Mark Iscoe, MD, MHS
Assistant Professor of Emergency Medicine and Biomedical Informatics and Data ScienceCards
About
Research
Publications
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-cTnTCase Report: A health system’s experience using clinical decision support to promote note sharing after the 21st Century Cures Act
Iscoe M, Venkatesh A, Powers E, Kashyap N, Hsiao A, Millard H, Sangal R. Case Report: A health system’s experience using clinical decision support to promote note sharing after the 21st Century Cures Act. JAMIA Open 2025, 8: ooaf051. PMID: 40510806, PMCID: PMC12161449, DOI: 10.1093/jamiaopen/ooaf051.Peer-Reviewed Original ResearchClinical decision supportHealth system's experienceRegional health systemDecision supportPatient engagementCentury Cures ActHealth systemPortal accessClinical notesConsistent with prior research showingCures ActPromote complianceSensitive informationStudy periodLinear regressionPediatricObservational analysisPsychiatryPatients/proxiesNotesPatientsSupportHealthCliniciansResearch showIdentifying 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 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 sites
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 detailsCliniciansBenchmarking Emergency Physician EHR Time per Encounter Based on Patient and Clinical Factors
Iscoe M, Venkatesh A, Holland M, Krumholz H, Sheares K, Melnick E. Benchmarking Emergency Physician EHR Time per Encounter Based on Patient and Clinical Factors. JAMA Network Open 2024, 7: e2427389. PMID: 39136949, PMCID: PMC11322841, DOI: 10.1001/jamanetworkopen.2024.27389.Peer-Reviewed Original ResearchIdentifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models
Iscoe M, Socrates V, Gilson A, Chi L, Li H, Huang T, Kearns T, Perkins R, Khandjian L, Taylor R. Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models. Academic Emergency Medicine 2024, 31: 599-610. PMID: 38567658, DOI: 10.1111/acem.14883.Peer-Reviewed Original ResearchElectronic health recordsNatural language processingNatural language processing modelsEmergency departmentTransformer-based modelsClinical notesF1-measureClinical decision supportLanguage modelSpaCy modelsU.S. health systemElements of natural language processingPublic health surveillanceConvolutional neural network-based modelProcessing long documentsIdentification of symptomsHealth recordsHealth systemClinician notesNeural network-based modelMedical careHealth surveillanceSymptom identificationEntity recognitionNetwork-based modelAutomated HEART score determination via ChatGPT: Honing a framework for iterative prompt development
Safranek C, Huang T, Wright D, Wright C, Socrates V, Sangal R, Iscoe M, Chartash D, Taylor R. Automated HEART score determination via ChatGPT: Honing a framework for iterative prompt development. Journal Of The American College Of Emergency Physicians Open 2024, 5: e13133. PMID: 38481520, PMCID: PMC10936537, DOI: 10.1002/emp2.13133.Peer-Reviewed Original ResearchPrompt designsChest pain evaluationRule-based logicScore determinationLanguage modelPrivacy safeguardsPrompt improvementExtract insightsPain evaluationClinical notesRate of responseDiagnostic performancePhysician assessmentPrompt testingDetermination of heartChatGPTDesign frameworkNote analysisHeartSubscoresSimulated patientsClinical space
2023
PROSER: A Web-Based Peripheral Blood Smear Interpretation Support Tool Utilizing Electronic Health Record Data
Iscoe M, Loza A, Turbiville D, Campbell S, Peaper D, Balbuena-Merle R, Hauser R. PROSER: A Web-Based Peripheral Blood Smear Interpretation Support Tool Utilizing Electronic Health Record Data. American Journal Of Clinical Pathology 2023, 160: 98-105. PMID: 37026746, DOI: 10.1093/ajcp/aqad024.Peer-Reviewed Original ResearchConceptsQuality improvement studyElectronic health recordsLaboratory valuesWeb-based clinical decision support toolClinical decision support toolElectronic health record dataHealth record dataImprovement studyResident trainingBlood smear interpretationClinical outcomesMorphologic findingsAcademic hospitalCorresponding reference rangesMedication informationReference rangeMicroscopy findingsCDS toolsIntervention effectsPathology practiceSmear interpretationHealth recordsRecord dataPathologistsPatients
2022
Restoring Meaningful Content to the Medical Record: Standardizing Measurement Could Improve EHR Utility While Decreasing Burden
Iscoe MS, McLean RM, Melnick ER. Restoring Meaningful Content to the Medical Record: Standardizing Measurement Could Improve EHR Utility While Decreasing Burden. Mayo Clinic Proceedings 2022, 97: 1971-1974. PMID: 36210197, DOI: 10.1016/j.mayocp.2022.07.007.Peer-Reviewed Original ResearchConceptsMedical records
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