About
Titles
Staff Affiliate - VAMC
Appointments
Departments & Organizations
Research
Research at a Glance
Yale Co-Authors
Frequent collaborators of Melissa Skanderson's published research.
Cynthia Brandt, MD, MPH
Ronald George Hauser III, MD
Jason Jonathon Sico, MD, MHS, FAHA, FAAN (Neurology), FANA, FACP
Julie Womack, PhD, CNM, FNP (BC)
Kaicheng Wang, MD, MPH
Allison E. Gaffey, PhD
Publications
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 ResearchAltmetricConceptsElectronic 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 MSTIdentification of hepatic steatosis among persons with and without HIV using natural language processing
Torgersen J, Skanderson M, Kidwai-Khan F, Carbonari D, Tate J, Park L, Bhattacharya D, Lim J, Taddei T, Justice A, Re V. Identification of hepatic steatosis among persons with and without HIV using natural language processing. Hepatology Communications 2024, 8: e0468. PMID: 38896066, PMCID: PMC11186806, DOI: 10.1097/hc9.0000000000000468.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsImaging ReportingSteatotic liver diseaseHIV statusHepatic steatosisPrevalence of metabolic comorbiditiesImaging studiesVeterans Aging Cohort StudyCompare patient characteristicsPositive predictive valueAlcohol use disorderAging Cohort StudyIdentification of hepatic steatosisHIV infectionHepatitis BMetabolic comorbiditiesNatural language processing algorithmsRadiological studiesCohort studyPatient characteristicsClinical reviewLiver diseaseHIVPredictive valueUse disorderClinical image reportsLeveraging 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 ResearchAltmetricMeSH Keywords and ConceptsConceptsVeterans 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 outcomesHealthOddsContribution of Potentially Inappropriate Medications to Polypharmacy-Associated Risk of Mortality in Middle-Aged Patients: A National Cohort Study
Guillot J, Justice A, Gordon K, Skanderson M, Pariente A, Bezin J, Rentsch C. Contribution of Potentially Inappropriate Medications to Polypharmacy-Associated Risk of Mortality in Middle-Aged Patients: A National Cohort Study. Journal Of General Internal Medicine 2024, 1-10. PMID: 38831248, DOI: 10.1007/s11606-024-08817-4.Peer-Reviewed Original ResearchAltmetricConceptsMiddle-aged patientsRisk of mortalityVeterans AffairsChronic medicationsVA patient populationIntegrated healthcare systemNational cohort studyAssociated with increased mortalityMiddle-aged individualsMechanism of injuryMiddle-aged peopleAssociated with mortalityInappropriate medicationsBeers criteriaHealthcare systemAttenuate riskCohort studyClinical characteristicsGeneral populationHyperpolypharmacyFollow-upPolypharmacyPatient populationBackgroundThe roleCox modelBlood 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 ResearchConceptsPancreatic 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 ResearchConceptsVeterans 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 ResearchAltmetricConceptsArtificial 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 ResearchAltmetricConceptsLGBT 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 rateDevelopment 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 ResearchConceptsElectronic 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 PPV
2021
Services for Headache Disorder(s) among Men and Women Veterans across the Veterans Health Administration – a 10-year Cohort Study (4669)
Seng E, Fenton B, Wang K, Skanderson M, Sico J. Services for Headache Disorder(s) among Men and Women Veterans across the Veterans Health Administration – a 10-year Cohort Study (4669). Neurology 2021, 96 DOI: 10.1212/wnl.96.15_supplement.4669.Peer-Reviewed Original Research