2023
Opioid use and opioid use disorder in mono and dual-system users of veteran affairs medical centers
Goulet J, Cheng Y, Becker W, Brandt C, Sandbrink F, Workman T, Ma P, Libin A, Shara N, Spevak C, Kupersmith J, Zeng-Treitler Q. Opioid use and opioid use disorder in mono and dual-system users of veteran affairs medical centers. Frontiers In Public Health 2023, 11: 1148189. PMID: 37124766, PMCID: PMC10141670, DOI: 10.3389/fpubh.2023.1148189.Peer-Reviewed Original ResearchConceptsOpioid use disorderNew opioid prescriptionsOpioid prescriptionsOUD diagnosisVA careUse disordersPrevalence of OUDVeterans Affairs Medical CenterGuideline-concordant careRetrospective cohort studyMultivariate logistic regressionNon-VA sourcesVeterans Administration dataCommunity care servicesPrescription sourceUS healthcare systemOpioid medicationsOpioid useCohort studyConcordant careActive patientsVA cliniciansIntra-class correlationMedical CenterWhite raceAssessing the contributions of modifiable risk factors to serious falls and fragility fractures among older persons living with HIV
Womack J, Murphy T, Leo‐Summers L, Bates J, Jarad S, Gill T, Hsieh E, Rodriguez‐Barradas M, Tien P, Yin M, Brandt C, Justice A. Assessing the contributions of modifiable risk factors to serious falls and fragility fractures among older persons living with HIV. Journal Of The American Geriatrics Society 2023, 71: 1891-1901. PMID: 36912153, PMCID: PMC10258163, DOI: 10.1111/jgs.18304.Peer-Reviewed Original ResearchConceptsModifiable risk factorsFragility fracturesRisk factorsAlcohol use disorderSerious fallsPhysiologic frailtyAntiretroviral therapyOlder PWHUse disordersVeterans Aging Cohort StudyMeasures of multimorbidityAging Cohort StudyBody mass indexMultivariable logistic modelAverage attributable fractionSuccessful prevention programsKey risk factorsOpioid prescriptionsCohort studyMass indexModifiable factorsSixth decadeAttributable fractionElevated riskICD9 codes
2019
Identifying Opioid Use Disorder in the Emergency Department: Multi-System Electronic Health Record–Based Computable Phenotype Derivation and Validation Study
Chartash D, Paek H, Dziura JD, Ross BK, Nogee DP, Boccio E, Hines C, Schott AM, Jeffery MM, Patel MD, Platts-Mills TF, Ahmed O, Brandt C, Couturier K, Melnick E. Identifying Opioid Use Disorder in the Emergency Department: Multi-System Electronic Health Record–Based Computable Phenotype Derivation and Validation Study. JMIR Medical Informatics 2019, 7: e15794. PMID: 31674913, PMCID: PMC6913746, DOI: 10.2196/15794.Peer-Reviewed Original ResearchOpioid use disorderNegative predictive valuePositive predictive valueEmergency department patientsEmergency departmentUse disordersHealth care systemPredictive valueComputable phenotypeExternal validation phasesDepartment patientsCare systemPhysician chart reviewLarge health care systemExternal validation cohortEmergency medicine physiciansHigh predictive valueElectronic health recordsChart reviewChief complaintValidation cohortPragmatic trialClinical dataBilling codesMedicine physicians