2023
Enhanced Identification of Hispanic Ethnicity Using Clinical Data
Ochoa-Allemant P, Tate J, Williams E, Gordon K, Marconi V, Bensley K, Rentsch C, Wang K, Taddei T, Justice A, Cohorts F. Enhanced Identification of Hispanic Ethnicity Using Clinical Data. Medical Care 2023, 61: 200-205. PMID: 36893404, PMCID: PMC10114212, DOI: 10.1097/mlr.0000000000001824.Peer-Reviewed Original ResearchMeSH KeywordsAgedCohort StudiesDelivery of Health CareElectronic Health RecordsEthnicityHispanic or LatinoHumansMedicareUnited StatesUnited States Department of Veterans AffairsConceptsBurden of diseaseHispanic patientsCountry of birthClinical dataHispanic ethnicityNon-Hispanic white patientsSex-adjusted prevalenceChronic liver diseaseHuman immunodeficiency virusDemographic characteristicsElectronic health record dataHealth careHealth record dataPrevalence of conditionsUS health care systemMedicare administrative dataHealth care systemWhite patientsLiver diseaseImmunodeficiency virusSelf-reported ethnicityHigh prevalenceGastric cancerHepatocellular carcinomaVeteran population
2020
High concordance between chart review adjudication and electronic medical record data to identify prevalent and incident diabetes mellitus among persons with and without HIV
McGinnis KA, Justice AC, Bailin S, Wellons M, Freiberg M, Koethe JR. High concordance between chart review adjudication and electronic medical record data to identify prevalent and incident diabetes mellitus among persons with and without HIV. Pharmacoepidemiology And Drug Safety 2020, 29: 1432-1439. PMID: 33006179, PMCID: PMC7810212, DOI: 10.1002/pds.5111.Peer-Reviewed Original ResearchMeSH KeywordsCohort StudiesDiabetes MellitusElectronic Health RecordsHIV InfectionsHumansMaleUnited StatesVeteransConceptsVeterans Health AdministrationElectronic medical recordsChart reviewVeterans Aging Cohort Study Biomarker CohortElectronic medical record dataPhysician chart reviewHIV-negative participantsIncident diabetes mellitusICD-9 codesMedical record dataIndication of diabetesPhysician adjudicationIncident diabetesDiabetes mellitusHIV infectionBiomarker cohortHIV statusDiabetes prevalenceMedical recordsMedication recordsLaboratory valuesEpidemiologic studiesDiabetes diagnosisDiagnostic criteriaDiabetesEstimating Aspirin Overuse for Primary Prevention of Atherosclerotic Cardiovascular Disease (from a Nationwide Healthcare System)
Ong SY, Chui P, Bhargava A, Justice A, Hauser RG. Estimating Aspirin Overuse for Primary Prevention of Atherosclerotic Cardiovascular Disease (from a Nationwide Healthcare System). The American Journal Of Cardiology 2020, 137: 25-30. PMID: 32991852, DOI: 10.1016/j.amjcard.2020.09.042.Peer-Reviewed Original ResearchConceptsLow-dose aspirinElectronic health recordsSelf-reported useEHR dataPatients' self-reported useLow-dose aspirin useAtherosclerotic cardiovascular diseaseAmerican Heart AssociationEHR recordsNon-specific terminologyAspirin usePrimary preventionHeart AssociationCardiovascular diseaseAmerican CollegeAspirinPatientsHealth recordsEHR implementationEHR searchesImplementable guidelinesGuidelinesRecordsDiseaseCardiologyValidating a non-invasive, ALT-based non-alcoholic fatty liver phenotype in the million veteran program
