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 groupsAutomated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing
Nargesi A, Adejumo P, Dhingra L, Rosand B, Hengartner A, Coppi A, Benigeri S, Sen S, Ahmad T, Nadkarni G, Lin Z, Ahmad F, Krumholz H, Khera R. Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing. JACC Heart Failure 2024 PMID: 39453355, DOI: 10.1016/j.jchf.2024.08.012.Peer-Reviewed Original ResearchReduced ejection fractionEjection fractionHeart failureLeft ventricular ejection fractionVentricular ejection fractionYale-New Haven HospitalIdentification of patientsCommunity hospitalIdentification of heart failureLanguage modelNorthwestern MedicineMeasure care qualityQuality of careNew Haven HospitalDeep learning-based natural language processingHFrEFGuideline-directed careDeep learning language modelsMIMIC-IIIDetect HFrEFNatural language processingReclassification improvementHospital dischargePatientsCare quality