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 ResearchConceptsBurden 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
2022
Survival analysis of localized prostate cancer with deep learning
Dai X, Park JH, Yoo S, D’Imperio N, McMahon BH, Rentsch CT, Tate JP, Justice AC. Survival analysis of localized prostate cancer with deep learning. Scientific Reports 2022, 12: 17821. PMID: 36280773, PMCID: PMC9592586, DOI: 10.1038/s41598-022-22118-y.Peer-Reviewed Original ResearchConceptsProstate cancer mortalityComposite outcomeCancer mortalityRisk predictionTime-dependent c-statisticsProstate-specific antigen (PSA) testLarge integrated healthcare systemLocalized prostate cancerElectronic health record dataClinical decision-making processProstate cancer patientsIntegrated healthcare systemProstate Cancer Risk PredictionHealth record dataLarge-scale electronic health record dataRisk prediction modelCancer risk predictionAntigen testC-statisticCancer patientsProstate cancerClinical decision systemSurvival analysisVeterans AffairsDeep learningUsing the biomarker cotinine and survey self-report to validate smoking data from United States Veterans Health Administration electronic health records
McGinnis K, Skanderson M, Justice A, Tindle H, Akgün K, Wrona A, Freiberg M, Goetz M, Rodriguez-Barradas M, Brown S, Crothers K. Using the biomarker cotinine and survey self-report to validate smoking data from United States Veterans Health Administration electronic health records. JAMIA Open 2022, 5: ooac040. PMID: 37252267, PMCID: PMC9154288, DOI: 10.1093/jamiaopen/ooac040.Peer-Reviewed Original ResearchICD-10 codesClinical remindersCurrent smokingSmoking dataSelf-reported smoking statusVeterans Health Administration electronic health recordsCohort Study participantsElectronic health record dataHealth record dataElectronic health recordsSmoking informationSmoking statusSalivary cotinineEpidemiologic studiesInternational ClassificationSmokingCotinineStudy participantsICD-10Health systemHealth recordsRecord dataKappa statisticsAfrican AmericansRemindersGeographic and temporal variation in racial and ethnic disparities in SARS-CoV-2 positivity between February 2020 and August 2021 in the United States
Ferguson JM, Justice AC, Osborne TF, Magid HSA, Purnell AL, Rentsch CT. Geographic and temporal variation in racial and ethnic disparities in SARS-CoV-2 positivity between February 2020 and August 2021 in the United States. Scientific Reports 2022, 12: 273. PMID: 34997001, PMCID: PMC8741774, DOI: 10.1038/s41598-021-03967-5.Peer-Reviewed Original Research
2021
Pharmacoepidemiology, Machine Learning, and COVID-19: An Intent-to-Treat Analysis of Hydroxychloroquine, With or Without Azithromycin, and COVID-19 Outcomes Among Hospitalized US Veterans
Gerlovin H, Posner DC, Ho YL, Rentsch CT, Tate JP, King JT, Kurgansky KE, Danciu I, Costa L, Linares FA, Goethert ID, Jacobson DA, Freiberg MS, Begoli E, Muralidhar S, Ramoni RB, Tourassi G, Gaziano JM, Justice AC, Gagnon DR, Cho K. Pharmacoepidemiology, Machine Learning, and COVID-19: An Intent-to-Treat Analysis of Hydroxychloroquine, With or Without Azithromycin, and COVID-19 Outcomes Among Hospitalized US Veterans. American Journal Of Epidemiology 2021, 190: 2405-2419. PMID: 34165150, PMCID: PMC8384407, DOI: 10.1093/aje/kwab183.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAnti-Bacterial AgentsAzithromycinCOVID-19COVID-19 Drug TreatmentDrug Therapy, CombinationFemaleHospitalizationHumansHydroxychloroquineIntention to Treat AnalysisMachine LearningMaleMiddle AgedPharmacoepidemiologyRetrospective StudiesSARS-CoV-2Treatment OutcomeUnited StatesVeteransConceptsUS veteransCOVID-19Veterans Affairs Health Care SystemRecent randomized clinical trialsAdministration of hydroxychloroquineEffectiveness of hydroxychloroquineRisk of intubationEffect of hydroxychloroquineElectronic health record dataRandomized clinical trialsTreatment of patientsUS veteran populationCOVID-19 outcomesCoronavirus disease 2019Health record dataRigorous study designsHealth care systemSurvival benefitTreat analysisEarly therapyHospitalized populationClinical trialsObservational studyDisease 2019Hydroxychloroquine