Serper M, Vujkovic M, Kaplan DE, Carr RM, Lee KM, Shao Q, Miller DR, Reaven PD, Phillips LS, O’Donnell C, Meigs JB, Wilson PWF, Vickers-Smith R, Kranzler HR, Justice AC, Gaziano JM, Muralidhar S, Pyarajan S, DuVall SL, Assimes TL, Lee JS, Tsao PS, Rader DJ, Damrauer SM, Lynch JA, Saleheen D, Voight BF, Chang KM, . Validating a non-invasive, ALT-based non-alcoholic fatty liver phenotype in the million veteran program. PLOS ONE 2020, 15: e0237430. PMID: 32841307, PMCID: PMC7447043, DOI: 10.1371/journal.pone.0237430.Peer-Reviewed Original ResearchMeSH Keywords17-Hydroxysteroid DehydrogenasesAbdomenAdaptor Proteins, Signal TransducingAgedAlanine TransaminaseElectronic Health RecordsFemaleGenetic LociGenetic Predisposition to DiseaseGenetic VariationHumansLipaseLiverLysophospholipaseMaleMembrane ProteinsMiddle AgedNon-alcoholic Fatty Liver DiseasePhenotypeRisk FactorsVeteransConceptsMetabolic risk factorsNAFLD phenotypeAlanine aminotransferaseUnits/LElectronic health recordsAdvanced fibrosisRisk factorsMillion Veteran ProgramAlcohol consumptionNon-invasive criteriaNormal alanine aminotransferaseNAFLD fibrosis scorePopulation-based studyGenetic variantsFatty liver phenotypeVeteran ProgramPNPLA3 locusNAFLD riskLiver biopsyLiver diseaseFibrosis scoreEHR reviewUS veteransBiopsy dataAbdominal imagingExtracting lung function measurements to enhance phenotyping of chronic obstructive pulmonary disease (COPD) in an electronic health record using automated tools
Akgün KM, Sigel K, Cheung KH, Kidwai-Khan F, Bryant AK, Brandt C, Justice A, Crothers K. Extracting lung function measurements to enhance phenotyping of chronic obstructive pulmonary disease (COPD) in an electronic health record using automated tools. PLOS ONE 2020, 15: e0227730. PMID: 31945115, PMCID: PMC6964890, DOI: 10.1371/journal.pone.0227730.Peer-Reviewed Original ResearchMeSH KeywordsCohort StudiesData MiningElectronic Health RecordsForced Expiratory VolumeHealth Information SystemsHospitalizationHumansLungNatural Language ProcessingPulmonary Disease, Chronic ObstructiveSeverity of Illness IndexSoftwareUnited StatesUnited States Department of Veterans AffairsVeteransVital CapacityConceptsChronic obstructive pulmonary diseaseVeterans Aging Cohort StudyObstructive pulmonary diseaseFEV1 valuesPulmonary diseasePhenotyping of patientsPulmonary function testsAging Cohort StudyLung function measurementsElectronic health record dataHealth record dataStructured electronic health record dataPositive predictive valueElectronic health recordsAirflow obstructionChart reviewCohort studyExpiratory volumeCOPD phenotypesFunction testsVital capacityFEV1 measurementsDATA SOURCESPredictive valueClinical notes
2019
Measuring Exposure to Incarceration Using the Electronic Health Record
Wang EA, Long JB, McGinnis KA, Wang KH, Wildeman CJ, Kim C, Bucklen KB, Fiellin DA, Bates J, Brandt C, Justice AC. Measuring Exposure to Incarceration Using the Electronic Health Record. Medical Care 2019, 57: s157-s163. PMID: 31095055, PMCID: PMC8352066, DOI: 10.1097/mlr.0000000000001049.Peer-Reviewed Original ResearchMeSH KeywordsAdministrative Claims, HealthcareAdultCohort StudiesElectronic Health RecordsEthnicityFemaleHumansInformation Storage and RetrievalMaleMedicareMiddle AgedNatural Language ProcessingPrisonersSelf ReportSensitivity and SpecificityUnited StatesUnited States Department of Veterans AffairsVeteransConceptsVeterans Aging Cohort StudyElectronic health recordsHuman immunodeficiency virus-infected patientsVHA electronic health recordsNational observational cohortVirus-infected patientsHealth recordsAging Cohort StudyEHR dataHealth care disparitiesAdministrative dataRace/ethnicityIncarceration exposureObservational cohortUninfected patientsCohort studySpecificity 99.3DATA SOURCESCare disparitiesSpecificity 100Specificity 98.9Social determinantsMedicaid ServicesSpecificity 95.9Health information
2018
Using DNA methylation to validate an electronic medical record phenotype for smoking
