2023
Collecting patient-reported outcome measures in the electronic health record: Lessons from the NIH pragmatic trials Collaboratory
Zigler C, Adeyemi O, Boyd A, Braciszewski J, Cheville A, Cuthel A, Dailey D, Del Fiol G, Ezenwa M, Faurot K, Justice M, Ho P, Lawrence K, Marsolo K, Patil C, Paek H, Richesson R, Staman K, Schlaeger J, O'Brien E. Collecting patient-reported outcome measures in the electronic health record: Lessons from the NIH pragmatic trials Collaboratory. Contemporary Clinical Trials 2023, 137: 107426. PMID: 38160749, PMCID: PMC10922303, DOI: 10.1016/j.cct.2023.107426.Peer-Reviewed Original ResearchPatient-reported outcome measuresElectronic health recordsPragmatic clinical trialsOutcome measuresHealth recordsClinical trialsHealth system's electronic health recordPatient-reported outcome dataOutcome measure selectionLow-resource settingsSecondary outcomesOutcome dataResource settingsLack of consensusStudy teamTrialsSystem prioritiesRecordsCliniciansAdministrationMeasuresQuantifying 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
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
2019
Identifying Opioid Use Disorder in the Emergency Department: Multi-System Electronic Health Record–Based Computable Phenotype Derivation and Validation Study
Chartash D, Paek H, Dziura JD, Ross BK, Nogee DP, Boccio E, Hines C, Schott AM, Jeffery MM, Patel MD, Platts-Mills TF, Ahmed O, Brandt C, Couturier K, Melnick E. Identifying Opioid Use Disorder in the Emergency Department: Multi-System Electronic Health Record–Based Computable Phenotype Derivation and Validation Study. JMIR Medical Informatics 2019, 7: e15794. PMID: 31674913, PMCID: PMC6913746, DOI: 10.2196/15794.Peer-Reviewed Original ResearchOpioid use disorderNegative predictive valuePositive predictive valueEmergency department patientsEmergency departmentUse disordersHealth care systemPredictive valueComputable phenotypeExternal validation phasesDepartment patientsCare systemPhysician chart reviewLarge health care systemExternal validation cohortEmergency medicine physiciansHigh predictive valueElectronic health recordsChart reviewChief complaintValidation cohortPragmatic trialClinical dataBilling codesMedicine physicians
2006
Qualitative study of patients' perceptions of safety and risk related to electronic health records in a hospital.
Paek HM, Swiatek-Kelley J, O'Connell R, Brandt C. Qualitative study of patients' perceptions of safety and risk related to electronic health records in a hospital. AMIA Annual Symposium Proceedings 2006, 2006: 1054. PMID: 17238673, PMCID: PMC1839539.Peer-Reviewed Original Research