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 characteristicsEvaluation of a Machine Learning-Guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems
Aminorroaya A, Dhingra L, Oikonomou E, Khera R. Evaluation of a Machine Learning-Guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems. Circulation Genomic And Precision Medicine 2025, 18: e004632. PMID: 39846171, PMCID: PMC11835527, DOI: 10.1161/circgen.124.004632.Peer-Reviewed Original ResearchConceptsYale New Haven Health SystemHealth systemVanderbilt University Medical CenterHealth system electronic health recordUniversity Medical CenterCoronary Artery Risk DevelopmentMulti-Ethnic Study of AtherosclerosisElectronic health recordsMedical CenterUS health systemHealth system patientsAssociated with significantly higher oddsMulti-Ethnic StudyUS-based cohortStudy of AtherosclerosisSignificantly higher oddsHealth recordsUK BiobankAtherosclerosis RiskRisk DevelopmentHigher oddsElevated Lp(aUniversal screeningSystem patientsStudy cohort
2024
The PAX LC Trial: A Decentralized, Phase 2, Randomized, Double-blind Study of Nirmatrelvir/Ritonavir Compared with Placebo/Ritonavir for Long COVID
Krumholz H, Sawano M, Bhattacharjee B, Caraballo C, Khera R, Li S, Herrin J, Coppi A, Holub J, Henriquez Y, Johnson M, Goddard T, Rocco E, Hummel A, Al Mouslmani M, Putrino D, Carr K, Carvajal-Gonzalez S, Charnas L, De Jesus M, Ziegler F, Iwasaki A. The PAX LC Trial: A Decentralized, Phase 2, Randomized, Double-blind Study of Nirmatrelvir/Ritonavir Compared with Placebo/Ritonavir for Long COVID. The American Journal Of Medicine 2024 PMID: 38735354, DOI: 10.1016/j.amjmed.2024.04.030.Peer-Reviewed Original ResearchLC trialPROMIS-29Participants' homesTargeting viral persistencePlacebo-controlled trialDouble-blind studyElectronic health recordsCore Outcome MeasuresLong COVIDEQ-5D-5LRepeated measures analysisEvidence-based treatmentsPhase 2Double-blindParticipant-centred approachStudy drugPrimary endpointSecondary endpointsCommunity-dwellingHealth recordsHealthcare utilizationContiguous US statesViral persistencePatient groupDrug treatmentDevelopment and multinational validation of an algorithmic strategy for high Lp(a) screening
Aminorroaya A, Dhingra L, Oikonomou E, Saadatagah S, Thangaraj P, Vasisht Shankar S, Spatz E, Khera R. Development and multinational validation of an algorithmic strategy for high Lp(a) screening. Nature Cardiovascular Research 2024, 3: 558-566. PMID: 39195936, DOI: 10.1038/s44161-024-00469-1.Peer-Reviewed Original ResearchElectronic health recordsAssociated with premature atherosclerotic cardiovascular diseaseElevated Lp(aHealth recordsUK BiobankPremature atherosclerotic cardiovascular diseaseMachine learning modelsAtherosclerotic cardiovascular diseaseCohort studyReal-world settingsTargeted screeningCardiovascular diseaseLearning modelsNovel targeted therapeuticsAlgorithmic strategiesCohortProbability thresholdScreeningClinical featuresValidation cohortElevated lipoproteinRisk inspectionARICLp(a
2023
Multinational patterns of second line antihyperglycaemic drug initiation across cardiovascular risk groups: federated pharmacoepidemiological evaluation in LEGEND-T2DM
Khera R, Dhingra L, Aminorroaya A, Li K, Zhou J, Arshad F, Blacketer C, Bowring M, Bu F, Cook M, Dorr D, Duarte-Salles T, DuVall S, Falconer T, French T, Hanchrow E, Horban S, Lau W, Li J, Liu Y, Lu Y, Man K, Matheny M, Mathioudakis N, McLemore M, Minty E, Morales D, Nagy P, Nishimura A, Ostropolets A, Pistillo A, Posada J, Pratt N, Reyes C, Ross J, Seager S, Shah N, Simon K, Wan E, Yang J, Yin C, You S, Schuemie M, Ryan P, Hripcsak G, Krumholz H, Suchard M. Multinational patterns of second line antihyperglycaemic drug initiation across cardiovascular risk groups: federated pharmacoepidemiological evaluation in LEGEND-T2DM. BMJ Medicine 2023, 2: e000651. PMID: 37829182, PMCID: PMC10565313, DOI: 10.1136/bmjmed-2023-000651.Peer-Reviewed Original ResearchType 2 diabetes mellitusSecond-line