2025
Emergency Department Implementation of a Multimodal Electronic Health Record–Integrated Clinical Intervention for High-Sensitivity Troponin Testing Increases Diagnostic Efficiency
Sangal R, Iscoe M, Rothenberg C, Possick S, Taylor R, Safdar B, Desai N, Rhodes D, Venkatesh A. Emergency Department Implementation of a Multimodal Electronic Health Record–Integrated Clinical Intervention for High-Sensitivity Troponin Testing Increases Diagnostic Efficiency. Journal Of The American College Of Emergency Physicians Open 2025, 6: 100202. DOI: 10.1016/j.acepjo.2025.100202.Peer-Reviewed Original ResearchEmergency departmentAcute myocardial infarction diagnosisTroponin testingED dischargeMyocardial infarction diagnosisAssociated with lower oddsAccelerated diagnostic protocolPhysician practice variationAcute coronary syndromeInfarction diagnosisChest pain evaluationMultivariate logistic regressionSuspected acute coronary syndromePostintervention periodDownstream testingPhysician practicesPreintervention periodED dispositionLower oddsCoronary syndromeDecreased oddsIncreased oddsPractice variationED patientsHs-cTnTDetection 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 encountersNovel algorithms & blood‐based biomarkers: Dementia detection and care transitions for persons living with dementia in the emergency department
Saxena S, Carpenter C, Floden D, Meldon S, Taylor R, Hwang U. Novel algorithms & blood‐based biomarkers: Dementia detection and care transitions for persons living with dementia in the emergency department. Alzheimer's & Dementia 2025, 21: e70287. PMID: 40390207, PMCID: PMC12089069, DOI: 10.1002/alz.70287.Peer-Reviewed Original ResearchConceptsElectronic health recordsGeriatric emergency departmentCare partnersEmergency departmentImprove careLeveraging electronic health recordsRisk of dementiaHigh emergency departmentRisk stratification algorithmCare transitionsCoordinated careED environmentDeliver careED settingHealth recordsDementia detectionHealthcare systemHigh acuityCareOutpatient settingStratification algorithmDementiaEmergency cliniciansBlood-based biomarkersPLWDCorrection: 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. Correction: Computational phenotypes for patients with opioid-related disorders presenting to the emergency department. PLOS ONE 2025, 20: e0324877. PMID: 40378111, PMCID: PMC12083821, DOI: 10.1371/journal.pone.0324877.Peer-Reviewed Original ResearchPredicting 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 dataRacial, ethnic, and sex disparities in buprenorphine treatment from emergency departments by discharge diagnosis
Chhabra N, Smith D, Parde N, Hsing‐Smith N, Bianco J, Taylor R, D'Onofrio G, Karnik N. Racial, ethnic, and sex disparities in buprenorphine treatment from emergency departments by discharge diagnosis. Academic Emergency Medicine 2025 PMID: 40277252, DOI: 10.1111/acem.70035.Peer-Reviewed Original ResearchOpioid withdrawalPrescribing of buprenorphineEmergency departmentSex disparitiesBlack patientsDischarge diagnosisEffects of opioidsOpioid overdoseED-initiated buprenorphineOpioid-related ED encountersMultivariate logistic regressionReceipt of buprenorphineFemale patientsOpioid complicationsBuprenorphine treatmentWhite patientsCross-sectional analysisOpioid-related encountersOpioidAmerican patientsAdjusted oddsDecreased oddsBuprenorphinePatientsSubtype analysisIdentifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study
Socrates V, Wright D, Huang T, Fereydooni S, Dien C, Chi L, Albano J, Patterson B, Kanaparthy N, Wright C, Loza A, Chartash D, Iscoe M, Taylor R. Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study. JMIR Aging 2025, 8: e69504. PMID: 40215480, PMCID: PMC12032504, DOI: 10.2196/69504.Peer-Reviewed Original ResearchEmergency Care Access Based on a Proposed CMS National Quality Measure
Sangal R, Rothenberg C, Taylor R, Venkatesh A. Emergency Care Access Based on a Proposed CMS National Quality Measure. JAMA Health Forum 2025, 6: e250417. PMID: 40215073, PMCID: PMC11992599, DOI: 10.1001/jamahealthforum.2025.0417.Peer-Reviewed Original ResearchAutomated computation of the HEART score with the GPT-4 large language model
