2025
Detection of emergency department patients at risk of dementia through artificial intelligence
Cohen I, Taylor R, Xue H, Faustino I, Festa N, Brandt C, Gao E, Han L, Khasnavis S, Lai J, Mecca A, Sapre A, Young J, Zanchelli M, Hwang U. Detection of emergency department patients at risk of dementia through artificial intelligence. Alzheimer's & Dementia 2025, 21: e70334. PMID: 40457744, PMCID: PMC12130574, DOI: 10.1002/alz.70334.Peer-Reviewed Original ResearchConceptsElectronic health record dataHealth record dataEmergency departmentDetect dementiaDementia detectionYale New Haven HealthRecord dataRisk of dementiaEmergency department patientsBalance detection accuracyDementia algorithmsImprove patient outcomesCare coordinationCare transitionsDementia diagnosisReal-time applicationsClinical decision-makingClinician supportED usePatient safetyProbable dementiaMachine learning algorithmsED workflowED visitsED encountersPredicting Agitation Events in the Emergency Department Through Artificial Intelligence
Wong A, Sapre A, Wang K, Nath B, Shah D, Kumar A, Faustino I, Desai R, Hu Y, Robinson L, Meng C, Tong G, Bernstein S, Yonkers K, Melnick E, Dziura J, Taylor R. Predicting Agitation Events in the Emergency Department Through Artificial Intelligence. JAMA Network Open 2025, 8: e258927. PMID: 40332935, PMCID: PMC12059975, DOI: 10.1001/jamanetworkopen.2025.8927.Peer-Reviewed Original ResearchConceptsED visitsEmergency departmentAgitation eventsElectronic health record dataArea under the receiver operating characteristic curvePatient-centered careHealth service utilizationPrimary outcomeHealth record dataUrban health systemED visit dataMode of arrivalPrevention of agitationOutcome of agitationDiverse patient populationsRestraint ordersCross-sectional cohortService utilizationVital signsED sitesHealth systemMain OutcomesRestraint eventsRange of predicted probabilitiesVisit dataMapping Emergency Medicine Data to the Observational Medical Outcomes Partnership Common Data Model: A Gap Analysis of the American College of Emergency Physicians Clinical Emergency Data Registry
Cohen I, Diao Z, Goyal P, Gupta A, Hawk K, Malcom B, Malicki C, Sharma D, Sweeney B, Weiner S, Venkatesh A, Taylor R. Mapping Emergency Medicine Data to the Observational Medical Outcomes Partnership Common Data Model: A Gap Analysis of the American College of Emergency Physicians Clinical Emergency Data Registry. Journal Of The American College Of Emergency Physicians Open 2025, 6: 100016. PMID: 40012646, PMCID: PMC11853007, DOI: 10.1016/j.acepjo.2024.100016.Peer-Reviewed Original ResearchObservational Medical Outcomes Partnership Common Data ModelCommon Data ModelOMOP CDMElectronic health record dataData RegistryObservational Health Data SciencesHealth record dataEmergency department dataData modelDepartment dataRecord dataCommunity forumsAmerican CollegePublic healthDescriptive analysisRegistryData harmonizationData scienceGap analysisData fieldCross-institutional collaborationMapping processMedicine dataPotential challengesHealth
2024
Racial, Ethnic, and Age-Related Disparities in Sedation and Restraint Use for Older Adults in the Emergency Department
Jivalagian P, Gettel C, Smith C, Robinson L, Brinker M, Shah D, Kumar A, Faustino I, Nath B, Chang-Sing E, Taylor R, Kennedy M, Hwang U, Wong A. Racial, Ethnic, and Age-Related Disparities in Sedation and Restraint Use for Older Adults in the Emergency Department. American Journal Of Geriatric Psychiatry 2024, 33: 1-14. PMID: 39054237, PMCID: PMC11625012, DOI: 10.1016/j.jagp.2024.07.004.Peer-Reviewed Original ResearchPhysical restraint useRestraint useOlder adultsED visitsPhysical restraintEmergency departmentElectronic health record dataHealth record dataBlack non-HispanicPatient-level characteristicsAge-related disparitiesAssociated with increased useRegional hospital networkCross-sectional studyLogistic regression modelsChemical sedationRetrospective cross-sectional studyNon-Hispanic groupNon-HispanicAgitation managementHospital sitesHospital networkRecord dataWhite non-Hispanic groupPrimary outcome
2023
Computational phenotypes for patients with opioid-related disorders presenting to the emergency department
Taylor R, Gilson A, Schulz W, Lopez K, Young P, Pandya S, Coppi A, Chartash D, Fiellin D, D’Onofrio G. Computational phenotypes for patients with opioid-related disorders presenting to the emergency department. PLOS ONE 2023, 18: e0291572. PMID: 37713393, PMCID: PMC10503758, DOI: 10.1371/journal.pone.0291572.Peer-Reviewed Original ResearchConceptsSubstance use disordersUse disordersED visitsPatient presentationCarlson comorbidity indexOpioid-related diagnosesOpioid-related disordersOne-year survivalRate of medicationOpioid use disorderElectronic health record dataPatient-oriented outcomesYears of ageHealth record dataChronic substance use disordersED returnComorbidity indexAcute overdoseMedical managementClinical entityRetrospective studyEmergency departmentChronic conditionsInclusion criteriaUnique cohortDisparities Associated With Electronic Behavioral Alerts for Safety and Violence Concerns in the Emergency Department
Haimovich A, Taylor R, Chang-Sing E, Brashear T, Cramer L, Lopez K, Wong A. Disparities Associated With Electronic Behavioral Alerts for Safety and Violence Concerns in the Emergency Department. Annals Of Emergency Medicine 2023, 83: 100-107. PMID: 37269262, PMCID: PMC10689576, DOI: 10.1016/j.annemergmed.2023.04.004.Peer-Reviewed Original ResearchConceptsHealth care systemEmergency departmentPatient-level analysisCare systemED visitsLeft-without-being-seenNegative perceptions of patientsElectronic health record dataUnited States health care systemRegional health care systemStates health care systemDiscontinuity of careHealth record dataElectronic health recordsBlack non-Hispanic patientsPerceptions of patientsBlack non-HispanicRetrospective cross-sectional study of adult patientsAdult emergency departmentNon-Hispanic patientsCross-sectional study of adult patientsMixed-effects regression analysisStudy periodRetrospective cross-sectional studyCare delivery
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