2024
Shortfalls in Follow-up Albuminuria Quantification After an Abnormal Result on a Urine Protein Dipstick Test.
Xu Y, Shin J, Wallace A, Carrero J, Inker L, Mukhopadhyay A, Blecker S, Horwitz L, Grams M, Chang A. Shortfalls in Follow-up Albuminuria Quantification After an Abnormal Result on a Urine Protein Dipstick Test. Annals Of Internal Medicine 2024 PMID: 39348706, DOI: 10.7326/annals-24-00549.Peer-Reviewed Original ResearchFrom Classification to Governance: Ethical Challenges of Adaptive Learning in Medicine
Griffen Z, Rosen K, Horwitz L, Owens K. From Classification to Governance: Ethical Challenges of Adaptive Learning in Medicine. The American Journal Of Bioethics 2024, 24: 107-109. PMID: 39283393, DOI: 10.1080/15265161.2024.2388721.Peer-Reviewed Original ResearchDifferentiation of Prior SARS-CoV-2 Infection and Postacute Sequelae by Standard Clinical Laboratory Measurements in the RECOVER Cohort.
Erlandson K, Geng L, Selvaggi C, Thaweethai T, Chen P, Erdmann N, Goldman J, Henrich T, Hornig M, Karlson E, Katz S, Kim C, Cribbs S, Laiyemo A, Letts R, Lin J, Marathe J, Parthasarathy S, Patterson T, Taylor B, Duffy E, Haack M, Julg B, Maranga G, Hernandez C, Singer N, Han J, Pemu P, Brim H, Ashktorab H, Charney A, Wisnivesky J, Lin J, Chu H, Go M, Singh U, Levitan E, Goepfert P, Nikolich J, Hsu H, Peluso M, Kelly J, Okumura M, Flaherman V, Quigley J, Krishnan J, Scholand M, Hess R, Metz T, Costantine M, Rouse D, Taylor B, Goldberg M, Marshall G, Wood J, Warren D, Horwitz L, Foulkes A, McComsey G. Differentiation of Prior SARS-CoV-2 Infection and Postacute Sequelae by Standard Clinical Laboratory Measurements in the RECOVER Cohort. Annals Of Internal Medicine 2024, 177: 1209-1221. PMID: 39133923, PMCID: PMC11408082, DOI: 10.7326/m24-0737.Peer-Reviewed Original ResearchPostacute sequelae of SARS-CoV-2 infectionSARS-CoV-2 infectionLaboratory markersSARS-CoV-2Laboratory valuesUrinary albumin-creatinine ratioClinical laboratory markersStandard clinical laboratory testsAlbumin-creatinine ratioClinical laboratory valuesHemoglobin A<sub>1c</sub> (HbA<sub>1c</sub>Clinically useful biomarkersClinical laboratory testsClinical laboratory measurementsPropensity score adjustmentSequelae of SARS-CoV-2 infectionPreexisting diabetesIndex dateMeasured 6 monthsClinical significanceNational Institutes of HealthStudy visitsEnrollment siteRisk factorsClinical biomarkersPrescription Patterns for Sodium-Glucose Cotransporter 2 Inhibitors in U.S. Health Systems
Shin J, Xu Y, Chang A, Carrero J, Flaherty C, Mukhopadhyay A, Inker L, Blecker S, Horwitz L, Grams M. Prescription Patterns for Sodium-Glucose Cotransporter 2 Inhibitors in U.S. Health Systems. Journal Of The American College Of Cardiology 2024, 84: 683-693. PMID: 39142721, DOI: 10.1016/j.jacc.2024.05.057.Peer-Reviewed Original ResearchConceptsSodium-glucose cotransporter 2Class 1A recommendationSodium-glucose cotransporter 2 inhibitor therapyChronic kidney diseaseU.S. health systemHealth systemInhibitor prescriptionHeart failurePrescription ratesInhibitor therapyInhibitor useSodium-glucose cotransporter 2 inhibitorsSodium-glucose cotransporter 2 inhibitor useOptum Labs Data WarehouseProportion of patientsSGLT2 inhibitor usePresence of diabetesRecurrent cardiovascular eventsAtherosclerotic cardiovascular diseaseCotransporter 2Analysis of U.S. dataSevere albuminuriaPrescription patternsCardiovascular eventsCommercial insurancePost–Acute Sequelae of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) After Infection During Pregnancy
