2024
Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure
Adejumo P, Thangaraj P, Dhingra L, Aminorroaya A, Zhou X, Brandt C, Xu H, Krumholz H, Khera R. Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure. JAMA Network Open 2024, 7: e2443925. PMID: 39509128, PMCID: PMC11544492, DOI: 10.1001/jamanetworkopen.2024.43925.Peer-Reviewed Original ResearchConceptsFunctional status assessmentArea under the receiver operating characteristic curveClinical documentationElectronic health record dataHF symptomsOptimal care deliveryHealth record dataAssess functional statusStatus assessmentClinical trial participationProcessing of clinical documentsFunctional status groupCare deliveryOutpatient careMain OutcomesMedical notesTrial participantsNew York Heart AssociationFunctional statusQuality improvementRecord dataHeart failureClinical notesDiagnostic studiesStatus groupsMultimodal fusion learning for long QT syndrome pathogenic genotypes in a racially diverse population
Jiang J, Thi Vy H, Charney A, Kovatch P, Reddy V, Jayaraman P, Do R, Khera R, Chugh S, Bhatt D, Vaid A, Lampert J, Nadkarni G. Multimodal fusion learning for long QT syndrome pathogenic genotypes in a racially diverse population. Npj Digital Medicine 2024, 7: 226. PMID: 39181999, PMCID: PMC11344778, DOI: 10.1038/s41746-024-01218-1.Peer-Reviewed Original ResearchLong QT syndromeUnited Kingdom BiobankHigh-risk genotypesElectronic health record dataHealth record dataPathogenic variantsRacially/ethnically diverse cohortCongenital long QT syndromeLQTS-susceptibility genesRacially diverse populationMount Sinai BioMe BiobankPathogenic genetic mutationsQT corrected intervalArea under the receiver operating curveBioMe BiobankPatient prioritizationReceiver operating curveQT syndromeRecord dataDiverse cohortGenetic testingDiverse populationsPathogen genotypesGenetic mutationsPatients
2022
A multicenter evaluation of computable phenotyping approaches for SARS-CoV-2 infection and COVID-19 hospitalizations
Khera R, Mortazavi BJ, Sangha V, Warner F, Patrick Young H, Ross JS, Shah ND, Theel ES, Jenkinson WG, Knepper C, Wang K, Peaper D, Martinello RA, Brandt CA, Lin Z, Ko AI, Krumholz HM, Pollock BD, Schulz WL. A multicenter evaluation of computable phenotyping approaches for SARS-CoV-2 infection and COVID-19 hospitalizations. Npj Digital Medicine 2022, 5: 27. PMID: 35260762, PMCID: PMC8904579, DOI: 10.1038/s41746-022-00570-4.Peer-Reviewed Original ResearchCOVID-19 hospitalizationMayo ClinicDiagnosis codesCOVID-19 diagnosisPositive SARS-CoV-2 PCRYale New Haven Health SystemPositive SARS-CoV-2 testSARS-CoV-2 infectionSARS-CoV-2 PCRSARS-CoV-2 testCOVID-19Higher inhospital mortalitySARS-CoV2 infectionElectronic health record dataICD-10 diagnosisPositive laboratory testsHealth record dataInhospital mortalityAdditional patientsAntigen testSecondary diagnosisPrincipal diagnosisMulticenter evaluationPositive testComputable phenotype definitions