Wright D, Socrates V, Huang T, Safranek C, Sangal R, Dilip M, Boivin Z, Srica N, Wright C, Feher A, Miller E, Chartash D, Taylor R. Automated computation of the HEART score with the GPT-4 large language model. The American Journal Of Emergency Medicine 2025, 93: 120-125. PMID: 40184662, PMCID: PMC12202168, DOI: 10.1016/j.ajem.2025.03.065.Peer-Reviewed Original ResearchConceptsClinical decision supportHEART scoreChest pain observation unitAverage heart scoreCohen's weighted kappaDecision supportNurse practitionersPhysician assistantsRetrospective cohort studyRoutine careCases of disagreementProspective InvestigationAPP scoresCohort studySafety interventionsPhysician judgmentObservation unitAdverse cardiac eventsInstitutional registryScoresPhysiciansInterventionParticipantsNo significant differenceAppsImpact of Artificial Intelligence–Based Triage Decision Support on Emergency Department Care
Taylor R, Chmura C, Hinson J, Steinhart B, Sangal R, Venkatesh A, Xu H, Cohen I, Faustino I, Levin S. Impact of Artificial Intelligence–Based Triage Decision Support on Emergency Department Care. NEJM AI 2025, 2 DOI: 10.1056/aioa2400296.Peer-Reviewed Original ResearchAdaptive decision support for addiction treatment to implement initiation of buprenorphine for opioid use disorder in the emergency department: protocol for the ADAPT Multiphase Optimization Strategy trial
Iscoe M, Hooper C, Levy D, Buchanan L, Dziura J, Meeker D, Taylor R, D’Onofrio G, Oladele C, Sarpong D, Paek H, Wilson F, Heagerty P, Delgado M, Hoppe J, Melnick E. Adaptive decision support for addiction treatment to implement initiation of buprenorphine for opioid use disorder in the emergency department: protocol for the ADAPT Multiphase Optimization Strategy trial. BMJ Open 2025, 15: e098072. PMID: 39979056, PMCID: PMC11842997, DOI: 10.1136/bmjopen-2024-098072.Peer-Reviewed Original ResearchConceptsClinical decision supportMultiphase optimization strategyOpioid use disorderEmergency departmentInitiation of buprenorphineClinical decision support usePlan-Do-Study-Act cyclesLearning health system approachPlan-Do-Study-ActClinical decision support toolHealth system approachAdaptive decision supportUse disorderDecision supportAddiction treatmentPeer-reviewed journalsBuprenorphine initiationOpioid use disorder treatment initiationOpioid-related mortalityIntervention componentsED settingClinician feedbackInstitute Institutional Review BoardTreatment of opioid use disorderParticipating sitesAssociation between patient primary language, physical restraints, and intramuscular sedation in the emergency department
Kumar A, Ryus C, Tartak J, Nath B, Faustino I, Shah D, Robinson L, Desai R, Heckmann R, Taylor R, Wong A. Association between patient primary language, physical restraints, and intramuscular sedation in the emergency department. Academic Emergency Medicine 2025 PMID: 39948714, DOI: 10.1111/acem.70004.Peer-Reviewed Original ResearchPatient's primary languagePortuguese-speaking patientsPhysical restraintEmergency departmentPrimary languageED visitsQuality of clinical interactionsRegional health care networkHealth care networkVerbal de-escalationElectronic medical recordsLogistic regression modelsAdult patients ageLanguage speakersEnglish speakersCare networkSpanish speakersPortuguese speakersCultural interpretationRetrospective cohort analysisAgitation symptomsOdds ratioClinical interactionsEvaluate associationsPrimary outcomeUsing natural language processing to identify emergency department patients with incidental lung nodules requiring follow‐up
Moore C, Socrates V, Hesami M, Denkewicz R, Cavallo J, Venkatesh A, Taylor R. Using natural language processing to identify emergency department patients with incidental lung nodules requiring follow‐up. Academic Emergency Medicine 2025, 32: 274-283. PMID: 39821298, DOI: 10.1111/acem.15080.Peer-Reviewed Original ResearchNatural language processingIncidental lung nodulesFollow-upChest CTsCT reportsF1 scoreLung nodulesEmergency departmentLanguage processingFollow-up of incidental findingsIncidental findingNatural language processing developersAbsence of malignancyMetrics of precisionNatural language processing pipelineNatural language processing metricsChest CT reportsRecommended follow-upEmergency department patientsFollow-up rateLanguage modelLung cancerReduce errorsMalignancyDepartment patientsMapping 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 challengesHealthCharacterizing Emergency Department Care for Patients With Histories of Incarceration
