2024
Virtual Scribes and Physician Time Spent on Electronic Health Records
Rotenstein L, Melnick E, Iannaccone C, Zhang J, Mugal A, Lipsitz S, Healey M, Holland C, Snyder R, Sinsky C, Ting D, Bates D. Virtual Scribes and Physician Time Spent on Electronic Health Records. JAMA Network Open 2024, 7: e2413140. PMID: 38787556, PMCID: PMC11127114, DOI: 10.1001/jamanetworkopen.2024.13140.Peer-Reviewed Original ResearchConceptsEHR timeElectronic health recordsHealth recordsPhysician timePre-post quality improvement studyPrimary care specialtiesQuality improvement studyFactors associated with changesAssociated with significant decreasesAssociated with burnoutMultivariate linear regression modelAcademic medical centerCare specialtiesImprovement studyLinear regression modelsMedical specialistsMedical specialtiesOutpatient settingStudy sampleSignificant decreasePhysiciansMedical CenterParticipation episodesAppointmentWomen's Hospital
2023
Why Do Physicians Depart Their Practice? A Qualitative Study of Attrition in a Multispecialty Ambulatory Practice Network
O'Connell R, Hosain F, Colucci L, Nath B, Melnick E. Why Do Physicians Depart Their Practice? A Qualitative Study of Attrition in a Multispecialty Ambulatory Practice Network. The Journal Of The American Board Of Family Medicine 2023, 36: 1050-1057. PMID: 37857441, DOI: 10.3122/jabfm.2023.230052r2.Peer-Reviewed Original ResearchAssociation of Primary Care Physicians’ Electronic Inbox Activity Patterns with Patients’ Likelihood to Recommend the Physician
Rotenstein L, Melnick E, Jeffery M, Zhang J, Sinsky C, Gitomer R, Bates D. Association of Primary Care Physicians’ Electronic Inbox Activity Patterns with Patients’ Likelihood to Recommend the Physician. Journal Of General Internal Medicine 2023, 39: 150-152. PMID: 37731135, PMCID: PMC10817856, DOI: 10.1007/s11606-023-08417-8.Peer-Reviewed Original ResearchPredicting 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
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
2021
Analysis 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
2019
The Association Between Perceived Electronic Health Record Usability and Professional Burnout Among US Physicians
Melnick ER, Dyrbye LN, Sinsky CA, Trockel M, West CP, Nedelec L, Tutty MA, Shanafelt T. The Association Between Perceived Electronic Health Record Usability and Professional Burnout Among US Physicians. Mayo Clinic Proceedings 2019, 95: 476-487. PMID: 31735343, DOI: 10.1016/j.mayocp.2019.09.024.Peer-Reviewed Original ResearchConceptsElectronic health record usabilityOdds of burnoutUS physiciansStrong dose-response relationshipAmerican Medical Association Physician MasterfileEHR usabilityDose-response relationshipCross-sectional surveyLower oddsPhysician MasterfileMultivariate analysisPractice settingsCurrent EHR systemsMaslach Burnout InventoryPhysiciansSUS scoreProfessional burnoutMedical specialtiesNumber of nightsPrevious studiesOddsScoresPhysician usersTechnology usabilityBurnout Inventory