2020
Association of OPRM1 Functional Coding Variant With Opioid Use Disorder
Zhou H, Rentsch CT, Cheng Z, Kember RL, Nunez YZ, Sherva RM, Tate JP, Dao C, Xu K, Polimanti R, Farrer LA, Justice AC, Kranzler HR, Gelernter J. Association of OPRM1 Functional Coding Variant With Opioid Use Disorder. JAMA Psychiatry 2020, 77: 1072-1080. PMID: 32492095, PMCID: PMC7270886, DOI: 10.1001/jamapsychiatry.2020.1206.Peer-Reviewed Original ResearchConceptsOpioid use disorderUse disordersMendelian randomization analysisAfrican American individualsMAIN OUTCOMEFunctional coding variantSignificant associationCausal associationRandomization analysisElectronic health record dataCurrent opioid crisisAmerican individualsHealth record dataCognitive performanceInternational Statistical ClassificationRelated Health ProblemsPotential causal associationAmerican controlsEuropean American controlsAfrican-American controlsCoding variantBuprenorphine treatmentOUD diagnosisTobacco smokingNinth RevisionValidation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV
Rodriguez-Barradas MC, McGinnis KA, Akgün K, Tate JP, Brown ST, Butt AA, Fine M, Goetz MB, Graber CJ, Huang L, Rimland D, Justice A, Crothers K. Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV. Pneumonia 2020, 12: 6. PMID: 32724760, PMCID: PMC7382068, DOI: 10.1186/s41479-020-00068-1.Peer-Reviewed Original ResearchICD-9 codesPharmacy dataUninfected groupEHR algorithmPrimary positionOverall positive predictive valueResultsFive hundred fortyGroup of patientsElectronic health record dataICD-9 diagnosisHealth record dataPositive predictive valueCode-based algorithmsElectronic health recordsCAP hospitalizationsCOPD exacerbationsMicrobiologic workupOverall PPVUninfected patientsAspiration pneumoniaPneumonia hospitalizationsHospital admissionHIV statusCaP diagnosisEtiologic diagnosisUsing longitudinal PSA values and machine learning for predicting progression of early stage prostate cancer in veterans.
Danciu I, Erwin S, Agasthya G, Janet T, McMahon B, Tourassi G, Justice A. Using longitudinal PSA values and machine learning for predicting progression of early stage prostate cancer in veterans. Journal Of Clinical Oncology 2020, 38: e17554-e17554. DOI: 10.1200/jco.2020.38.15_suppl.e17554.Peer-Reviewed Original ResearchDisease progressionClinical data warehouseLast PSAPSA valuesEarly-stage prostate cancerSEER summary stageTime of diagnosisAppropriate treatment planProstate cancer patientsStage prostate cancerHealth record dataProstate cancer diagnosisEvidence-based approachClinical decision supportCancer RegistryRadium-223Cancer patientsGleason scoreSummary stageLaboratory valuesProstate cancerTreatment planOutcome predictionDiagnosisPSAExtracting 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
Opioid use trajectory groups and changes in a physical health biomarker among HIV-positive and uninfected patients receiving opioid agonist treatment
McGinnis KA, Fiellin DA, Skanderson M, Hser YI, Lucas GM, Justice AC, Tate JP, Group F. Opioid use trajectory groups and changes in a physical health biomarker among HIV-positive and uninfected patients receiving opioid agonist treatment. Drug And Alcohol Dependence 2019, 204: 107511. PMID: 31546119, PMCID: PMC6993986, DOI: 10.1016/j.drugalcdep.2019.06.014.Peer-Reviewed Original ResearchConceptsOpioid agonist treatmentHIV-1 RNADetectable HIV-1 RNAUninfected patientsAgonist treatmentVeterans Aging Cohort StudyResponsiveness of CD4Substance use disorder treatmentHealth effectsUrine toxicology resultsUrine toxicology testsAging Cohort StudyElectronic health record dataUse disorder treatmentHealth record dataPhysical health effectsRace/ethnicityOAT initiationCohort studyOpioid useBiomarker changesToxicology resultsNegative groupUninfected individualsDisorder treatmentRegional and Rural-Urban Differences in the Use of Direct-acting Antiviral Agents for Hepatitis C Virus
