2024
Incorporating Medicare Advantage Admissions Into the CMS Hospital-Wide Readmission Measure
Kyanko K, Sahay K, Wang Y, Li S, Schreiber M, Hager M, Myers R, Johnson W, Zhang J, Krumholz H, Suter L, Triche E. Incorporating Medicare Advantage Admissions Into the CMS Hospital-Wide Readmission Measure. JAMA Network Open 2024, 7: e2414431. PMID: 38829614, PMCID: PMC11148674, DOI: 10.1001/jamanetworkopen.2024.14431.Peer-Reviewed Original ResearchConceptsCenters for Medicare & Medicaid ServicesSpecialty subgroupsPerformance quintileMedicare AdvantageReadmission ratesRisk-standardized readmission ratesHospital-wide readmission measureHospital outcome measuresTest-retest reliabilityRisk-adjustment variablesMeasurement reliabilityAdministrative claims dataReadmission measuresImprove measurement reliabilityIntegrated data repositoryMA beneficiariesQuintile rankingsMedicare beneficiariesMedicaid ServicesAll-causePublic reportingStudy assessed differencesClaims dataOutcome measuresMA cohortPre-COVID-19 hospital quality and hospital response to COVID-19: examining associations between risk-adjusted mortality for patients hospitalised with COVID-19 and pre-COVID-19 hospital quality
Peter D, Li S, Wang Y, Zhang J, Grady J, McDowell K, Norton E, Lin Z, Bernheim S, Venkatesh A, Fleisher L, Schreiber M, Suter L, Triche E. Pre-COVID-19 hospital quality and hospital response to COVID-19: examining associations between risk-adjusted mortality for patients hospitalised with COVID-19 and pre-COVID-19 hospital quality. BMJ Open 2024, 14: e077394. PMID: 38553067, PMCID: PMC10982775, DOI: 10.1136/bmjopen-2023-077394.Peer-Reviewed Original ResearchMeSH KeywordsAgedCOVID-19Hospital MortalityHospitalsHumansMedicarePandemicsRetrospective StudiesUnited StatesConceptsHospital qualityPatient experiencePre-COVID-19Medicare patientsShort-term acute care hospitalsCritical access hospitalsAcute care hospitalsFuture public health emergenciesHigher odds of mortalityIn-hospitalRisk-adjusted mortalityOdds of mortalityCare deliveryAccess hospitalsEffective careCOVID-19-related deathsAssociated with mortalityCare structuresHospital characteristicsPublic health emergencySummary scoreMedicare beneficiariesHigher oddsHospital responseRSMRs
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
2019
Development and Validation of a Risk Prediction Model for Cesarean Delivery After Labor Induction
Danilack VA, Hutcheon JA, Triche EW, Dore DD, Muri JH, Phipps MG, Savitz DA. Development and Validation of a Risk Prediction Model for Cesarean Delivery After Labor Induction. Journal Of Women's Health 2019, 29: 656-669. PMID: 31657668, PMCID: PMC8935479, DOI: 10.1089/jwh.2019.7822.Peer-Reviewed Original ResearchConceptsLabor inductionCesarean deliveryHistory of herpesTerm labor inductionInternal validationExcessive fetal growthBetter risk stratificationExternal validation cohortVariables gestational ageRisk prediction modelStart of inductionRisk stratificationTime of inductionDevelopment cohortValidation cohortMaternal ageFetal growthMaternal raceMedical indicationsWoman's riskU.S. hospitalsCharacteristic curveHospitalCohortInductionDevelopment 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 infarction
2018
Gene-Centric Analysis of Preeclampsia Identifies Maternal Association at PLEKHG1
Gray KJ, Kovacheva VP, Mirzakhani H, Bjonnes AC, Almoguera B, DeWan AT, Triche EW, Saftlas AF, Hoh J, Bodian DL, Klein E, Huddleston KC, Ingles SA, Lockwood CJ, Hakonarson H, McElrath TF, Murray JC, Wilson ML, Norwitz ER, Karumanchi SA, Bateman BT, Keating BJ, Saxena R. Gene-Centric Analysis of Preeclampsia Identifies Maternal Association at PLEKHG1. Hypertension 2018, 72: 408-416. PMID: 29967039, PMCID: PMC6043396, DOI: 10.1161/hypertensionaha.117.10688.Peer-Reviewed Original Research
2015
The Rising Burden of Preeclampsia in the United States Impacts Both Maternal and Child Health
