2024
Balancing act: the complex role of artificial intelligence in addressing burnout and healthcare workforce dynamics
Pavuluri S, Sangal R, Sather J, Taylor R. Balancing act: the complex role of artificial intelligence in addressing burnout and healthcare workforce dynamics. BMJ Health & Care Informatics Online 2024, 31: e101120. PMID: 39181545, PMCID: PMC11344516, DOI: 10.1136/bmjhci-2024-101120.Peer-Reviewed Original ResearchConceptsQuality of patient careSustainability of health systemsComplexity of medical informationArtificial intelligenceWorkforce attritionHealth systemClinical skillsPatient careSense of purposeHealthcare workersHealthcareMedical informationWorkforce dynamicsMedical practiceProfessional attributesDigital scribeData management systemCognitive burdenBurnoutAdvanced data management systemsAI technologyAI potentialAutomated billingSignificant riskCaregiversSOFA score performs worse than age for predicting mortality in patients with COVID-19
Sherak R, Sajjadi H, Khimani N, Tolchin B, Jubanyik K, Taylor R, Schulz W, Mortazavi B, Haimovich A. SOFA score performs worse than age for predicting mortality in patients with COVID-19. PLOS ONE 2024, 19: e0301013. PMID: 38758942, PMCID: PMC11101117, DOI: 10.1371/journal.pone.0301013.Peer-Reviewed Original ResearchConceptsCrisis standards of careIn-hospital mortalityIntensive care unitAcademic health systemSequential Organ Failure Assessment scoreCohort of intensive care unitSequential Organ Failure AssessmentStandard of careLogistic regression modelsMortality predictionPredicting in-hospital mortalityHealth systemUnivariate logistic regression modelCrisis standardsDisease morbidityCOVID-19Geriatric End-of-Life Screening Tool Prediction of 6-Month Mortality in Older Patients
Haimovich A, Burke R, Nathanson L, Rubins D, Taylor R, Kross E, Ouchi K, Shapiro N, Schonberg M. Geriatric End-of-Life Screening Tool Prediction of 6-Month Mortality in Older Patients. JAMA Network Open 2024, 7: e2414213. PMID: 38819823, PMCID: PMC11143461, DOI: 10.1001/jamanetworkopen.2024.14213.Peer-Reviewed Original ResearchConceptsElectronic health recordsEmergency departmentObserved mortality rateED encountersEnd-of-Life Screening ToolOlder adultsEnd-of-life preferencesMortality riskIllness criteriaLife-limiting illnessOptimal screening criteriaDays of ED arrivalEHR-based algorithmTertiary care EDLow risk of mortalityHigher mortality riskMortality rateRisk of mortalityHealth recordsReceiver operating characteristic curveIllness diagnosisMain OutcomesED arrivalSerious illnessDemographic subgroupsThe Scope of Multimorbidity in Family Medicine: Identifying Age Patterns Across the Lifespan
Chartash D, Gilson A, Taylor R, Hart L. The Scope of Multimorbidity in Family Medicine: Identifying Age Patterns Across the Lifespan. The Journal Of The American Board Of Family Medicine 2024, 37: 251-260. PMID: 38740476, DOI: 10.3122/jabfm.2023.230221r1.Peer-Reviewed Original ResearchConceptsRates of multimorbidityICD-10 diagnostic codesFamily medicine clinicPresence of multimorbidityHealth care systemCardiometabolic disordersMedical historyStudy periodMultimorbidity rateMultimorbidity indexGroup of diagnosesPatient transitionsFamily medicineGeriatric careRetrospective cohort studyCare systemMental healthMultimorbidityMedicine clinicDiagnostic codesPractical resourcesAlcohol use disorderCohort studyAged 0Age groupsFormative evaluation of an emergency department clinical decision support system for agitation symptoms: a study protocol
Wong A, Nath B, Shah D, Kumar A, Brinker M, Faustino I, Boyce M, Dziura J, Heckmann R, Yonkers K, Bernstein S, Adapa K, Taylor R, Ovchinnikova P, McCall T, Melnick E. Formative evaluation of an emergency department clinical decision support system for agitation symptoms: a study protocol. BMJ Open 2024, 14: e082834. PMID: 38373857, PMCID: PMC10882402, DOI: 10.1136/bmjopen-2023-082834.Peer-Reviewed Original ResearchConceptsComputerised clinical decision supportED treatRestraint useExperiences of restraint useMental health-related visitsEmergency departmentPrevent agitationSystems-related factorsImprove patient experienceClinical decision support systemsRegional health systemClinical decision supportDe-escalation techniquesRandomised controlled trialsFormative evaluationPeer-reviewed journalsBest-practice guidanceAt-risk populationsCDS toolsThematic saturationED cliniciansPatient experienceED sitesHealth systemED physicians
