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 demandMachineValidatingPatientsProgress Report on EMBED: A Pragmatic Trial of User-Centered Clinical Decision Support to Implement EMergency Department-Initiated BuprenorphinE for Opioid Use Disorder †
Melnick ER, Nath B, Ahmed OM, Brandt C, Chartash D, Dziura JD, Hess EP, Holland WC, Hoppe JA, Jeffery MM, Katsovich L, Li F, Lu CC, Maciejewski K, Maleska M, Mao JA, Martel S, Michael S, Paek H, Patel MD, Platts-Mills TF, Rajeevan H, Ray JM, Skains RM, Soares WE, Deutsch A, Solad Y, D’Onofrio G. Progress Report on EMBED: A Pragmatic Trial of User-Centered Clinical Decision Support to Implement EMergency Department-Initiated BuprenorphinE for Opioid Use Disorder †. Journal Of Psychiatry And Brain Science 2020, 2: e200003. PMID: 32309637, PMCID: PMC7164817, DOI: 10.20900/jpbs.20200003.Peer-Reviewed Original ResearchBuprenorphine/naloxoneOpioid use disorderClinical decision supportPragmatic trialElectronic health recordsUse disordersEmergency Department-Initiated BuprenorphineMulti-centre pragmatic trialRoutine emergency careHealthcare systemRates of EDNaloxone prescribingPilot testingSingle EDEmergency departmentPhysicians' perceptionsEmergency careMortality rateEarly identificationComputable phenotypeUnique physiciansInformed consentCare paradigmHealth recordsIntervention effectivenessPragmatic clinical trial design in emergency medicine: Study considerations and design types
Gettel CJ, Yiadom MYAB, Bernstein SL, Grudzen CR, Nath B, Li F, Hwang U, Hess EP, Melnick ER. Pragmatic clinical trial design in emergency medicine: Study considerations and design types. Academic Emergency Medicine 2022, 29: 1247-1257. PMID: 35475533, PMCID: PMC9790188, DOI: 10.1111/acem.14513.Peer-Reviewed Original ResearchConceptsPragmatic clinical trialsClinical trial designTrial designReal-world clinical practicePragmatic clinical trial designElectronic health recordsEmergency departmentClinical trialsStudy design typeClinical practiceStudy typeTrial componentsHealth recordsEmergency medicineEmergency medicine investigatorsHuman subjects concernsInvestigatorsStudy findingsStudy considerationsTrialistsTrialsAnalysis of Electronic Health Record Use and Clinical Productivity and Their Association With Physician Turnover
Melnick ER, Fong A, Nath B, Williams B, Ratwani RM, Goldstein R, O’Connell R, Sinsky CA, Marchalik D, Mete M. Analysis of Electronic Health Record Use and Clinical Productivity and Their Association With Physician Turnover. JAMA Network Open 2021, 4: e2128790. PMID: 34636911, PMCID: PMC8511970, DOI: 10.1001/jamanetworkopen.2021.28790.Peer-Reviewed Original ResearchConceptsElectronic health recordsPhysician turnoverRetrospective cohort studyElectronic health record usePractice networkPhysician productivityWarrants further investigationCohort studyEHR timeAge 45Care teamPhysician departurePhysician ordersMAIN OUTCOMEHigh riskPatient timeAmbulatory physiciansPatient volumeUnique physiciansRecord useEHR useHealth care organizationsPhysiciansHealth recordsClinical timeCharacterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis
Melnick ER, Ong SY, Fong A, Socrates V, Ratwani RM, Nath B, Simonov M, Salgia A, Williams B, Marchalik D, Goldstein R, Sinsky CA. Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis. Journal Of The American Medical Informatics Association 2021, 28: 1383-1392. PMID: 33822970, PMCID: PMC8279798, DOI: 10.1093/jamia/ocab011.Peer-Reviewed Original ResearchConceptsElectronic health recordsEHR timeCross-sectional analysisAmbulatory physiciansPatient timeHealth systemClinical hoursHours of patientsMedStar Health systemYale-New HavenObstetrics/gynecologyNeurology/psychiatryMultivariable analysisPhysician genderCertain medical specialtiesPhysical medicineFemale physiciansEHR usePhysiciansHealth recordsHealthcare systemMedical specialtiesHoursSpecialtiesGender