McGinnis KA, Justice AC, Tate JP, Kranzler HR, Tindle HA, Becker WC, Concato J, Gelernter J, Li B, Zhang X, Zhao H, Crothers K, Xu K, Group F. Using DNA methylation to validate an electronic medical record phenotype for smoking. Addiction Biology 2018, 24: 1056-1065. PMID: 30284751, PMCID: PMC6541538, DOI: 10.1111/adb.12670.Peer-Reviewed Original ResearchMeSH KeywordsDNA MethylationElectronic Health RecordsFemaleHumansMaleMiddle AgedPhenotypeReproducibility of ResultsSelf ReportSmokingVeteransConceptsVeterans Aging Cohort StudyAging Cohort StudyStrong associationDNA methylation sitesSmoking metricsCohort studyCurrent smokingSmoking statusSpearman correlation coefficientBiomarker cohortBlood samplesSmoking behaviorCriterion standardLogistic regressionSmokingSmoking phenotypesCurve analysisGroup assignmentText notesAssociationDescriptive statisticsPhenotypeCorrelation coefficientGenetic discoveriesPercentProvider verification of electronic health record receipt and nonreceipt of direct-acting antivirals for the treatment of hepatitis C virus infection
Rentsch CT, Cartwright EJ, Gandhi NR, Brown ST, Rodriguez-Barradas MC, Goetz MB, Marconi VC, Gibert CL, Re VL, Fiellin DA, Justice AC, Tate JP. Provider verification of electronic health record receipt and nonreceipt of direct-acting antivirals for the treatment of hepatitis C virus infection. Annals Of Epidemiology 2018, 28: 808-811. PMID: 30195616, PMCID: PMC6318448, DOI: 10.1016/j.annepidem.2018.08.007.Peer-Reviewed Original ResearchConceptsHepatitis C virus infectionCorporate Data WarehouseChronic HCV infectionC virus infectionPositive predictive valuePredictive valueHCV infectionHCV treatmentVirus infectionVeterans Health Administration Corporate Data WarehouseChronic hepatitis C virus (HCV) infectionStudy periodModern treatment eraRetrospective cohort studyElectronic health record dataPharmacy fill recordsHealth record dataNegative predictive valueElectronic health recordsAntiviral regimenHCV therapyTreatment eraChart reviewCohort studyAntiviral treatmentRacial disparities in discontinuation of long-term opioid therapy following illicit drug use among black and white patients
Gaither JR, Gordon K, Crystal S, Edelman EJ, Kerns RD, Justice AC, Fiellin DA, Becker WC. Racial disparities in discontinuation of long-term opioid therapy following illicit drug use among black and white patients. Drug And Alcohol Dependence 2018, 192: 371-376. PMID: 30122319, PMCID: PMC7106601, DOI: 10.1016/j.drugalcdep.2018.05.033.Peer-Reviewed Original ResearchConceptsLong-term opioid therapyIllicit drug useUrine drug testsDrug useOpioid therapyWhite racePositive urine drug testDrug testsMonths of treatmentElectronic medical recordsWhite patientsChronic painPatient raceMedical recordsPatientsLogistic regressionOpioidsRacial disparitiesDrug testingCocaineCannabisTherapyCliniciansDiscontinuationPainAUDIT‐C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two US populations
Justice AC, Smith RV, Tate JP, McGinnis K, Xu K, Becker WC, Lee K, Lynch K, Sun N, Concato J, Fiellin DA, Zhao H, Gelernter J, Kranzler HR, Program O. AUDIT‐C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two US populations. Addiction 2018, 113: 2214-2224. PMID: 29972609, PMCID: PMC6226338, DOI: 10.1111/add.14374.Peer-Reviewed Original ResearchAccuracy of electronic health record data for the diagnosis of chronic obstructive pulmonary disease in persons living with HIV and uninfected persons
