2024
Benchmarking 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 model
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
Cluster Analysis of Primary Care Physician Phenotypes for Electronic Health Record Use: Retrospective Cohort Study
Fong A, Iscoe M, Sinsky CA, Haimovich A, Williams B, O'Connell RT, Goldstein R, Melnick E. Cluster Analysis of Primary Care Physician Phenotypes for Electronic Health Record Use: Retrospective Cohort Study. JMIR Medical Informatics 2022, 10: e34954. PMID: 35275070, PMCID: PMC9055474, DOI: 10.2196/34954.Peer-Reviewed Original ResearchElectronic health recordsCare physiciansEHR timeRetrospective cohort studyRetrospective cohort analysisElectronic health record usePrimary care physiciansOffice-based physician practicesClusters of physiciansAmbulatory care physiciansCohort studyCohort analysisPediatric specialtiesInternal medicineRecord useEHR usePhysiciansPhysician practicesHealth recordsFamily medicineHoursPhenotype clustersPhenotypeLarge proportionMedicine