2022
Predictive Risk Model for Serious Falls Among Older Persons Living With HIV
Womack JA, Murphy TE, Leo-Summers L, Bates J, Jarad S, Smith AC, Gill TM, Hsieh E, Rodriguez-Barradas MC, Tien PC, Yin MT, Brandt CA, Justice AC. Predictive Risk Model for Serious Falls Among Older Persons Living With HIV. JAIDS Journal Of Acquired Immune Deficiency Syndromes 2022, 91: 168-174. PMID: 36094483, PMCID: PMC9470988, DOI: 10.1097/qai.0000000000003030.Peer-Reviewed Original ResearchConceptsMiddle-aged veteransOlder PWHAntiretroviral therapySerious fallsOlder personsVeterans Aging Cohort StudyMeasures of multimorbidityAging Cohort StudyBody mass indexMultivariable logistic regressionPredictive risk modelCohort studyMass indexInjury codesElevated riskGeneral populationSix monthsPWHLogistic regressionPotential predictorsSubstance useRadiology reportsHIVExternal causesVeteransMental Health Diagnoses are Not Associated With Indicators of Lower Quality Pain Care in Electronic Health Records of a National Sample of Veterans Treated in Veterans Health Administration Primary Care Settings
Dobscha SK, Luther SL, Kerns RD, Finch DK, Goulet JL, Brandt CA, Skanderson M, Bathulapalli H, Fodeh SJ, Hahm B, Bouayad L, Lee A, Han L. Mental Health Diagnoses are Not Associated With Indicators of Lower Quality Pain Care in Electronic Health Records of a National Sample of Veterans Treated in Veterans Health Administration Primary Care Settings. Journal Of Pain 2022, 24: 273-281. PMID: 36167230, PMCID: PMC9898089, DOI: 10.1016/j.jpain.2022.08.009.Peer-Reviewed Original ResearchConceptsPain care qualityQuality pain careMental health conditionsPrimary care cliniciansVeterans Health AdministrationPain carePCQ scoresHealth conditionsCare cliniciansUse disordersCare qualitySevere musculoskeletal painRetrospective cohort studyPrimary care visitsGeneral medical carePrimary care settingElectronic health record dataFinal adjusted modelMental health diagnosesEquation Poisson modelsHealth record dataBipolar disorder diagnosisSubstance use disordersAlcohol use disorderPost-traumatic stress disorder
2021
Brief Report: Are Serious Falls Associated With Subsequent Fragility Fractures Among Veterans Living With HIV?
Womack JA, Murphy TE, Ramsey C, Bathulapalli H, Leo-Summers L, Smith AC, Bates J, Jarad S, Gill TM, Hsieh E, Rodriguez-Barradas MC, Tien PC, Yin MT, Brandt C, Justice AC. Brief Report: Are Serious Falls Associated With Subsequent Fragility Fractures Among Veterans Living With HIV? JAIDS Journal Of Acquired Immune Deficiency Syndromes 2021, 88: 192-196. PMID: 34506360, PMCID: PMC8513792, DOI: 10.1097/qai.0000000000002752.Peer-Reviewed Original ResearchConceptsSubsequent fragility fracturesFragility fracturesAntiretroviral therapySerious fallsRisk factorsVeterans Aging Cohort StudyAging Cohort StudyMultivariable logistic regressionUpper arm fracturesMiddle-aged populationYears of ageAlcohol use disorderCohort studyHip fractureVertebral fracturesArm fracturesInjury codesICD9 codesGeneral populationUse disordersLogistic regressionIntegrase inhibitorsOlder adultsRadiology reportsHIVMeasuring pain care quality in the Veterans Health Administration primary care setting
Luther SL, Finch DK, Bouayad L, McCart J, Han L, Dobscha SK, Skanderson M, Fodeh SJ, Hahm B, Lee A, Goulet JL, Brandt CA, Kerns RD. Measuring pain care quality in the Veterans Health Administration primary care setting. Pain 2021, 163: e715-e724. PMID: 34724683, PMCID: PMC8920945, DOI: 10.1097/j.pain.0000000000002477.Peer-Reviewed Original ResearchConceptsPain care qualityPattern of documentationSevere pain intensityFrequency of documentationPresence of painSite of painPrimary care providersPrimary care settingCare quality indicatorsQuality improvement initiativesTotal PCQ scoresPatient characteristicsPain intensityPain carePain impactPCQ scoresCare settingsCare providersMusculoskeletal disordersFurther evaluationPainCare qualityHealthcare facilitiesImprovement initiativesUnique visitsTwitter-based analysis reveals differential COVID-19 concerns across areas with socioeconomic disparities