Metz T, Reeder H, Clifton R, Flaherman V, Aragon L, Baucom L, Beamon C, Braverman A, Brown J, Cao T, Chang A, Costantine M, Dionne J, Gibson K, Gross R, Guerreros E, Habli M, Hadlock J, Han J, Hess R, Hillier L, Hoffman M, Hoffman M, Hughes B, Jia X, Kale M, Katz S, Laleau V, Mallett G, Mehari A, Mendez-Figueroa H, McComsey G, Monteiro J, Monzon V, Okumura M, Pant D, Pacheco L, Palatnik A, Palomares K, Parry S, Pettker C, Plunkett B, Poppas A, Ramsey P, Reddy U, Rouse D, Saade G, Sandoval G, Sciurba F, Simhan H, Skupski D, Sowles A, Thorp J, Tita A, Wiegand S, Weiner S, Yee L, Horwitz L, Foulkes A, Jacoby V. Post–Acute Sequelae of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) After Infection During Pregnancy. Obstetrics And Gynecology 2024, 144: 411-420. PMID: 38991216, PMCID: PMC11326967, DOI: 10.1097/aog.0000000000005670.Peer-Reviewed Original ResearchSARS-CoV-2 infectionSARS-CoV-2Clinical characteristicsSevere acute respiratory syndrome coronavirus 2Gastrointestinal symptomsAcute respiratory syndrome coronavirus 2Respiratory syndrome coronavirus 2Risk factorsPost-acute sequelae of severe acute respiratory syndrome coronavirus 2Syndrome coronavirus 2Acute SARS-CoV-2 infectionHistory of obesityMulticenter cohort studyAssociated with increased prevalenceMultivariate logistic regression modelPostexertional malaiseCoronavirus 2Median timeAcute infection severityLogistic regression modelsAcute infectionCohort studyPredominant symptomPrimary outcomeStudy visitsAnalysis of Clinical Criteria for Discharge Among Patients Hospitalized for COVID-19: Development and Validation of a Risk Prediction Model
Schnipper J, Oreper S, Hubbard C, Kurbegov D, Egloff S, Najafi N, Valdes G, Siddiqui Z, O.’Leary K, Horwitz L, Lee T, Auerbach A. Analysis of Clinical Criteria for Discharge Among Patients Hospitalized for COVID-19: Development and Validation of a Risk Prediction Model. Journal Of General Internal Medicine 2024, 1-13. PMID: 38937368, DOI: 10.1007/s11606-024-08856-x.Peer-Reviewed Original ResearchTime of dischargeInternal validation setPost-discharge readmissionRisk factorsDays of dischargeRetrospective observational cohort studyIndependent risk factorReceiver operating characteristic curveObservational cohort studyReversible risk factorsAssociated with lower oddsPatients 7Lack of improvementRetrospective studyValidation setFollow-upCohort studyRisk prediction modelReadmission risk scoreAcademic centersPositive testPatientsRisk scoreCOVID-19 respiratory diseaseLower oddsMeasuring Equity in Readmission as a Distinct Assessment of Hospital Performance
Nash K, Weerahandi H, Yu H, Venkatesh A, Holaday L, Herrin J, Lin Z, Horwitz L, Ross J, Bernheim S. Measuring Equity in Readmission as a Distinct Assessment of Hospital Performance. JAMA 2024, 331: 111-123. PMID: 38193960, PMCID: PMC10777266, DOI: 10.1001/jama.2023.24874.Peer-Reviewed Original ResearchConceptsBlack patientsPatient populationHospital characteristicsHospital-wide readmission measureDual-eligible patientsHospital patient populationCross-sectional studyMeasures of hospitalHealth care qualityPatient demographicsReadmission ratesClinical outcomesPatient raceEligible hospitalsReadmissionMAIN OUTCOMEReadmission measuresMedicare dataUS hospitalsHospitalCare qualityPatientsMedicaid ServicesOutcomesLower percentageLB01 Development of post-acute sequelae of SARS-CoV-2 (PASC) after infection in pregnancy: NIH RECOVER-Pregnancy Cohort