Crothers K, Rodriguez CV, Nance RM, Akgun K, Shahrir S, Kim J, Hoo G, Sharafkhaneh A, Crane HM, Justice AC. Accuracy of electronic health record data for the diagnosis of chronic obstructive pulmonary disease in persons living with HIV and uninfected persons. Pharmacoepidemiology And Drug Safety 2018, 28: 140-147. PMID: 29923258, PMCID: PMC6309326, DOI: 10.1002/pds.4567.Peer-Reviewed Original ResearchMeSH KeywordsAdministration, InhalationAge FactorsAlgorithmsBronchodilator AgentsCohort StudiesData AccuracyData Interpretation, StatisticalDrug PrescriptionsElectronic Health RecordsFemaleHIV InfectionsHumansInternational Classification of DiseasesLogistic ModelsMaleMiddle AgedNebulizers and VaporizersPrevalencePulmonary Disease, Chronic ObstructiveRisk FactorsSmokingSpirometryConceptsChronic obstructive pulmonary diseaseICD-9 codesObstructive pulmonary diseaseElectronic health record dataHealth record dataPulmonary diseaseHIV-Associated Lung Emphysema (EXHALE) studyIntegrated Clinical Systems cohortVeterans Aging Cohort StudyHIV uninfected personsAIDS Research NetworkAging Cohort StudyRecord dataEHR dataReceiver-operating curveCohort studyRespiratory symptomsHIV statusUninfected personsClinical variablesDevelopment cohortClinical indicationsSpirometry dataSpirometryUninfected individuals
2017
Utilizing patient data from the veterans administration electronic health record to support web-based clinical decision support: informatics challenges and issues from three clinical domains
Rajeevan N, Niehoff KM, Charpentier P, Levin FL, Justice A, Brandt CA, Fried TR, Miller PL. Utilizing patient data from the veterans administration electronic health record to support web-based clinical decision support: informatics challenges and issues from three clinical domains. BMC Medical Informatics And Decision Making 2017, 17: 111. PMID: 28724368, PMCID: PMC5517800, DOI: 10.1186/s12911-017-0501-x.Peer-Reviewed Original ResearchMeSH KeywordsDecision Support Systems, ClinicalElectronic Health RecordsHumansUnited StatesUnited States Department of Veterans AffairsConceptsClinical decision supportElectronic health recordsCDS systemsDecision supportPatient-specific clinical decision supportEHR environmentInformatics challengesWeb-based clinical decision supportHealth recordsPatient dataWeb technologiesData accessComputational infrastructureParticular architectureIssues/challengesDesign issuesSuch systemsInformatics methodsPowerful setData availabilityVeterans AdministrationInfrastructureVA electronic health recordClinical domainsUS Veterans Administration
2016
Estimating healthcare mobility in the Veterans Affairs Healthcare System
Wang KH, Goulet JL, Carroll CM, Skanderson M, Fodeh S, Erdos J, Womack JA, Abel EA, Bathulapalli H, Justice AC, Nunez-Smith M, Brandt CA. Estimating healthcare mobility in the Veterans Affairs Healthcare System. BMC Health Services Research 2016, 16: 609. PMID: 27769221, PMCID: PMC5075153, DOI: 10.1186/s12913-016-1841-4.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overDelivery of Health CareElectronic Health RecordsEmigration and ImmigrationFemaleHospitals, VeteransHumansMaleMental DisordersMiddle AgedPatient Acceptance of Health CareRetrospective StudiesUnited StatesUnited States Department of Veterans AffairsVeteransVeterans HealthYoung AdultConceptsHealthcare systemVeterans Health Administration electronic health recordsVeterans Affairs Healthcare SystemHealthcare mobilityRetrospective cohort studyHepatitis C virusOutcomes of careDifferent healthcare systemsDistinct healthcare systemsElectronic health recordsClinical characteristicsCohort studyHealthcare utilizationC virusSpecialty carePsychiatric disordersYounger veteransDisease preventionYounger agePopulation healthHealth recordsVeteransStatus changesCareYear periodComparison of AUDIT-C collected via electronic medical record and self-administered research survey in HIV infected and uninfected patients