Su Y, Venkat A, Yadav Y, Puglisi LB, Fodeh SJ. Twitter-based analysis reveals differential COVID-19 concerns across areas with socioeconomic disparities. Computers In Biology And Medicine 2021, 132: 104336. PMID: 33761419, PMCID: PMC9159205, DOI: 10.1016/j.compbiomed.2021.104336.Peer-Reviewed Original ResearchConceptsArea Deprivation Index
2020
Utilizing a multi-class classification approach to detect therapeutic and recreational misuse of opioids on Twitter
Fodeh SJ, Al-Garadi M, Elsankary O, Perrone J, Becker W, Sarker A. Utilizing a multi-class classification approach to detect therapeutic and recreational misuse of opioids on Twitter. Computers In Biology And Medicine 2020, 129: 104132. PMID: 33290931, PMCID: PMC7855783, DOI: 10.1016/j.compbiomed.2020.104132.Peer-Reviewed Original ResearchIdentification of Patients with Nontraumatic Intracranial Hemorrhage Using Administrative Claims Data
Sangal RB, Fodeh S, Taylor A, Rothenberg C, Finn EB, Sheth K, Matouk C, Ulrich A, Parwani V, Sather J, Venkatesh A. Identification of Patients with Nontraumatic Intracranial Hemorrhage Using Administrative Claims Data. Journal Of Stroke And Cerebrovascular Diseases 2020, 29: 105306. PMID: 33070110, PMCID: PMC7686163, DOI: 10.1016/j.jstrokecerebrovasdis.2020.105306.Peer-Reviewed Original ResearchDefining facets of social distancing during the COVID-19 pandemic: Twitter analysis
Kwon J, Grady C, Feliciano JT, Fodeh SJ. Defining facets of social distancing during the COVID-19 pandemic: Twitter analysis. Journal Of Biomedical Informatics 2020, 111: 103601. PMID: 33065264, PMCID: PMC7553881, DOI: 10.1016/j.jbi.2020.103601.Peer-Reviewed Original ResearchSerious Falls in Middle‐Aged Veterans: Development and Validation of a Predictive Risk Model
Womack JA, Murphy TE, Bathulapalli H, Smith A, Bates J, Jarad S, Redeker NS, Luther SL, Gill TM, Brandt CA, Justice AC. Serious Falls in Middle‐Aged Veterans: Development and Validation of a Predictive Risk Model. Journal Of The American Geriatrics Society 2020, 68: 2847-2854. PMID: 32860222, PMCID: PMC7744431, DOI: 10.1111/jgs.16773.Peer-Reviewed Original ResearchConceptsMiddle-aged veteransVeterans Health AdministrationOpioid useSerious fallsAlcohol Use Disorders Identification Test-Consumption scoresCategory-free net reclassification improvementIllicit substance use disordersMental health comorbiditiesPrescription opioid useMultivariable logistic regressionNet reclassification improvementSubstance use disordersQuality of lifeHazardous alcohol usePredictive risk modelChronic medicationsCohort studyHealth comorbiditiesNinth RevisionReclassification improvementGeriatric healthInjury codesHazardous alcoholInternational ClassificationUse disordersExploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization
Coleman BC, Fodeh S, Lisi AJ, Goulet JL, Corcoran KL, Bathulapalli H, Brandt CA. Exploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization. Chiropractic & Manual Therapies 2020, 28: 47. PMID: 32680545, PMCID: PMC7368704, DOI: 10.1186/s12998-020-00335-4.Peer-Reviewed Original ResearchConceptsSpinal pain conditionsService utilizationPain conditionsChiropractic careConservative interventionsChiropractic servicesVA chiropractic servicesRetrospective cohort studyHealthcare service utilizationHealthcare cost burdenLimited clinical utilityLower healthcare costsCohort entryCohort studyDiagnosis cohortPain statusPrimary outcomeChiropractic visitsClinical featuresUS adultsClinical utilityHealthcare costsDifferent clinical populationsVisitsClinical populations
2019
Polypharmacy, Hazardous Alcohol and Illicit Substance Use, and Serious Falls Among PLWH and Uninfected Comparators.
