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
2018
Provider 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 treatment
2013
Validation of an algorithm to identify antiretroviral‐naïve status at time of entry into a large, observational cohort of HIV‐infected patients
Gandhi NR, Tate JP, Rodriguez‐Barradas M, Rimland D, Goetz MB, Gibert C, Brown ST, Mattocks K, Justice AC. Validation of an algorithm to identify antiretroviral‐naïve status at time of entry into a large, observational cohort of HIV‐infected patients. Pharmacoepidemiology And Drug Safety 2013, 22: 1019-1025. PMID: 23836591, PMCID: PMC3831617, DOI: 10.1002/pds.3476.Peer-Reviewed Original ResearchConceptsART-naïve patientsViral load thresholdMedical record reviewAntiretroviral treatmentMedical recordsHIV cohortObservational cohortRecord reviewVeterans Aging Cohort Study Virtual CohortVirtual cohortPrevious antiretroviral treatmentLaboratory dataPatients' medical recordsPositive predictive value 87Cohort entryAdverse eventsHIV outcomesRandomized trialsRetrospective studyAdverse reactionsTime of entryCopies/ART treatmentTreatment statusTreatment history