2023
Predicting physician departure with machine learning on EHR use patterns: A longitudinal cohort from a large multi-specialty ambulatory practice
Lopez K, Li H, Paek H, Williams B, Nath B, Melnick E, Loza A. Predicting physician departure with machine learning on EHR use patterns: A longitudinal cohort from a large multi-specialty ambulatory practice. PLOS ONE 2023, 18: e0280251. PMID: 36724149, PMCID: PMC9891518, DOI: 10.1371/journal.pone.0280251.Peer-Reviewed Original ResearchConceptsElectronic health recordsEHR use patternsHealthcare industryPhysician departureSHAP valuesHealth recordsPhysician characteristicsLongitudinal cohortPhysician ageRisk physiciansAmbulatory practiceTargeted interventionsAppropriate interventionsPhysiciansTop variablesDocumentation timePhysician turnoverPredictive modelHeavy burdenInterventionInboxPhysician demandMachineValidatingPatients
2022
Emergency physicians' EHR use across hospitals: A cross-sectional analysis
Iscoe MS, Holland ML, Paek H, Flood C, Melnick ER. Emergency physicians' EHR use across hospitals: A cross-sectional analysis. The American Journal Of Emergency Medicine 2022, 61: 205-207. PMID: 35842301, DOI: 10.1016/j.ajem.2022.07.014.Peer-Reviewed Original Research