Shih T, Peneva D, Xu X, Sutton A, Triche E, Ehrenkranz RA, Paidas M, Stevens W. The Rising Burden of Preeclampsia in the United States Impacts Both Maternal and Child Health. American Journal Of Perinatology 2015, 33: 329-338. PMID: 26479171, DOI: 10.1055/s-0035-1564881.Peer-Reviewed Original ResearchConceptsEarly-onset preeclampsiaNumerous adverse health consequencesHealth consequencesConsiderable perinatal morbidityAdverse health consequencesEstimates of burdenSeverity of outcomePerinatal morbidityPreterm deliveryPreterm birthTerm pregnancyMaternal mortalityUS incidencePreeclampsiaChild healthEffective treatmentEconomic burdenRising BurdenSocial burdenHealth careBurdenMortalityUnited StatesHealthMothersThe effect of labour induction on the risk of caesarean delivery: using propensity scores to control confounding by indication
Danilack V, Dore D, Triche E, Muri J, Phipps M, Savitz D. The effect of labour induction on the risk of caesarean delivery: using propensity scores to control confounding by indication. BJOG An International Journal Of Obstetrics & Gynaecology 2015, 123: 1521-1529. PMID: 26411752, DOI: 10.1111/1471-0528.13682.Peer-Reviewed Original ResearchConceptsWeeks of gestationCaesarean deliveryLabor inductionRisk ratioPropensity scoreElevated riskNational Perinatal Information CenterPrimary caesarean deliveryRisk of caesareanAdministrative hospital discharge dataHospital discharge dataMedical record informationCross-sectional analysisExpectant managementPreterm deliveryLiveborn deliveryPropensity score methodsGestationMember hospitalsPS adjustmentWeeksCovariate adjustmentSubsequent weeksTraditional covariatesRiskGenetic Risk Score for Essential Hypertension and Risk of Preeclampsia
Smith CJ, Saftlas AF, Spracklen CN, Triche EW, Bjonnes A, Keating B, Saxena R, Breheny PJ, Dewan AT, Robinson JG, Hoh J, Ryckman KK. Genetic Risk Score for Essential Hypertension and Risk of Preeclampsia. American Journal Of Hypertension 2015, 29: 17-24. PMID: 26002928, PMCID: PMC4692983, DOI: 10.1093/ajh/hpv069.Peer-Reviewed Original ResearchConceptsDiastolic blood pressureSystolic blood pressureGenetic risk scoreRisk of preeclampsiaBlood pressureEssential hypertensionRisk scoreNormotensive pregnant controlsHypertensive complicationsArterial pressurePregnant controlsWeeks' gestationPreeclamptic casesHypertensive stateEpidemiological evidenceHypertensionPreeclampsiaUS populationNonsignificant associationGenetic risk lociGenetic susceptibilitySwab samplesBuccal swab samplesGenetic riskRegression analysis
2013
The association between epilepsy and autism symptoms and maladaptive behaviors in children with autism spectrum disorder
Viscidi E, Johnson A, Spence S, Buka S, Morrow E, Triche E. The association between epilepsy and autism symptoms and maladaptive behaviors in children with autism spectrum disorder. Autism 2013, 18: 996-1006. PMID: 24165273, PMCID: PMC4002664, DOI: 10.1177/1362361313508027.Peer-Reviewed Original ResearchConceptsAutism spectrum disorderAutism symptomsMaladaptive behaviorsAutism phenotypeHyperactivity symptomsSpectrum disorderMore autism symptomsCo-occurring intellectual disabilitySimons Simplex CollectionEpilepsy groupLower IQGreater impairmentMore irritabilityIntellectual disabilityIQChildrenImportant clinical implicationsClinical implicationsDisordersSymptomsBehaviorImpairmentIrritabilityImplicationsAssociationClinical Characteristics of Children with Autism Spectrum Disorder and Co-Occurring Epilepsy
Viscidi E, Triche E, Pescosolido M, McLean R, Joseph R, Spence S, Morrow E. Clinical Characteristics of Children with Autism Spectrum Disorder and Co-Occurring Epilepsy. PLOS ONE 2013, 8: e67797. PMID: 23861807, PMCID: PMC3701630, DOI: 10.1371/journal.pone.0067797.Peer-Reviewed Original ResearchConceptsPrevalence of epilepsyClinical characteristicsDevelopmental regressionOlder ageAverage prevalenceCo-occurring epilepsyAutism spectrum disorderDate of patientsMultivariate logistic regressionLarger patient populationCross-sectional studyPopulation-based samplePatient populationChildren ages 10Independent associationRisk factorsMultivariate regression modelSpectrum disorderEpilepsyAlert cliniciansSample of childrenLarger studyLogistic regressionPrevalenceAge 10Exploring the Role of Antithrombin Replacement for the Treatment of Preeclampsia: A Prospective Randomized Evaluation of the Safety and Efficacy of Recombinant Antithrombin in Very Preterm Preeclampsia (PRESERVE‐1)
