2023
Adoption of Emergency Department–Initiated Buprenorphine for Patients With Opioid Use Disorder
Gao E, Melnick E, Paek H, Nath B, Taylor R, Loza A. Adoption of Emergency Department–Initiated Buprenorphine for Patients With Opioid Use Disorder. JAMA Network Open 2023, 6: e2342786. PMID: 37948075, PMCID: PMC10638655, DOI: 10.1001/jamanetworkopen.2023.42786.Peer-Reviewed Original ResearchConceptsHealth care systemED initiationOpioid use disorderBuprenorphine initiationCare systemUse disordersEmergency Department-Initiated BuprenorphineSecondary analysisClinician's roleEmergency department initiationClinical decision support interventionClinical decision support toolProportional hazard modelingCare of patientsNetwork of cliniciansDecision support interventionsAdvanced practice practitionersDose-dependent mannerUnique cliniciansTime-dependent covariatesTrial interventionNonintervention groupED clustersMore effective interventionsNumber of exposuresQuantifying EHR and Policy Factors Associated with the Gender Productivity Gap in Ambulatory, General Internal Medicine
Li H, Rotenstein L, Jeffery M, Paek H, Nath B, Williams B, McLean R, Goldstein R, Nuckols T, Hoq L, Melnick E. Quantifying EHR and Policy Factors Associated with the Gender Productivity Gap in Ambulatory, General Internal Medicine. Journal Of General Internal Medicine 2023, 39: 557-565. PMID: 37843702, PMCID: PMC10973284, DOI: 10.1007/s11606-023-08428-5.Peer-Reviewed Original ResearchElectronic health recordsWork relative value unitsPhysician genderPractice characteristicsWomen physiciansMen physiciansGeneral internal medicine physiciansEHR useInternal medicine physiciansPhysician productivityGeneral internal medicineMultivariable adjustmentPatient counselingCare discussionsPhysician ageClinical activityMedicine physiciansPredicting 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
User centered clinical decision support to implement initiation of buprenorphine for opioid use disorder in the emergency department: EMBED pragmatic cluster randomized controlled trial
Melnick ER, Nath B, Dziura JD, Casey MF, Jeffery MM, Paek H, Soares WE, Hoppe JA, Rajeevan H, Li F, Skains RM, Walter LA, Patel MD, Chari SV, Platts-Mills TF, Hess EP, D'Onofrio G. User centered clinical decision support to implement initiation of buprenorphine for opioid use disorder in the emergency department: EMBED pragmatic cluster randomized controlled trial. The BMJ 2022, 377: e069271. PMID: 35760423, PMCID: PMC9231533, DOI: 10.1136/bmj-2021-069271.Peer-Reviewed Original ResearchConceptsOpioid use disorderUsual care armEmergency departmentUse disordersCare armPragmatic clusterClinical decision supportIntervention armRoutine emergency careSecondary implementation outcomesSeverity of withdrawalTertiary care centerClinical decision support toolInitiation of buprenorphineElectronic health record tasksElectronic health record workflowsRE-AIM frameworkElectronic health record platformsHealth record platformsClinical decision support systemElectronic health recordsVisit documentationTreatment of addictionUsual careAdult patients
2021
Emergency Department Visits for Nonfatal Opioid Overdose During the COVID-19 Pandemic Across Six US Health Care Systems
Soares WE, Melnick ER, Nath B, D'Onofrio G, Paek H, Skains RM, Walter LA, Casey MF, Napoli A, Hoppe JA, Jeffery MM. Emergency Department Visits for Nonfatal Opioid Overdose During the COVID-19 Pandemic Across Six US Health Care Systems. Annals Of Emergency Medicine 2021, 79: 158-167. PMID: 34119326, PMCID: PMC8449788, DOI: 10.1016/j.annemergmed.2021.03.013.Peer-Reviewed Original ResearchConceptsHealth care systemCause ED visitsNonfatal opioid overdoseED visitsOpioid use disorderCare systemOpioid overdoseUse disordersCOVID-19 pandemicOpioid-related complicationsEmergency department visitsHospital-based interventionsED visit ratesEmergency department utilizationVisit countsUS health care systemOpioid overdose ratesDepartment visitsHistorical controlsAdult visitsOpioid overdosesOverdose ratesMedical emergencyVisit ratesMore weeks
2020
Progress 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 effectiveness
2024
Correction: 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. Correction: Predicting physician departure with machine learning on EHR use patterns: A longitudinal cohort from a large multi-specialty ambulatory practice. PLOS ONE 2024, 19: e0315090. PMID: 39625911, PMCID: PMC11614266, DOI: 10.1371/journal.pone.0315090.Peer-Reviewed Original Research