Metz T, Reeder H, Clifton R, Flaherman V, Aragon L, Baucom L, Braverman A, Cao T, Dionne J, Foulkes A, Gross R, Han J, Hess R, Horwitz L, Jia X, Kale M, Mehari A, Monteiro J, Pant D, Ramsey P, Jacoby V. LB01 Development of post-acute sequelae of SARS-CoV-2 (PASC) after infection in pregnancy: NIH RECOVER-Pregnancy Cohort. American Journal Of Obstetrics And Gynecology 2024, 230: s6. DOI: 10.1016/j.ajog.2023.11.1258.Peer-Reviewed Original Research
2023
Researching COVID to enhance recovery (RECOVER) pregnancy study: Rationale, objectives and design
Metz T, Clifton R, Gallagher R, Gross R, Horwitz L, Jacoby V, Martin-Herz S, Peralta-Carcelen M, Reeder H, Beamon C, Chan J, Chang A, Costantine M, Fitzgerald M, Foulkes A, Gibson K, Güthe N, Habli M, Hackney D, Hoffman M, Hoffman M, Hughes B, Katz S, Laleau V, Mallett G, Mendez-Figueroa H, Monzon V, Palatnik A, Palomares K, Parry S, Pettker C, Plunkett B, Poppas A, Reddy U, Rouse D, Saade G, Sandoval G, Schlater S, Sciurba F, Simhan H, Skupski D, Sowles A, Thaweethai T, Thomas G, Thorp J, Tita A, Weiner S, Weigand S, Yee L, Flaherman V, Initiative O. Researching COVID to enhance recovery (RECOVER) pregnancy study: Rationale, objectives and design. PLOS ONE 2023, 18: e0285351. PMID: 38128008, PMCID: PMC10734909, DOI: 10.1371/journal.pone.0285351.Peer-Reviewed Original ResearchConceptsSARS-CoV-2 infectionSARS-CoV-2Long-term outcomesMonths of agePregnancy cohortMaternal-Fetal Medicine Units NetworkHealth outcomesSARS-CoV-2 antibody testingAdverse long-term outcomesEunice Kennedy Shriver National InstitutePost-acute sequelaeLong-term sequelaeClinical trial registrationMaternal-child dyadsNational InstituteMulti-site observational studyCalifornia San FranciscoUnique physiologic changesPregnancy modifiesMaternal infectionMultiple gestationsOverall cohortRetrospective cohortAntibody testingLong COVID3 A/B testing in healthcare: how you can apply tech industry methods to improve quality in your system
Krelle H, King W, Jones S, Rosen K, Tsuruo S, Klapheke N, Stadelman J, Horwitz L. 3 A/B testing in healthcare: how you can apply tech industry methods to improve quality in your system. 2023, a1.3-a1. DOI: 10.1136/bmjoq-2023-ihi.3.Peer-Reviewed Original ResearchImpact of Visit Volume on the Effectiveness of Electronic Tools to Improve Heart Failure Care
Mukhopadhyay A, Reynolds H, King W, Phillips L, Nagler A, Szerencsy A, Saxena A, Klapheke N, Katz S, Horwitz L, Blecker S. Impact of Visit Volume on the Effectiveness of Electronic Tools to Improve Heart Failure Care. JACC Heart Failure 2023, 12: 665-674. PMID: 38043045, DOI: 10.1016/j.jchf.2023.11.002.Peer-Reviewed Original ResearchMineralocorticoid antagonistsVolume groupVisit volumeElectronic health record toolsPhysician workloadGuideline-recommended therapiesReduced ejection fractionUsual care armHeart failure carePrespecified subgroup analysisHigh-volume groupCluster-randomized trialLog-binomial modelsBusy practice settingsCare armEHR alertUsual careEjection fractionHeart failureSubgroup analysisEHR toolsNumber of visitsCardiology officePractice settingsStudy period
