2024
Electronic Health Record Concordance with Survey-Reported Military Sexual Trauma Among Younger Veterans: Associations with Health Care Utilization and Mental Health Diagnoses
Gaffey A, Burg M, Skanderson M, Deviva J, Brandt C, Bastian L, Haskell S. Electronic Health Record Concordance with Survey-Reported Military Sexual Trauma Among Younger Veterans: Associations with Health Care Utilization and Mental Health Diagnoses. Journal Of Women's Health 2024 PMID: 38946553, DOI: 10.1089/jwh.2023.0993.Peer-Reviewed Original ResearchElectronic health recordsHealth care utilizationAssociated with health care utilizationMilitary sexual traumaVeterans Health AdministrationCare utilizationPosttraumatic stress disorderVeteran health care utilizationMental health visitsPrimary care utilizationMental health diagnosesCross-sectional associationsService-related characteristicsPost-9/11 veteransSexual traumaLikelihood of posttraumatic stress disorderEHR screensPrimary careVHA careHealth visitsOlder veteransHealth recordsYounger veteransDepression diagnosisExperience MSTLeveraging Electronic Health Records to Assess Residential Mobility Among Veterans in the Veterans Health Administration
Wang K, Hendrickson Z, Miller M, Abel E, Skanderson M, Erdos J, Womack J, Brandt C, Desai M, Han L. Leveraging Electronic Health Records to Assess Residential Mobility Among Veterans in the Veterans Health Administration. Medical Care 2024, 62: 458-463. PMID: 38848139, DOI: 10.1097/mlr.0000000000002017.Peer-Reviewed Original ResearchConceptsVeterans Health AdministrationElectronic health recordsResidential addressesHealth recordsHealth AdministrationLeveraging electronic health recordsInfluence health care utilizationVeterans Health Administration dataAssociations of sociodemographicsHealth care utilizationHealth care systemPatient's residential addressCross-sectional analysisGeneralized logistic regressionCare utilizationHealth systemResidential mobilitySubstance use disordersCare systemPatient's residenceLogistic regressionVeteransMultinomial outcomesHealthOddsBlood type as a risk factor for pancreatic ductal adenocarcinoma.
Rahimi Larki N, Skanderson M, Tate J, Levinson R, Hauser R, Brandt C, Yang Y, Justice A, Wang L. Blood type as a risk factor for pancreatic ductal adenocarcinoma. Journal Of Clinical Oncology 2024, 42: 10559-10559. DOI: 10.1200/jco.2024.42.16_suppl.10559.Peer-Reviewed Original ResearchPancreatic ductal adenocarcinoma riskVeterans Health AdministrationRisk of pancreatic ductal adenocarcinomaNon-O blood typeNeighborhood-level socioeconomic dataIntegrated healthcare systemHigh risk of pancreatic ductal adenocarcinomaPancreatic ductal adenocarcinomaAssociated with higher riskAssociated with increased riskUnited StatesHealth AdministrationOutpatient encountersHealthcare systemBaseline ageAlcohol useIndex dateAssociation of blood typeCancer deathWhite populationSocioeconomic dataBlack patientsDiverse populationsRisk factorsBlood typeEstimating risk for pancreatic cancer among 9.4 million veterans in care.