Womack JA, Murphy TE, Rentsch CT, Tate JP, Bathulapalli H, Smith AC, Bates J, Jarad S, Gibert CL, Rodriguez-Barradas MC, Tien PC, Yin MT, Gill TM, Friedlaender G, Brandt CA, Justice AC. Polypharmacy, Hazardous Alcohol and Illicit Substance Use, and Serious Falls Among PLWH and Uninfected Comparators. JAIDS Journal Of Acquired Immune Deficiency Syndromes 2019, 82: 305-313. PMID: 31339866, PMCID: PMC7176040, DOI: 10.1097/qai.0000000000002130.Peer-Reviewed Original ResearchConceptsIllicit substance useHazardous alcoholSerious fallsUninfected comparatorsMedication classesOpioid prescriptionsSubstance useHIV statusMuscle relaxantsRisk factorsVeterans Aging Cohort StudyAging Cohort StudyIllicit substance abuseUnconditional logistic regressionNon-ART medicationsHazardous alcohol useSubstance use/abuseCase-control designKey risk factorsUse/abuseCohort studyMedication countInjury codesDuration of observationBaseline date
2017
Classifying clinical notes with pain assessment using machine learning
Fodeh SJ, Finch D, Bouayad L, Luther SL, Ling H, Kerns RD, Brandt C. Classifying clinical notes with pain assessment using machine learning. Medical & Biological Engineering & Computing 2017, 56: 1285-1292. PMID: 29280092, PMCID: PMC6014866, DOI: 10.1007/s11517-017-1772-1.Peer-Reviewed Original ResearchConceptsPain care qualityPain assessmentClinical notesChronic painMusculoskeletal diagnosesSignificant public health problemCharacteristics of patientsIntensity of painType of painPublic health problemPain sitesPain complaintsPatient reportsPainPatientsHealth problemsCare qualityFiscal year 2011Health recordsMillions of peopleComplete dataClinical applicationDiagnosisDemographic variablesWide spectrumClassifying Clinical Notes with Pain Assessment.
Fodeh SJ, Finch D, Bouayad L, Luther S, Kerns RD, Brandt C. Classifying Clinical Notes with Pain Assessment. 2017, 245: 1261. PMID: 29295346.Peer-Reviewed Original Research
2016
Estimating healthcare mobility in the Veterans Affairs Healthcare System
Wang KH, Goulet JL, Carroll CM, Skanderson M, Fodeh S, Erdos J, Womack JA, Abel EA, Bathulapalli H, Justice AC, Nunez-Smith M, Brandt CA. Estimating healthcare mobility in the Veterans Affairs Healthcare System. BMC Health Services Research 2016, 16: 609. PMID: 27769221, PMCID: PMC5075153, DOI: 10.1186/s12913-016-1841-4.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overDelivery of Health CareElectronic Health RecordsEmigration and ImmigrationFemaleHospitals, VeteransHumansMaleMental DisordersMiddle AgedPatient Acceptance of Health CareRetrospective StudiesUnited StatesUnited States Department of Veterans AffairsVeteransVeterans HealthYoung AdultConceptsHealthcare systemVeterans Health Administration electronic health recordsVeterans Affairs Healthcare SystemHealthcare mobilityRetrospective cohort studyHepatitis C virusOutcomes of careDifferent healthcare systemsDistinct healthcare systemsElectronic health recordsClinical characteristicsCohort studyHealthcare utilizationC virusSpecialty carePsychiatric disordersYounger veteransDisease preventionYounger agePopulation healthHealth recordsVeteransStatus changesCareYear periodElectronic approaches to making sense of the text in the adverse event reporting system
Benin AL, Fodeh SJ, Lee K, Koss M, Miller P, Brandt C. Electronic approaches to making sense of the text in the adverse event reporting system. Journal Of Healthcare Risk Management 2016, 36: 10-20. PMID: 27547874, DOI: 10.1002/jhrm.21237.Peer-Reviewed Original ResearchConceptsRule-based queryMachine learningUse casesSemi-supervised machine learningWeb-based software toolSoftware systemsSoftware toolsHigh recallQueriesRich informationElectronic approachRobust programEvent reportsDaily workLearningImportant dataHigh precisionReporting systemInformationTextMachineSystemEvent Reporting SystemAdverse Event Reporting SystemError