treatmentCardiovascular risk groupsDiabetes mellitusCardiovascular diseaseAntihyperglycaemic drugsLine treatmentRisk groupsObservational Health Data SciencesGlucagon-like peptide-1 receptor agonistsElectronic health recordsSodium-glucose cotransporter 2 inhibitorsCalendar year trendsPeptide-1 receptor agonistsUS databaseOutcomes of patientsCotransporter 2 inhibitorsAdministrative claims databaseSecond-line drugsHealth recordsSodium-glucose cotransporter-2 inhibitorsMedication useMetformin monotherapyGuideline recommendationsOutcome measuresCardiovascular Care Innovation through Data-Driven Discoveries in the Electronic Health Record
Dhingra L, Shen M, Mangla A, Khera R. Cardiovascular Care Innovation through Data-Driven Discoveries in the Electronic Health Record. The American Journal Of Cardiology 2023, 203: 136-148. PMID: 37499593, PMCID: PMC10865722, DOI: 10.1016/j.amjcard.2023.06.104.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsElectronic health recordsData elementsUnstructured data streamsUnstructured data elementsNatural language processingCommon data modelHealth recordsStructured data elementsComputer visionUnstructured dataData streamsHeterogeneity challengesSeamless deliveryData modelLanguage processingData storageFree textClinical narrativesComputational phenotypesOngoing workPatient informationRapid innovationSpecific expertiseConfidentialityOngoing innovationClinical Risk Prediction Models with Meta-Learning Prototypes of Patient Heterogeneity
Zhang L, Khera R, Mortazavi B. Clinical Risk Prediction Models with Meta-Learning Prototypes of Patient Heterogeneity. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2023, 00: 1-4. PMID: 38083199, PMCID: PMC11007255, DOI: 10.1109/embc40787.2023.10340765.Peer-Reviewed Original ResearchDeveloping Validated Tools to Identify Pulmonary Embolism in Electronic Databases: Rationale and Design of the PE-EHR+ Study
Bikdeli B, Lo Y, Khairani C, Bejjani A, Jimenez D, Barco S, Mahajan S, Caraballo C, Secemsky E, Klok F, Hunsaker A, Aghayev A, Muriel A, Wang Y, Hussain M, Appah-Sampong A, Lu Y, Lin Z, Aneja S, Khera R, Goldhaber S, Zhou L, Monreal M, Krumholz H, Piazza G. Developing Validated Tools to Identify Pulmonary Embolism in Electronic Databases: Rationale and Design of the PE-EHR+ Study. Thrombosis And Haemostasis 2023, 123: 649-662. PMID: 36809777, PMCID: PMC11200175, DOI: 10.1055/a-2039-3222.Peer-Reviewed Original ResearchConceptsElectronic health recordsNLP algorithmNatural language processing toolsLanguage processing toolsPrincipal discharge diagnosisICD-10 codesDischarge diagnosisNLP toolsChart reviewHealth systemProcessing toolsYale New Haven Health SystemPatient identificationElectronic databasesHealth recordsData validationHigh-risk PEPulmonary Embolism ResearchSecondary discharge diagnosisIdentification of patientsManual chart reviewNegative predictive valueCodeRadiology reportsAlgorithm
2021
Electronic health record risk score provides earlier prognostication of clinical outcomes in patients admitted to the cardiac intensive care unit
Kunitomo Y, Thomas A, Chouairi F, Canavan ME, Kochar A, Khera R, Katz JN, Murphy C, Jentzer J, Ahmad T, Desai NR, Brennan J, Miller PE. Electronic health record risk score provides earlier prognostication of clinical outcomes in patients admitted to the cardiac intensive care unit. American Heart Journal 2021, 238: 85-88. PMID: 33891906, DOI: 10.1016/j.ahj.2021.04.004.Peer-Reviewed Original ResearchConceptsCardiac intensive care unitIntensive care unitRothman IndexCare unitRisk scoreModern cardiac intensive care unitSequential Organ Failure Assessment scoreOrgan Failure Assessment scoreElectronic health recordsCICU mortalityCICU patientsSOFA scoreCICU admissionClinical outcomesEarly prognosticationObservational studyPrognostic abilityAssessment scoresOutcome predictionHealth recordsGood calibrationSuperior discriminationPatientsAdmissionScores
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