Paidas MJ, Sibai BM, Triche EW, Frieling J, Lowry S, Group T. Exploring the Role of Antithrombin Replacement for the Treatment of Preeclampsia: A Prospective Randomized Evaluation of the Safety and Efficacy of Recombinant Antithrombin in Very Preterm Preeclampsia (PRESERVE‐1). American Journal Of Reproductive Immunology 2013, 69: 539-544. PMID: 23444920, DOI: 10.1111/aji.12091.Peer-Reviewed Original ResearchConceptsProspective Randomized EvaluationAntithrombin replacementWeeks' gestationRandomized EvaluationRecombinant antithrombinTreatment of preeclampsiaRecombinant human ATExpectant managementPreterm preeclampsiaPrimary endpointMaternal indicationsGestational ageStudy enrollmentAT therapyPreeclampsia studyPreeclampsiaGestationHuman ATAT replacementPharmacokinetic activityAntithrombinEfficacySafetyLaboratory assaysDelivery
2012
Implementing Provider‐based Sampling for the National Children's Study: Opportunities and Challenges
Belanger K, Buka S, Cherry DC, Dudley DJ, Elliott MR, Hale DE, Hertz‐Picciotto I, Illuzzi JL, Paneth N, Robbins JM, Triche EW, Bracken MB. Implementing Provider‐based Sampling for the National Children's Study: Opportunities and Challenges. Paediatric And Perinatal Epidemiology 2012, 27: 20-26. PMID: 23215706, DOI: 10.1111/ppe.12005.Peer-Reviewed Original ResearchConceptsNational Children's StudyProvider-based samplingChildren's StudyNational cohort studyPrenatal care providersNational probability sampleType of providerProbability sampleCohort studyPrenatal careCare providersChild healthProvider groupsAge 21Risk estimatesPrimary sampling unitsWomenBirthProvidersHealthSampling frameSecondary sampling unitsPregnancyNumber of strategiesUtero
2011
Prenatal Factors for Childhood Blood Pressure Mediated by Intrauterine and/or Childhood Growth?
Wen X, Triche E, Hogan J, Shenassa E, Buka S. Prenatal Factors for Childhood Blood Pressure Mediated by Intrauterine and/or Childhood Growth? Pediatrics 2011, 127: e713-e721. PMID: 21300676, PMCID: PMC3065147, DOI: 10.1542/peds.2010-2000.Peer-Reviewed Original ResearchConceptsOffspring systolic blood pressureSystolic blood pressureIntrauterine growth restrictionPregnancy weight gainBlood pressureYears of ageMaternal smokingPrenatal factorsChildhood growthPrepregnancy BMIBMI trajectoriesChildhood systolic blood pressureChildren's systolic blood pressureMaternal pregnancy weight gainWeight gainChildhood BMI trajectoriesHeavy maternal smokingOffspring blood pressureChildhood blood pressureMother-child pairsCollaborative Perinatal ProjectChronic hypertensionObstetric formPreeclampsia-eclampsiaChildhood BMI
2010
Birth Weight and Adult Hypercholesterolemia
Wen X, Triche E, Hogan J, Shenassa E, Buka S. Birth Weight and Adult Hypercholesterolemia. Epidemiology 2010, 21: 786-790. PMID: 20798636, DOI: 10.1097/ede.0b013e3181f20990.Peer-Reviewed Original ResearchConceptsMaternal smokingAdult hypercholesterolemiaSGA subgroupsElevated riskMean age 39 yearsGestational age subgroupsOnly certain subgroupsMaternal smoking statusAge 39 yearsCollaborative Perinatal ProjectSGA infantsHazard ratioHeavy smokingSmoking statusBirth weightFetal growthModerate smokingHigh riskAdult offspringHypercholesterolemiaSmokingPerinatal ProjectPregnancyClinical diagnosisCertain subgroups
2006
The Epidemiology of Asthma During Pregnancy: Prevalence, Diagnosis, and Symptoms
Kwon HL, Triche EW, Belanger K, Bracken MB. The Epidemiology of Asthma During Pregnancy: Prevalence, Diagnosis, and Symptoms. Immunology And Allergy Clinics Of North America 2006, 26: 29-62. PMID: 16443142, DOI: 10.1016/j.iac.2005.11.002.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsMeSH KeywordsAsthmaCohort StudiesFemaleHumansPregnancyPregnancy ComplicationsPrevalenceUnited StatesConceptsPregnant womenLarge prospective cohort studyEpidemiology of asthmaProspective cohort studySelf-reported asthmaPopulation-level improvementsAsthma controlCohort studyAsthma diagnosisAsthma attacksCommon conditionPrevalence ratesClinical involvementAsthmaNational dataPregnancyPrevalenceDiagnosisWomenUnited StatesPopulation characteristicsRepresentative dataPrevious yearFurther researchFurther characterization