2015
Classification of radiology reports for falls in an HIV study cohort
Bates J, Fodeh SJ, Brandt CA, Womack JA. Classification of radiology reports for falls in an HIV study cohort. Journal Of The American Medical Informatics Association 2015, 23: e113-e117. PMID: 26567329, PMCID: PMC4954638, DOI: 10.1093/jamia/ocv155.Peer-Reviewed Original ResearchConceptsFeature selectionMutual informationSVM classifierUnified Medical Language System (UMLS) conceptsSupport vector machine classifierRadiology reportsFeature selection approachStructured electronic health record dataFeature selection methodVector machine classifierMachine learningNumber of featuresSupervised machineDiscriminative featuresFeature setsMachine classifierVACS-VCClassifier performanceStudy cohortClassifierSelection approachElectronic health record dataCurve scoreVeterans Aging Cohort Study Virtual CohortSelection methodBaseline Cluster Membership Demonstrates Positive Associations with First Occurrence of Multiple Gerontologic Outcomes Over 10 Years
Fodeh SJ, Trentalange M, Allore HG, Gill TM, Brandt CA, Murphy TE. Baseline Cluster Membership Demonstrates Positive Associations with First Occurrence of Multiple Gerontologic Outcomes Over 10 Years. Experimental Aging Research 2015, 41: 177-192. PMID: 25724015, PMCID: PMC4347941, DOI: 10.1080/0361073x.2015.1001655.Peer-Reviewed Original ResearchConceptsBaseline valuesCommunity-living personsProportional hazards regressionPositive associationLevel of impairmentHazards regressionChronic conditionsBaseline predictorsFollowing outcomesSlow gaitDaily livingDepressive symptomsCognitive statusOutcomesFirst occurrenceDichotomous indicatorsMobility measuresAssociationDeathCandidate variablesDisabilityBaseline cluster
2013
Validating a natural language processing tool to exclude psychogenic nonepileptic seizures in electronic medical record-based epilepsy research
Hamid H, Fodeh SJ, Lizama AG, Czlapinski R, Pugh MJ, LaFrance WC, Brandt CA. Validating a natural language processing tool to exclude psychogenic nonepileptic seizures in electronic medical record-based epilepsy research. Epilepsy & Behavior 2013, 29: 578-580. PMID: 24135384, DOI: 10.1016/j.yebeh.2013.09.025.Peer-Reviewed Original ResearchConceptsPsychogenic nonepileptic seizuresPositive predictive valueNonepileptic seizuresDefinite PNESAfghanistan veteransEpilepsy researchNational Clinical DatabaseVideo electroencephalograph monitoringDiagnosis of epilepsySeizure disorderDefinitive diagnosisElectronic health record systemsEpidemiologic dataHealth record systemsPredictive valueClinical databaseElectroencephalograph monitoringPatientsEpilepsyVEEGEpidemiologic researchVeteransRecord systemSeizuresDiagnosisFunctional Impairments as Symptoms in the Symptom Cluster Analysis of Patients Newly Diagnosed With Advanced Cancer
Fodeh SJ, Lazenby M, Bai M, Ercolano E, Murphy T, McCorkle R. Functional Impairments as Symptoms in the Symptom Cluster Analysis of Patients Newly Diagnosed With Advanced Cancer. Journal Of Pain And Symptom Management 2013, 46: 500-510. PMID: 23380336, PMCID: PMC4321795, DOI: 10.1016/j.jpainsymman.2012.09.011.Peer-Reviewed Original ResearchConceptsFunctional impairmentAdvanced cancerSymptom cluster analysisDays of diagnosisTime of diagnosisEarly cancer stagesHealth care providersLate-stage cancerSelf-reported symptomsSubsequent functional impairmentSelf-reported physical symptomsAdvanced gastrointestinalLung cancerCancer sitesCancer stageEarly recognitionCare providersDaily livingPhysical symptomsPatientsSymptomsInsomniaFunctional changesCancerImpairment