Wang L, Rahimi Larki N, Skanderson M, Tate J, Hauser R, Brandt C, Yang Y, Justice A. Estimating risk for pancreatic cancer among 9.4 million veterans in care. Journal Of Clinical Oncology 2024, 42: 10544-10544. DOI: 10.1200/jco.2024.42.16_suppl.10544.Peer-Reviewed Original ResearchVeterans Health AdministrationGeneral populationAlcohol useIntegrated health systemElectronic health recordsTen-year riskHistory of cancerLoss to follow-upFollow-upEvaluated model discriminationMedian baseline ageCox proportional hazards modelsRisk prediction modelHealth recordsProportional hazards modelHealth systemHealth AdministrationMultivariate Cox proportional hazards modelSmoking statusCharlson Comorbidity IndexBaseline ageClinical reasoningRange of risksHazards modelFinal predictorsA roadmap to artificial intelligence (AI): Methods for designing and building AI ready data to promote fairness
Kidwai-Khan F, Wang R, Skanderson M, Brandt C, Fodeh S, Womack J. A roadmap to artificial intelligence (AI): Methods for designing and building AI ready data to promote fairness. Journal Of Biomedical Informatics 2024, 154: 104654. PMID: 38740316, PMCID: PMC11144439, DOI: 10.1016/j.jbi.2024.104654.Peer-Reviewed Original ResearchArtificial intelligenceMachine learningNatural language processing techniquesRaw dataLife cycle of dataLanguage processing techniquesInput dataApplication of artificial intelligenceArtificial intelligence processesMachine learning algorithmsTransform raw dataNatural language processing algorithmsArtificial intelligence methodsApplication of AILanguage processing algorithmsLearning algorithmsIntelligent processingError rateIntelligence methodsData governanceProcessing algorithmsData expertiseAlgorithmic biasElectronic health record dataData frameworksSexual and Gender Minority Status and Suicide Mortality: An Explainable Artificial Intelligence Analysis
Yin Y, Workman T, Blosnich J, Brandt C, Skanderson M, Shao Y, Goulet J, Zeng-Treitler Q. Sexual and Gender Minority Status and Suicide Mortality: An Explainable Artificial Intelligence Analysis. International Journal Of Public Health 2024, 69: 1606855. PMID: 38770181, PMCID: PMC11103011, DOI: 10.3389/ijph.2024.1606855.Peer-Reviewed Original ResearchLGBT statusSuicide death riskLGBT patientsLGBTCrude suicide mortality rateSuicide mortality ratesDeath riskProtective factorsAssociated with reduced riskTransgenderCase-control studyVeteransOlder veteransUS veteransHealthcare systemSuicideSuicide riskStatusReligionRisk factorsDeath risk factorsHigh riskLow riskMortality ratePatterns of gabapentin prescription and of hospitalization in a national cohort of US Veterans
Levy D, Gordon K, Bastian L, Brandt C, Gunderson C. Patterns of gabapentin prescription and of hospitalization in a national cohort of US Veterans. Pain Medicine 2024, 25: 534-537. PMID: 38676664, DOI: 10.1093/pm/pnae027.Peer-Reviewed Original ResearchIdentifying incarceration status in the electronic health record using large language models in emergency department settings
Huang T, Socrates V, Gilson A, Safranek C, Chi L, Wang E, Puglisi L, Brandt C, Taylor R, Wang K. Identifying incarceration status in the electronic health record using large language models in emergency department settings. Journal Of Clinical And Translational Science 2024, 8: e53. PMID: 38544748, PMCID: PMC10966832, DOI: 10.1017/cts.2024.496.Peer-Reviewed Original ResearchElectronic health recordsNatural language processingHealth recordsIncarceration statusSignificant social determinant of healthSocial determinants of healthClinic electronic health recordsEHR databasePopulation health initiativesDeterminants of healthMitigate health disparitiesRacial health inequitiesEmergency department settingICD-10 codesHealth inequalitiesNatural language processing modelsHealth disparitiesHealth initiativesDepartment settingEmergency departmentSystem interventionsICD-10Clinical notesStudy populationLanguage modelDevelopment and Validation of Case-Finding Algorithms to Identify Pancreatic Cancer in the Veterans Health Administration
