2025
Assessment of health conditions from patient electronic health record portals vs self-reported questionnaires: an analysis of the INSPIRE study
Khera R, Sawano M, Warner F, Coppi A, Pedroso A, Spatz E, Yu H, Gottlieb M, Saydah S, Stephens K, Rising K, Elmore J, Hill M, Idris A, Montoy J, O’Laughlin K, Weinstein R, Venkatesh A, Weinstein R, Gottlieb M, Santangelo M, Koo K, Derden A, Gottlieb M, Gatling K, Ahmed Z, Gomez C, Guzman D, Hassaballa M, Jerger R, Kaadan A, Venkatesh A, Spatz E, Kinsman J, Malicki C, Lin Z, Li S, Yu H, Mannan I, Yang Z, Liu M, Venkatesh A, Spatz E, Ulrich A, Kinsman J, Malicki C, Dorney J, Pierce S, Puente X, Salah W, Nichol G, Stephens K, Anderson J, Schiffgens M, Morse D, Adams K, Stober T, Maat Z, O’Laughlin K, Gentile N, Geyer R, Willis M, Zhang Z, Chang G, Lyon V, Klabbers R, Ruiz L, Malone K, Park J, Rising K, Kean E, Chang A, Renzi N, Watts P, Kelly M, Schaeffer K, Grau D, Cheng D, Shutty C, Charlton A, Shughart L, Shughart H, Amadio G, Miao J, Hannikainen P, Elmore J, Wisk L, L’Hommedieu M, Chandler C, Eguchi M, Roldan K, Moreno R, Rodriguez R, Wang R, Montoy J, Kemball R, Chan V, Chavez C, Wong A, Arreguin M, Hill M, Site R, Kane A, Nikonowicz P, Sapp S, Idris A, McDonald S, Gallegos D, Martin K, Saydah S, Plumb I, Hall A, Briggs-Hagen M. Assessment of health conditions from patient electronic health record portals vs self-reported questionnaires: an analysis of the INSPIRE study. Journal Of The American Medical Informatics Association 2025, ocaf027. PMID: 40036551, DOI: 10.1093/jamia/ocaf027.Peer-Reviewed Original ResearchElectronic health recordsSelf-report questionnairesSelf-reportHealth conditionsElectronic health record portalsElectronic health record platformsEHR elementsSelf-reported health conditionsElectronic health record dataSelf-reported conditionsAssessment of health conditionEvaluation of health conditionsPrevalence of conditionsPatient portalsTraditional self-reportPrevalence of comorbiditiesHealth recordsEHR dataEHR phenotypesDiagnosis codesHospitalization riskComputable phenotypeNationwide studyCohen's kappaPatient characteristics
2021
Sparse Gated Mixture-of-Experts to Separate and Interpret Patient Heterogeneity in EHR data
Huo Z, Zhang L, Khera R, Huang S, Qian X, Wang Z, Mortazavi B. Sparse Gated Mixture-of-Experts to Separate and Interpret Patient Heterogeneity in EHR data. 2021, 00: 1-4. DOI: 10.1109/bhi50953.2021.9508549.Peer-Reviewed Original Research
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