2019
Developing Customizable Cancer Information Extraction Modules for Pathology Reports Using CLAMP
Soysal E, Warner J, Wang J, Jiang M, Harvey K, Jain S, Dong X, Song H, Siddhanamatha H, Wang L, Dai Q, Chen Q, Du X, Tao C, Yang P, Denny J, Liu H, Xu H. Developing Customizable Cancer Information Extraction Modules for Pathology Reports Using CLAMP. 2019, 264: 1041-1045. PMID: 31438083, PMCID: PMC7359882, DOI: 10.3233/shti190383.Peer-Reviewed Original ResearchConceptsElectronic health recordsNLP solutionNatural language processing technologyInformation extraction moduleLanguage processing technologyInformation extraction tasksUser-friendly interfaceBest F-measureInformation extractionExtraction moduleExtraction taskCustomizable modulesNLP systemsF-measureAcademic useHealth recordsComparable performanceProcessing technologyVanderbilt University Medical CenterModuleDiverse typesInformationNLPSubstantial effortSystemDiscovery of Noncancer Drug Effects on Survival in Electronic Health Records of Patients With Cancer: A New Paradigm for Drug Repurposing
Wu Y, Warner J, Wang L, Jiang M, Xu J, Chen Q, Nian H, Dai Q, Du X, Yang P, Denny J, Liu H, Xu H. Discovery of Noncancer Drug Effects on Survival in Electronic Health Records of Patients With Cancer: A New Paradigm for Drug Repurposing. JCO Clinical Cancer Informatics 2019, 3: cci.19.00001. PMID: 31141421, PMCID: PMC6693869, DOI: 10.1200/cci.19.00001.Peer-Reviewed Original ResearchConceptsVanderbilt University Medical CenterCancer survivalMayo ClinicDrug repurposingNoncancer drugsElectronic health record dataCancer registry dataEHR dataClinical trial evaluationOverall cancer survivalUniversity Medical CenterHealth record dataElectronic health recordsTreatment of cancerClinical trialsDrug classesRegistry dataMedical CenterDrug effectsSignificant associationLongitudinal EHRNew indicationsPatientsCancerHealth records
2016
Evaluation of a Prediction Model for the Development of Atrial Fibrillation in a Repository of Electronic Medical Records
Kolek M, Graves A, Xu M, Bian A, Teixeira P, Shoemaker M, Parvez B, Xu H, Heckbert S, Ellinor P, Benjamin E, Alonso A, Denny J, Moons K, Shintani A, Harrell F, Roden D, Darbar D. Evaluation of a Prediction Model for the Development of Atrial Fibrillation in a Repository of Electronic Medical Records. JAMA Cardiology 2016, 1: 1007-1013. PMID: 27732699, PMCID: PMC5293184, DOI: 10.1001/jamacardio.2016.3366.Peer-Reviewed Original ResearchIncident atrial fibrillationElectronic medical recordsCHARGE-AF modelAtrial fibrillationRisk prediction modelMedical recordsEMR cohortHistory of AFInternal medicine outpatient clinicProspective cohort studyDiastolic blood pressureMedicine outpatient clinicIndividuals 40 yearsType 2 diabetesHigh-risk individualsVanderbilt University Medical CenterUniversity Medical CenterLow-risk individualsPoor calibrationAfrican AmericansFuture risk modelsHealth care expendituresAF managementCohort studyEchocardiographic variablesA long journey to short abbreviations: developing an open-source framework for clinical abbreviation recognition and disambiguation (CARD)
Wu Y, Denny J, Rosenbloom S, Miller R, Giuse D, Wang L, Blanquicett C, Soysal E, Xu J, Xu H. A long journey to short abbreviations: developing an open-source framework for clinical abbreviation recognition and disambiguation (CARD). Journal Of The American Medical Informatics Association 2016, 24: e79-e86. PMID: 27539197, PMCID: PMC7651947, DOI: 10.1093/jamia/ocw109.Peer-Reviewed Original ResearchConceptsClinical NLP systemsOpen-source frameworkNLP systemsClinical corpusClinical abbreviationsClinic visit notesSense inventoryKnowledge Extraction SystemAbbreviation recognitionWord sense disambiguation methodDischarge summariesF1 scoreExternal corpusClinical narrativesSense disambiguation methodSystem capabilitiesVanderbilt University Medical CenterWrapperFrequent abbreviationsDisambiguation methodMetaMapAbbreviation identificationCardsVisit notesDisambiguation
2014
Validating drug repurposing signals using electronic health records: a case study of metformin associated with reduced cancer mortality
Xu H, Aldrich M, Chen Q, Liu H, Peterson N, Dai Q, Levy M, Shah A, Han X, Ruan X, Jiang M, Li Y, St Julien J, Warner J, Friedman C, Roden D, Denny J. Validating drug repurposing signals using electronic health records: a case study of metformin associated with reduced cancer mortality. Journal Of The American Medical Informatics Association 2014, 22: 179-191. PMID: 25053577, PMCID: PMC4433365, DOI: 10.1136/amiajnl-2014-002649.Peer-Reviewed Original ResearchConceptsType 2 diabetes patientsElectronic health recordsCancer patientsCancer mortalityDiabetes patientsEHR dataNon-diabetic cancer patientsCox proportional hazards modelDrug exposure informationOral hypoglycemic medicationsCharlson Comorbidity IndexNon-diabetic patientsUse of metforminCancer diagnosisHealth recordsSite-specific cancersBody mass indexProportional hazards modelVanderbilt University Medical CenterUniversity Medical CenterLarge electronic health recordHypoglycemic medicationsCause mortalityComorbidity indexInsulin use
2012
Comparative analysis of pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records
Liu M, Hinz E, Matheny M, Denny J, Schildcrout J, Miller R, Xu H. Comparative analysis of pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records. Journal Of The American Medical Informatics Association 2012, 20: 420-426. PMID: 23161894, PMCID: PMC3628053, DOI: 10.1136/amiajnl-2012-001119.Peer-Reviewed Original ResearchConceptsAdverse drug reactionsElectronic medical recordsProportional reporting ratioVanderbilt University Medical CenterSpontaneous reporting systemDrug-event pairsDrug reactionsMedical recordsMedication ordersAbnormal laboratory resultsDrug-exposed groupNew adverse drug reactionsUniversity Medical CenterSpecific drug administrationReference standardLaboratory resultsUnexposed groupGamma Poisson ShrinkerMedical CenterPatient harmDrug AdministrationPharmacovigilance measuresBayesian confidence propagation neural networkEarly detectionReporting ratioOptimizing Drug Outcomes Through Pharmacogenetics: A Case for Preemptive Genotyping
Schildcrout J, Denny J, Bowton E, Gregg W, Pulley J, Basford M, Cowan J, Xu H, Ramirez A, Crawford D, Ritchie M, Peterson J, Masys D, Wilke R, Roden D. Optimizing Drug Outcomes Through Pharmacogenetics: A Case for Preemptive Genotyping. Clinical Pharmacology & Therapeutics 2012, 92: 235-242. PMID: 22739144, PMCID: PMC3785311, DOI: 10.1038/clpt.2012.66.Peer-Reviewed Original ResearchConceptsVanderbilt University Medical CenterAdverse eventsPreemptive genotypingPotential adverse eventsUniversity Medical CenterHome patientsPharmacogenetic associationsMedical CenterVariant allelesMedicationsDrug outcomesPatient safetyDrug decision makingRelevant genetic variantsRoutine integrationTarget drugsGenetic variantsOutcomesFrequency of opportunitiesGenotypingSafetyPrescribingPatientsCohortPharmacogenetics