McGinnis KA, Tate JP, Williams EC, Skanderson M, Bryant KJ, Gordon AJ, Kraemer KL, Maisto SA, Crystal S, Fiellin DA, Justice AC. Comparison of AUDIT-C collected via electronic medical record and self-administered research survey in HIV infected and uninfected patients. Drug And Alcohol Dependence 2016, 168: 196-202. PMID: 27694059, PMCID: PMC5086273, DOI: 10.1016/j.drugalcdep.2016.09.015.Peer-Reviewed Original ResearchMeSH KeywordsAdultAlcohol DrinkingAlcoholismCohort StudiesElectronic Health RecordsFemaleHIV InfectionsHumansMaleMiddle AgedSurveys and QuestionnairesVeteransConceptsUnhealthy alcohol useVeterans Aging Cohort StudyAlcohol useClinical screeningElectronic medical record dataHepatitis C infectionAging Cohort StudyMedical record dataElectronic medical recordsUninfected womenC infectionUninfected menUninfected patientsCohort studyMedical recordsUninfected individualsClinical decisionHIVModerate agreementRecord dataEMR dataMenAssess agreementWomenEMR
2015
Depression and Human Immunodeficiency Virus Infection Are Risk Factors for Incident Heart Failure Among Veterans
White JR, Chang CC, So-Armah KA, Stewart JC, Gupta SK, Butt AA, Gibert CL, Rimland D, Rodriguez-Barradas MC, Leaf DA, Bedimo RJ, Gottdiener JS, Kop WJ, Gottlieb SS, Budoff MJ, Khambaty T, Tindle HA, Justice AC, Freiberg MS. Depression and Human Immunodeficiency Virus Infection Are Risk Factors for Incident Heart Failure Among Veterans. Circulation 2015, 132: 1630-1638. PMID: 26358261, PMCID: PMC4624488, DOI: 10.1161/circulationaha.114.014443.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgingAntidepressive AgentsAnti-HIV AgentsCardiovascular DiseasesComorbidityDepressive Disorder, MajorDiabetes MellitusElectronic Health RecordsEthnicityFemaleFollow-Up StudiesHeart FailureHIV InfectionsHumansHyperlipidemiasIncidenceKidney DiseasesMaleMiddle AgedProspective StudiesRisk FactorsSubstance-Related DisordersUnited StatesVeteransConceptsMajor depressive disorderRisk factorsHuman immunodeficiency virus (HIV) infectionCox proportional hazards modelBaseline antidepressant useIncident HF eventsRisk of HFIncident heart failureImmunodeficiency virus infectionIndependent risk factorCohort Study participantsHeart failure riskProportional hazards modelHF morbidityCommon comorbiditiesIncident HFAntidepressant useHeart failureHIV infectionHIV- participantsPrimary outcomeNinth RevisionHF eventsMedical recordsDepressive disorder
2013
Acetaminophen receipt among HIV‐infected patients with advanced hepatic fibrosis
Edelman EJ, Gordon KS, Re V, Skanderson M, Fiellin DA, Justice AC, Team F. Acetaminophen receipt among HIV‐infected patients with advanced hepatic fibrosis. Pharmacoepidemiology And Drug Safety 2013, 22: 1352-1356. PMID: 24285468, PMCID: PMC4164158, DOI: 10.1002/pds.3517.Peer-Reviewed Original ResearchConceptsAdvanced hepatic fibrosisAcetaminophen exposureHCV statusHepatic fibrosisHIV/HCV-coinfected patientsVeterans Aging Cohort StudyAdvanced liver fibrosisAging Cohort StudyAcetaminophen-induced hepatotoxicitySample of HIVCross-sectional associationsPolytomous logistic regressionAlcohol use disorderCross-sectional analysisAcetaminophen prescriptionsAcetaminophen useHIV-monoinfectedFIB-4Cohort studyLiver injuryPlatelet countLiver fibrosisAlanine aminotransferaseHIVPatientsAgreement Between Electronic Medical Record-based and Self-administered Pain Numeric Rating Scale
