattera JA, Jerant AF, Krumholz HM. Telemonitoring for Patients With Chronic Heart Failure: A Systematic Review. Journal Of Cardiac Failure 2007, 13: 56-62. PMID: 17339004, PMCID: PMC1910700, DOI: 10.1016/j.cardfail.2006.09.001.BooksConceptsHeart failure patientsFailure patientsHeart failureHigh-risk heart failure patientsHigh-risk Hispanic populationMonitoring of signsChronic heart failureHeart failure hospitalizationLow-risk patientsDisease managementHigh-quality careFailure hospitalizationNegative studiesSymptom monitoringPatientsHealth statusMEDLINE databaseSystematic reviewQuality carePhysiologic monitoringIntervention typeEvidence baseSimilar effectivenessIntervention costsHispanic population