Automated 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 qualityMeasuring 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 percentage