2020
Trends in COVID‐19 Risk‐Adjusted Mortality Rates
Horwitz LI, Jones SA, Cerfolio RJ, Francois F, Greco J, Rudy B, Petrilli CM. Trends in COVID‐19 Risk‐Adjusted Mortality Rates. Journal Of Hospital Medicine 2020, 16: 90-92. PMID: 33147129, DOI: 10.12788/jhm.3552.Peer-Reviewed Original ResearchConceptsHospital mortalityMortality rateHealth systemRisk-adjusted mortality ratesAdmission vital signsStandardized mortality ratioCoronavirus disease 2019Academic health systemPatient characteristicsClinical factorsMortality ratioDisease 2019High mortalityVital signsMortalityComorbiditiesCOVID-19Laboratory resultsEarlier reportsHospitalizationPatientsHospiceDemographicsFactors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study
Petrilli CM, Jones SA, Yang J, Rajagopalan H, O'Donnell L, Chernyak Y, Tobin KA, Cerfolio RJ, Francois F, Horwitz LI. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. The BMJ 2020, 369: m1966. PMID: 32444366, PMCID: PMC7243801, DOI: 10.1136/bmj.m1966.Peer-Reviewed Original ResearchConceptsBody mass indexProspective cohort studyCritical illnessCoronavirus disease 2019Hospital admissionCohort studyHeart failureMale sexDisease 2019Hospice careAcute respiratory syndrome coronavirus 2 infectionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectionSyndrome coronavirus 2 infectionC-reactive protein levelsSingle academic medical centerAdmission oxygen saturationCoronavirus 2 infectionReactive protein levelsChronic kidney diseaseD-dimer levelsMarkers of inflammationAge 75 yearsSeverity of illnessStrong riskMultivariable logistic regressionQuantifying Health Systems’ Investment In Social Determinants Of Health, By Sector, 2017–19
Horwitz LI, Chang C, Arcilla HN, Knickman JR. Quantifying Health Systems’ Investment In Social Determinants Of Health, By Sector, 2017–19. Health Affairs 2020, 39: 192-198. PMID: 32011928, DOI: 10.1377/hlthaff.2019.01246.Peer-Reviewed Original Research
2019
Creating a Learning Health System through Rapid-Cycle, Randomized Testing
Horwitz LI, Kuznetsova M, Jones SA. Creating a Learning Health System through Rapid-Cycle, Randomized Testing. New England Journal Of Medicine 2019, 381: 1175-1179. PMID: 31532967, DOI: 10.1056/nejmsb1900856.Peer-Reviewed Original ResearchBending the cost curve: time series analysis of a value transformation programme at an academic medical centre
Chatfield SC, Volpicelli FM, Adler NM, Kim KL, Jones SA, Francois F, Shah PC, Press RA, Horwitz LI. Bending the cost curve: time series analysis of a value transformation programme at an academic medical centre. BMJ Quality & Safety 2019, 28: 449. PMID: 30877149, PMCID: PMC6860728, DOI: 10.1136/bmjqs-2018-009068.Peer-Reviewed Original ResearchConceptsLength of stayDiagnosis Related GroupsAcademic medical centerHospital mortalityMedical CenterMedical diagnosis related groupsSurgical diagnosis related groupsStudy periodSame-hospital readmissionsCost of careNYU Langone HealthVariable direct costsValue of healthcareSecondary outcomesHigh-value careStudy cohortOutlier patientsHealth outcomesValue careEarly increaseIntervention costsDirect costsHealthcare valueShared Savings ProgramHospitalisationTrends 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
