2020
A Prototype Application to Identify LGBT Patients in Clinical Notes
Workman T, Goulet J, Brandt C, Skanderson M, Wang R, Warren A, Eleazer J, Gordon K, Zeng-Treitler Q. A Prototype Application to Identify LGBT Patients in Clinical Notes. 2020, 00: 4270-4275. DOI: 10.1109/bigdata50022.2020.9378109.Peer-Reviewed Original ResearchElectronic health record notesPrototype applicationLGBT patientsRule-based patternLarge data sourcesBinary classification taskRecord notesData scientistsMachine learningClassification taskPositive predictive valueData researchData sourcesTest setClinical relevancePredictive valueHealthcare providersPatientsClinical notesHealth disparitiesLittle workDisproportional burdenApplicationsTaskLearning
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