Mezzacappa C, Larki N, Skanderson M, Park L, Brandt C, Hauser R, Justice A, Yang Y, Wang L. Development and Validation of Case-Finding Algorithms to Identify Pancreatic Cancer in the Veterans Health Administration. Digestive Diseases And Sciences 2024, 69: 1507-1513. PMID: 38453743, DOI: 10.1007/s10620-024-08324-w.Peer-Reviewed Original ResearchElectronic health recordsVeterans Health AdministrationHealth AdministrationElectronic health records data elementsElectronic health record dataDiagnosis of exocrine pancreatic cancerNational Cancer RegistryCancer RegistryHealth recordsExocrine pancreatic cancerOncology settingOutpatient encountersInpatient encountersData elementsExpert adjudicationPancreatic ductal adenocarcinomaEpidemiological studiesRandom sampleInterquartile rangeIdentification of patientsRange of patientsPancreatic cancerVeteransLate diagnosisExcellent PPVCreation and Validation of an Automated Registry for Outpatient Parenteral Antibiotics
Canterino J, Malinis M, Liu J, Kashyap N, Brandt C, Justice A. Creation and Validation of an Automated Registry for Outpatient Parenteral Antibiotics. Open Forum Infectious Diseases 2024, 11: ofae004. PMID: 38412514, PMCID: PMC10866572, DOI: 10.1093/ofid/ofae004.Peer-Reviewed Original ResearchElectronic medical recordsOutpatient parenteral antibiotic therapyOutpatient parenteral antibiotic therapy programsMedical recordsObjective dataHospital length of stayOPAT episodesLength of stayDischarge dispositionUnique patientsRegistryParenteral antibiotic therapyInsurance payorOutpatient parenteral antibioticsDeath rateHospital lengthHospital daysAntibiotic therapyParenteral antibioticsInfection syndromeHospitalProgramAntibiotic name
2023
Dementia risk analysis using temporal event modeling on a large real-world dataset
Taylor R, Gilson A, Chi L, Haimovich A, Crawford A, Brandt C, Magidson P, Lai J, Levin S, Mecca A, Hwang U. Dementia risk analysis using temporal event modeling on a large real-world dataset. Scientific Reports 2023, 13: 22618. PMID: 38114545, PMCID: PMC10730574, DOI: 10.1038/s41598-023-49330-8.Peer-Reviewed Original ResearchAmbiguity in care delivery terminology: implications that affect pragmatic clinical trials using non-pharmacological interventions
Rhon D, Davis A, Ali J, Brandt C, Burns A, Lucio W, Vining R, Young-McCaughan S. Ambiguity in care delivery terminology: implications that affect pragmatic clinical trials using non-pharmacological interventions. BMJ Evidence-Based Medicine 2023, bmjebm-2023-112547. PMID: 37989537, DOI: 10.1136/bmjebm-2023-112547.Peer-Reviewed Original ResearchOpioid prescription and risk of atrial fibrillation in younger veterans
Chui P, Khokhar A, Gordon K, Dziura J, Burg M, Brandt C, Haskell S, Malm B, Bastian L, Gandhi P. Opioid prescription and risk of atrial fibrillation in younger veterans. American Heart Journal 2023, 268: 61-67. PMID: 37949420, DOI: 10.1016/j.ahj.2023.11.001.Peer-Reviewed Original ResearchTime-updated Cox regressionIncident atrial fibrillationAtrial fibrillationOpioid exposureVeterans Health AdministrationOpioid typeCox regressionOpioid prescriptionsICD-9-CM diagnostic codesIncidence of AFDevelopment of AFPrescription opioid exposureModifiable risk factorsPrimary care visitsPrescribed opioidsCare visitsOpioid useRisk factorsDiagnostic codesTime-dependent variablesOpioidsHealth AdministrationYounger veteransBaseline periodStudy samplePatterns of emergency department visits prior to dementia or cognitive impairment diagnosis: An opportunity for dementia detection?
Seidenfeld J, Runels T, Goulet J, Augustine M, Brandt C, Hastings S, Hung W, Ragsdale L, Sullivan J, Zhu C, Hwang U. Patterns of emergency department visits prior to dementia or cognitive impairment diagnosis: An opportunity for dementia detection? Academic Emergency Medicine 2023 PMID: 37935451, PMCID: PMC11074234, DOI: 10.1111/acem.14832.Peer-Reviewed Original ResearchRelationship Between Pain and LGBT Status Among Veterans in Care in a Retrospective Cross-Sectional Cohort
Gordon K, Buta E, Pratt-Chapman M, Brandt C, Gueorguieva R, Warren A, Workman T, Zeng-Treitler Q, Goulet J. Relationship Between Pain and LGBT Status Among Veterans in Care in a Retrospective Cross-Sectional Cohort. Journal Of Pain Research 2023, 16: 4037-4047. PMID: 38054108, PMCID: PMC10695019, DOI: 10.2147/jpr.s432967.Peer-Reviewed Original ResearchRetrospective cross-sectional cohortCross-sectional cohortPersistent painSelf-reported pain scoresVeterans Health AdministrationRobust Poisson modelsCorporate Data WarehouseLGBT veteransPain screeningPain scoresClinic visitsPain assessmentPainAdjusted modelHealth AdministrationGreater painMental healthSubstance useCohortYear of entryBlack veteransHealthcare systemVeteransSignificant differencesAdministrative dataUnderstanding Veterans' intimate partner violence use and patterns of healthcare utilization
