2023
A privacy-preserving and computation-efficient federated algorithm for generalized linear mixed models to analyze correlated electronic health records data
Yan Z, Zachrison K, Schwamm L, Estrada J, Duan R. A privacy-preserving and computation-efficient federated algorithm for generalized linear mixed models to analyze correlated electronic health records data. PLOS ONE 2023, 18: e0280192. PMID: 36649349, PMCID: PMC9844867, DOI: 10.1371/journal.pone.0280192.Peer-Reviewed Original ResearchConceptsFederated algorithmPrivacy-preserving data integrationEHR dataElectronic health record dataComputation resource requirementsHealth record dataLongitudinal EHR dataPrivacy protectionData integrationResource requirementsMultiple healthcare facilitiesNumerical experimentsComputational efficiencyGeneralized linear mixed modelRecord dataCorrelated dataSite‐level heterogeneityAlgorithmNetworkSummary statisticsResearch NetworkLimited amountDatasetLinear mixed modelsGLMM
2019
Epilepsy Among Elderly Medicare Beneficiaries
Moura L, Smith J, Blacker D, Vogeli C, Schwamm L, Cole A, Hernandez-Diaz S, Hsu J. Epilepsy Among Elderly Medicare Beneficiaries. Medical Care 2019, 57: 318-324. PMID: 30762723, PMCID: PMC6417929, DOI: 10.1097/mlr.0000000000001072.Peer-Reviewed Original ResearchMeSH KeywordsAdministrative Claims, HealthcareAgedAlgorithmsElectronic Health RecordsEpilepsyFemaleHumansLongitudinal StudiesMaleMedicarePrevalenceUnited StatesConceptsMedicare administrative dataEpilepsy statusMedicare beneficiariesMedicare dataEpilepsy diagnosisElectronic health record dataElderly Medicare beneficiariesHealth record dataHealth insurance claimsAdministrative dataElectronic health recordsIncident epilepsyPrevalent epilepsyDrug claimsEpilepsyDiagnostic thresholdStratified random sampleInverse probabilityHealth recordsMedicare claims can identify post-stroke epilepsy
Moura L, Smith J, Blacker D, Vogeli C, Schwamm L, Hsu J. Medicare claims can identify post-stroke epilepsy. Epilepsy Research 2019, 151: 40-47. PMID: 30780120, PMCID: PMC6640134, DOI: 10.1016/j.eplepsyres.2019.02.002.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAlgorithmsElectronic Health RecordsEpilepsyHumansInternational Classification of DiseasesMedicareMiddle AgedStrokeUnited StatesConceptsElectronic health recordsAccountable care organizationsMedicare claimsCommunity-dwelling elderly individualsPost-stroke epilepsyElderly Medicare beneficiariesClaims-based algorithmPositive predictive valuePioneer Accountable Care OrganizationsDiscrete etiologyNeurologist visitOverall prevalenceMedicare patientsClaims diagnosesPSE diagnosisElderly individualsMedicare beneficiariesPatientsPredictive valueEpilepsyFuture epidemiological surveillanceEpidemiological surveillanceInverse probabilityHealth recordsDiagnosis
2017
Incorporating Stroke Severity Into Hospital Measures of 30-Day Mortality After Ischemic Stroke Hospitalization
Schwartz J, Wang Y, Qin L, Schwamm LH, Fonarow GC, Cormier N, Dorsey K, McNamara RL, Suter LG, Krumholz HM, Bernheim SM. Incorporating Stroke Severity Into Hospital Measures of 30-Day Mortality After Ischemic Stroke Hospitalization. Stroke 2017, 48: 3101-3107. PMID: 28954922, DOI: 10.1161/strokeaha.117.017960.Peer-Reviewed Original ResearchConceptsRisk-standardized mortality ratesElectronic health record dataHealth record dataStroke severityClaims dataMortality rateAmerican Heart Association/American Stroke AssociationHealth Stroke Scale scoreRisk variablesMedicaid ServicesRisk adjustmentMedian risk-standardized mortality rateGuidelines-Stroke registryLow-mortality hospitalsStroke Scale scoreAcute ischemic strokeAmerican Stroke AssociationOdds of mortalityMortality measuresRecord dataIschemic stroke hospitalizationsHigh-mortality hospitalsService claims dataRisk-adjustment variablesHospital admission
2015
Future of Quality and Outcomes Research in Stroke
Fonarow G, Kapral M, Schwamm L. Future of Quality and Outcomes Research in Stroke. Circulation Cardiovascular Quality And Outcomes 2015, 8: s66-s68. PMID: 26515211, DOI: 10.1161/circoutcomes.115.002309.Peer-Reviewed Original ResearchLack of Impact of Electronic Health Records on Quality of Care and Outcomes for Ischemic Stroke
Joynt K, Bhatt D, Schwamm L, Xian Y, Heidenreich P, Fonarow G, Smith E, Neely M, Grau-Sepulveda M, Hernandez A. Lack of Impact of Electronic Health Records on Quality of Care and Outcomes for Ischemic Stroke. Journal Of The American College Of Cardiology 2015, 65: 1964-1972. PMID: 25953748, DOI: 10.1016/j.jacc.2015.02.059.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overElectronic Health RecordsFemaleHospital Bed CapacityHospital MortalityHospitals, TeachingHumansLength of StayMaleMiddle AgedOutcome Assessment, Health CarePatient DischargePractice Guidelines as TopicQuality of Health CareStrokeTime-to-TreatmentTissue Plasminogen ActivatorUnited StatesConceptsElectronic health recordsIschemic strokeGWTG-Stroke hospitalsHealth recordsBetter clinical outcomesLogistic regression analysisAmerican Hospital Association Annual SurveyQuality of careOutcomes of interestHigh-quality careGuidelines-StrokeHospital mortalityStroke centersClinical outcomesStroke careSimilar oddsHospital characteristicsOutcome measuresTimely careHospitalPatientsStudy periodCareU.S. hospitalsStroke