Goulet JL, Brandt C, Crystal S, Fiellin DA, Gibert C, Gordon AJ, Kerns RD, Maisto S, Justice AC. Agreement Between Electronic Medical Record-based and Self-administered Pain Numeric Rating Scale. Medical Care 2013, 51: 245-250. PMID: 23222528, PMCID: PMC3572341, DOI: 10.1097/mlr.0b013e318277f1ad.Peer-Reviewed Original ResearchConceptsNumeric rating scaleElectronic medical recordsPain screeningMedical recordsPain numeric rating scaleRating ScaleModerate-severe painVeterans Affairs medical facilitiesPatients' electronic medical recordsMajor depressive disorderEMR dataQuality of careUnderestimation of painSample of veteransPosttraumatic stress disorderHealth care systemClinical characteristicsPatient characteristicsNRS scoresPain careDepressive disorderSurvey scoresPainLevel of agreementStress disorderPersonal Health Record Use and Its Association with Antiretroviral Adherence: Survey and Medical Record Data from 1871 US Veterans Infected with HIV
Keith McInnes D, Shimada SL, Rao SR, Quill A, Duggal M, Gifford AL, Brandt CA, Houston TK, Ohl ME, Gordon KS, Mattocks KM, Kazis LE, Justice AC. Personal Health Record Use and Its Association with Antiretroviral Adherence: Survey and Medical Record Data from 1871 US Veterans Infected with HIV. AIDS And Behavior 2013, 17: 3091-3100. PMID: 23334359, DOI: 10.1007/s10461-012-0399-3.Peer-Reviewed Original ResearchConceptsPersonal health record useMedical record dataPHR useAntiretroviral adherenceElectronic personal health record useVeterans Aging Cohort StudyRecord useHIV care processesMedication possession ratioAging Cohort StudyPharmacy refill dataRecord dataImproved patient outcomesCross-sectional surveyCohort studyPossession ratioDepression careRefill dataMedication adherenceUS veteransPatient outcomesAdherence measuresCare processesSocio-demographic variablesAdherence
2011
Validating Smoking Data From the Veteran’s Affairs Health Factors Dataset, an Electronic Data Source
McGinnis KA, Brandt CA, Skanderson M, Justice AC, Shahrir S, Butt AA, Brown ST, Freiberg MS, Gibert CL, Goetz MB, Kim JW, Pisani MA, Rimland D, Rodriguez-Barradas MC, Sico JJ, Tindle HA, Crothers K. Validating Smoking Data From the Veteran’s Affairs Health Factors Dataset, an Electronic Data Source. Nicotine & Tobacco Research 2011, 13: 1233-1239. PMID: 21911825, PMCID: PMC3223583, DOI: 10.1093/ntr/ntr206.Peer-Reviewed Original ResearchConceptsSmoking statusHealth factorsSmoking dataKappa statisticsSmoking variablesVeterans Aging Cohort StudyAging Cohort StudySelf-reported smoking dataCohort studyCurrent smokersSmoking interventionsVirtual cohortElectronic data sourcesEMR dataFuture studiesStatusParticipantsFactorsHIVSmokersSmokingStudy surveyCohortThe Yale cTAKES extensions for document classification: architecture and application
Garla V, Re V, Dorey-Stein Z, Kidwai F, Scotch M, Womack J, Justice A, Brandt C. The Yale cTAKES extensions for document classification: architecture and application. Journal Of The American Medical Informatics Association 2011, 18: 614-620. PMID: 21622934, PMCID: PMC3168305, DOI: 10.1136/amiajnl-2011-000093.Peer-Reviewed Original ResearchConceptsDocument classificationFeature extractionProcessing systemKnowledge Extraction SystemDocument classification systemClinical Text AnalysisDocument classifierFeature representationRadiology reportsOpen sourceClinical textText analysisTechnical challengesClassificationExtraction systemClassification systemRepresentationClassifierSemanticsSystemArchitectureRetrievalExtractionSyntaxExtension