Hospital Characteristics Associated With Postdischarge Hospital Readmission, Observation, and Emergency Department Utilization
Horwitz LI, Wang Y, Altaf FK, Wang C, Lin Z, Liu S, Grady J, Bernheim SM, Desai NR, Venkatesh AK, Herrin J. Hospital Characteristics Associated With Postdischarge Hospital Readmission, Observation, and Emergency Department Utilization. Medical Care 2018, 56: 281-289. PMID: 29462075, PMCID: PMC6170884, DOI: 10.1097/mlr.0000000000000882.Peer-Reviewed Original ResearchMeSH KeywordsCross-Sectional StudiesEmergency Service, HospitalFee-for-Service PlansHeart FailureHospital AdministrationHospitals, PublicHumansMedicareMyocardial InfarctionNursing Staff, HospitalOwnershipPatient ReadmissionPneumoniaResidence CharacteristicsRetrospective StudiesSafety-net ProvidersUnited StatesConceptsAcute care utilizationAcute myocardial infarctionHeart failureCare utilizationAcute careMyocardial infarctionHospital characteristicsNet hospitalExcess daysPublic hospitalsNonsafety net hospitalsHigher readmission ratesEmergency department utilizationProportion of hospitalsAcute care hospitalsSafety-net hospitalService Medicare beneficiariesLarge urban hospitalMajor teaching hospitalType of hospitalCross-sectional analysisPostdischarge utilizationHospital dischargeHospital factorsReadmission rates
2016
Association Between Hospital Penalty Status Under the Hospital Readmission Reduction Program and Readmission Rates for Target and Nontarget Conditions
Desai NR, Ross JS, Kwon JY, Herrin J, Dharmarajan K, Bernheim SM, Krumholz HM, Horwitz LI. Association Between Hospital Penalty Status Under the Hospital Readmission Reduction Program and Readmission Rates for Target and Nontarget Conditions. JAMA 2016, 316: 2647-2656. PMID: 28027367, PMCID: PMC5599851, DOI: 10.1001/jama.2016.18533.Peer-Reviewed Original ResearchConceptsHospital Readmissions Reduction ProgramAcute myocardial infarctionReadmission ratesReadmissions Reduction ProgramHeart failurePenalty statusNontarget conditionsMedicare feeMean readmission rateThirty-day riskRetrospective cohort studyUnplanned readmission rateReduction programsHRRP announcementHRRP implementationPenalized hospitalsCohort studyService patientsMyocardial infarctionMAIN OUTCOMEExcess readmissionsMedicare beneficiariesService beneficiariesHospitalPatientsQuasi-Experimental Evaluation of the Effectiveness of a Large-Scale Readmission Reduction Program
Jenq GY, Doyle MM, Belton BM, Herrin J, Horwitz LI. Quasi-Experimental Evaluation of the Effectiveness of a Large-Scale Readmission Reduction Program. JAMA Internal Medicine 2016, 176: 681. PMID: 27065180, DOI: 10.1001/jamainternmed.2016.0833.Peer-Reviewed Original ResearchConceptsDischarge patientsReadmissions Reduction ProgramControl populationReadmission ratesIntervention periodSame-hospital readmission ratesUrban academic medical centerTarget populationAdjusted readmission ratesOdds of readmissionHigh-risk patientsZip codesAdjusted admission ratesInterrupted time series analysisAcademic medical centerQuasi-experimental evaluationLogistic regression modelsReduction programsDischarge dispositionReadmission reduction effortsComparative interrupted time series analysisMedication reconciliationService patientsMean ageTransitional care