Njei B, Esserman D, Krishnan S, Ohl M, Tate JP, Hauser RG, Taddei T, Lim J, Justice AC. Regional and Rural-Urban Differences in the Use of Direct-acting Antiviral Agents for Hepatitis C Virus. Medical Care 2019, 57: 279-285. PMID: 30807449, PMCID: PMC6436819, DOI: 10.1097/mlr.0000000000001071.Peer-Reviewed Original ResearchConceptsDirect-acting antiviral agentsHepatitis C virus infectionVeterans Affairs Healthcare SystemRural-Urban Commuting Area codesCurative HCV treatmentRural-urban designationC virus infectionElectronic health record dataHepatitis C virusPrior treatment experienceLower odds ratioHealth record dataZone improvement plan codeEligible patientsHCV treatmentAntiretroviral medicationsRural-urban residenceLiver diseaseUnadjusted analysesC virusRural-urban differencesOdds ratioMultivariable modelLower incidenceObservational study
2018
Patterns of Alcohol Use Among Patients Living With HIV in Urban, Large Rural, and Small Rural Areas
Bensley KM, McGinnis KA, Fortney J, Chan KCG, Dombrowski JC, Ornelas I, Edelman EJ, Goulet JL, Satre DD, Justice AC, Fiellin DA, Williams EC. Patterns of Alcohol Use Among Patients Living With HIV in Urban, Large Rural, and Small Rural Areas. The Journal Of Rural Health 2018, 35: 330-340. PMID: 30339740, PMCID: PMC6502702, DOI: 10.1111/jrh.12326.Peer-Reviewed Original ResearchConceptsSmall rural areasAlcohol useAUDIT-C alcoholElectronic health record dataHealth record dataAlcohol-related interventionsPrevalence of AUDAlcohol use outcomesHeavy episodic drinkingPLWHRural areasReporting useHIVUse outcomesRecord dataEpisodic drinkingPatientsPrevalenceRegression modelsDrinkingRuralityAUDUnique challengesProvider 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 treatmentAccuracy 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 individualsRacial/ethnic differences in the association between alcohol use and mortality among men living with HIV
Bensley KM, McGinnis KA, Fiellin DA, Gordon AJ, Kraemer KL, Bryant KJ, Edelman EJ, Crystal S, Gaither JR, Korthuis PT, Marshall BDL, Ornelas IJ, Chan KCG, Dombrowski JC, Fortney JC, Justice AC, Williams EC. Racial/ethnic differences in the association between alcohol use and mortality among men living with HIV. Addiction Science & Clinical Practice 2018, 13: 2. PMID: 29353555, PMCID: PMC6389249, DOI: 10.1186/s13722-017-0103-z.Peer-Reviewed Original ResearchConceptsLow-risk alcohol useMortality riskAlcohol useRace/ethnicityWhite PLWHMortality rateAlcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaireVeterans Aging Cohort StudyCox proportional hazards modelHigh-risk alcohol useAUDIT-C screeningAging Cohort StudyElectronic health record dataRisk of mortalityHigh-risk relativesUnhealthy alcohol useHigher mortality riskProportional hazards modelHealth record dataHigh mortality rateEthnic groupsMale PLWHCohort studyWhite patientsGeneral outpatients
2017
Validating Harmful Alcohol Use as a Phenotype for Genetic Discovery Using Phosphatidylethanol and a Polymorphism in ADH1B
Justice AC, McGinnis KA, Tate JP, Xu K, Becker WC, Zhao H, Gelernter J, Kranzler HR. Validating Harmful Alcohol Use as a Phenotype for Genetic Discovery Using Phosphatidylethanol and a Polymorphism in ADH1B. Alcohol Clinical And Experimental Research 2017, 41: 998-1003. PMID: 28295416, PMCID: PMC5501250, DOI: 10.1111/acer.13373.Peer-Reviewed Original ResearchConceptsHarmful alcohol useAlcohol exposureAlcohol useElectronic health record dataEHR dataAUDIT-C scoresHealth record dataLongitudinal electronic health record dataLongitudinal trajectoriesChi-square testEHR-derived phenotypesStudy cohortBlood drawCommon missense polymorphismGenetic risk variantsBlood samplingMissense polymorphismAlcohol riskQuantitative biomarkersRecord dataMedianRisk variantsOverall sampleAfrican AmericansADH1B gene