Relyea M, Presseau C, Runels T, Humbert M, Martino S, Brandt C, Haskell S, Portnoy G. Understanding Veterans' intimate partner violence use and patterns of healthcare utilization. Health Services Research 2023, 58: 1198-1208. PMID: 37452496, PMCID: PMC10622301, DOI: 10.1111/1475-6773.14201.Peer-Reviewed Original ResearchConceptsVeterans Health AdministrationHealthcare utilizationIPV useChronic painMedical treatmentSevere chronic painNon-VA providersChronic sleep problemsNon-VA servicesPost-traumatic stress disorderChi-square testRisk factorsOperation New Dawn veteransProvider trainingSleep problemsVA healthcareNew Dawn veteransOperation Enduring FreedomDATA SOURCESWomen veteransOutpatient healthcareHealth AdministrationOperation Iraqi FreedomClinical settingStudy settingDetection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices
Khunte A, Sangha V, Oikonomou E, Dhingra L, Aminorroaya A, Mortazavi B, Coppi A, Brandt C, Krumholz H, Khera R. Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices. Npj Digital Medicine 2023, 6: 124. PMID: 37433874, PMCID: PMC10336107, DOI: 10.1038/s41746-023-00869-w.Peer-Reviewed Original ResearchArtificial intelligenceRandom Gaussian noiseNoisy electrocardiogramGaussian noiseElectrocardiogram (ECGWearable devicesSingle-lead electrocardiogramPortable devicesSNRWearableNoiseDevice noiseRepositoryAI-based screeningIntelligenceDetectionDevicesNoise sourcesVentricular systolic dysfunctionModelElectrocardiogramSingle-lead electrocardiographyTrainingPatient Dietary Supplements Use: Do Results from Natural Language Processing of Clinical Notes Agree with Survey Data?
Redd D, Workman T, Shao Y, Cheng Y, Tekle S, Garvin J, Brandt C, Zeng-Treitler Q. Patient Dietary Supplements Use: Do Results from Natural Language Processing of Clinical Notes Agree with Survey Data? Medical Sciences 2023, 11: 37. PMID: 37367736, PMCID: PMC10304046, DOI: 10.3390/medsci11020037.Peer-Reviewed Original ResearchConceptsSelf-reported supplement useSupplement useClinical notesStructured medical recordsUnstructured clinical notesPrescription medicationsClinical recordsMedical recordsPhysician guidanceDietary supplementsNatural language processing toolsPatientsNatural language processingFolic acidHealthcare facilitiesLanguage processing toolsSupplementsF1 scoreLanguage processingPotential interactionsNLP performanceProcessing toolsNLP extractionExtra informationMedicationsPersonal Health Libraries for People Returning From Incarceration: Protocol for a Qualitative Study
Foumakoye M, Britton M, Ansari E, Saunders M, McCall T, Wang E, Puglisi L, Workman T, Zeng-Treitler Q, Ying Y, Shavit S, Brandt C, Wang K. Personal Health Libraries for People Returning From Incarceration: Protocol for a Qualitative Study. JMIR Research Protocols 2023, 12: e44748. PMID: 37133907, PMCID: PMC10193212, DOI: 10.2196/44748.Peer-Reviewed Original ResearchHealth information technologyPersonal Health LibraryInformation technologyMobile appsINTERNATIONAL REGISTERED REPORT IDENTIFIERTechnology resourcesMultiple providersCarceral facilitiesCommunity settingsComplex systemsHealth LibraryHealth care clinicsThematic outputsHealth informationAppsTechnologyCare clinicsJustice-involved individualsNetwork clinicsNetworkingMental healthInformationSocioeconomic statusCommunity livingProvidersExtracting Pain Care Quality Indicators from U.S. Veterans Health Administration Chiropractic Care Using Natural Language Processing
Coleman B, Finch D, Wang R, Luther S, Heapy A, Brandt C, Lisi A. Extracting Pain Care Quality Indicators from U.S. Veterans Health Administration Chiropractic Care Using Natural Language Processing. Applied Clinical Informatics 2023, 14: 600-608. PMID: 37164327, PMCID: PMC10411229, DOI: 10.1055/a-2091-1162.Peer-Reviewed Original ResearchConceptsCare quality indicatorsVeterans Health AdministrationVisit typePain assessmentChiropractic careConsultation visitCare qualityClinic visit typePain care qualityComprehensive pain assessmentWomen Veterans Cohort StudyCare visitsCohort studyMusculoskeletal painManagement visitsVisit notesHealth AdministrationConsultation notesChiropractic servicesVisitsQuality indicatorsMean numberTreatment planningPatientsDescriptive statistics