Huang T, Socrates V, Ovchinnikova P, Faustino I, Kumar A, Safranek C, Chi L, Wang E, Puglisi L, Wong A, Wang K, Taylor R. Characterizing Emergency Department Care for Patients With Histories of Incarceration. Journal Of The American College Of Emergency Physicians Open 2025, 6: 100022. PMID: 40012663, PMCID: PMC11852703, DOI: 10.1016/j.acepjo.2024.100022.Peer-Reviewed Original ResearchCare processesHistory of incarcerationRestraint useEmergency departmentHealth care team membersMeasuring care processesCompare socio-demographic characteristicsCare team membersHealth care disparitiesEmergency department careHealth care systemSocio-demographic characteristicsUnique patient encountersMultivariate logistic regressionCare disparitiesHealth behaviorsED settingCare systemPatient encountersSubstance use historyMedical adviceLogistic regressionDemographic characteristicsTeam membersCare
2024
Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions
Taylor R, Sangal R, Smith M, Haimovich A, Rodman A, Iscoe M, Pavuluri S, Rose C, Janke A, Wright D, Socrates V, Declan A. Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions. Academic Emergency Medicine 2024, 32: 327-339. PMID: 39676165, PMCID: PMC11921089, DOI: 10.1111/acem.15066.Peer-Reviewed Original ResearchClinical decision supportEmergency departmentArtificial intelligencePatient safetyDiagnostic errorsImplementing AIImprove patient safetyClinical decision support systemsEnhance patient outcomesReducing diagnostic errorsLeverage artificial intelligenceEmergency medicineHealth careTargeted educationReduce cognitive loadQuality improvementEmergency cliniciansData retrievalReal-time insightsDecision supportPatient outcomesCognitive overloadInformation-gathering processPatient detailsCliniciansEnhancing Emergency Department Triage Equity With Artificial Intelligence: Outcomes From a Multisite Implementation
Hinson J, Levin S, Steinhart B, Chmura C, Sangal R, Venkatesh A, Taylor R. Enhancing Emergency Department Triage Equity With Artificial Intelligence: Outcomes From a Multisite Implementation. Annals Of Emergency Medicine 2024, 85: 288-290. PMID: 39570253, DOI: 10.1016/j.annemergmed.2024.10.014.Peer-Reviewed Original ResearchHEART: Learning better representation of EHR data with a heterogeneous relation-aware transformer
Huang T, Rizvi S, Thakur R, Socrates V, Gupta M, van Dijk D, Taylor R, Ying R. HEART: Learning better representation of EHR data with a heterogeneous relation-aware transformer. Journal Of Biomedical Informatics 2024, 159: 104741. PMID: 39476994, DOI: 10.1016/j.jbi.2024.104741.Peer-Reviewed Original ResearchElectronic health recordsElectronic health record datasetDownstream tasksLanguage modelModeling electronic health recordsLearning better representationsPretrained language modelsEntity predictionRepresentation learningAnomaly detectionAttention weightsRelation embeddingsHealthcare applicationsEncoding schemeMed-BERTHigher-order representationsInput sequenceComputational costReadmission predictionPairwise relationshipsEHR dataElectronic health record dataSuperior performanceHeterogeneous contextsMedical entitiesTrends and Disparities in Initiation of Buprenorphine in US Emergency Departments, 2013-2022
Chhabra N, Smith D, Dickinson G, Caglianone L, Taylor R, D’Onofrio G, Karnik N. Trends and Disparities in Initiation of Buprenorphine in US Emergency Departments, 2013-2022. JAMA Network Open 2024, 7: e2435603. PMID: 39325455, PMCID: PMC11428009, DOI: 10.1001/jamanetworkopen.2024.35603.Peer-Reviewed Original ResearchAccelerated Chest Pain Treatment With Artificial Intelligence–Informed, Risk-Driven Triage
Hinson J, Taylor R, Venkatesh A, Steinhart B, Chmura C, Sangal R, Levin S. Accelerated Chest Pain Treatment With Artificial Intelligence–Informed, Risk-Driven Triage. JAMA Internal Medicine 2024, 184: 1125-1127. PMID: 39037785, PMCID: PMC11264065, DOI: 10.1001/jamainternmed.2024.3219.Peer-Reviewed Original Research
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