2023
Dementia risk analysis using temporal event modeling on a large real-world dataset
Taylor R, Gilson A, Chi L, Haimovich A, Crawford A, Brandt C, Magidson P, Lai J, Levin S, Mecca A, Hwang U. Dementia risk analysis using temporal event modeling on a large real-world dataset. Scientific Reports 2023, 13: 22618. PMID: 38114545, PMCID: PMC10730574, DOI: 10.1038/s41598-023-49330-8.Peer-Reviewed Original ResearchAdoption 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 exposuresComputational phenotypes for patients with opioid-related disorders presenting to the emergency department
Taylor R, Gilson A, Schulz W, Lopez K, Young P, Pandya S, Coppi A, Chartash D, Fiellin D, D’Onofrio G. Computational phenotypes for patients with opioid-related disorders presenting to the emergency department. PLOS ONE 2023, 18: e0291572. PMID: 37713393, PMCID: PMC10503758, DOI: 10.1371/journal.pone.0291572.Peer-Reviewed Original ResearchConceptsSubstance use disordersUse disordersED visitsPatient presentationCarlson comorbidity indexOpioid-related diagnosesOpioid-related disordersOne-year survivalRate of medicationOpioid use disorderElectronic health record dataPatient-oriented outcomesYears of ageHealth record dataChronic substance use disordersED returnComorbidity indexAcute overdoseMedical managementClinical entityRetrospective studyEmergency departmentChronic conditionsInclusion criteriaUnique cohortDisparities Associated With Electronic Behavioral Alerts for Safety and Violence Concerns in the Emergency Department
Haimovich A, Taylor R, Chang-Sing E, Brashear T, Cramer L, Lopez K, Wong A. Disparities Associated With Electronic Behavioral Alerts for Safety and Violence Concerns in the Emergency Department. Annals Of Emergency Medicine 2023, 83: 100-107. PMID: 37269262, PMCID: PMC10689576, DOI: 10.1016/j.annemergmed.2023.04.004.Peer-Reviewed Original ResearchConceptsHealth care systemEmergency departmentPatient-level analysisCare systemED visitsLeft-without-being-seenNegative perceptions of patientsElectronic health record dataUnited States health care systemRegional health care systemStates health care systemDiscontinuity of careHealth record dataElectronic health recordsBlack non-Hispanic patientsPerceptions of patientsBlack non-HispanicRetrospective cross-sectional study of adult patientsAdult emergency departmentNon-Hispanic patientsCross-sectional study of adult patientsMixed-effects regression analysisStudy periodRetrospective cross-sectional studyCare deliveryPredicting relations between SOAP note sections: The value of incorporating a clinical information model
Socrates V, Gilson A, Lopez K, Chi L, Taylor R, Chartash D. Predicting relations between SOAP note sections: The value of incorporating a clinical information model. Journal Of Biomedical Informatics 2023, 141: 104360. PMID: 37061014, PMCID: PMC10197152, DOI: 10.1016/j.jbi.2023.104360.Peer-Reviewed Original ResearchClinical criteria to exclude acute vascular pathology on CT angiogram in patients with dizziness
Tu L, Malhotra A, Venkatesh A, Taylor R, Sheth K, Yaesoubi R, Forman H, Sureshanand S, Navaratnam D. Clinical criteria to exclude acute vascular pathology on CT angiogram in patients with dizziness. PLOS ONE 2023, 18: e0280752. PMID: 36893103, PMCID: PMC9997874, DOI: 10.1371/journal.pone.0280752.Peer-Reviewed Original ResearchConceptsAcute vascular pathologyEmergency departmentVascular pathologyNegative predictive valueDizzy patientsStroke codeCTA headPredictive valueAdult ED encountersTransient ischemic attackHalf of patientsLong-term smokersLarge vessel occlusionCoronary artery diseasePast medical historySeparate validation cohortCross-sectional analysisIschemic attackAnalysis cohortArterial dissectionArtery diseaseClinical factorsED encountersMedication useChief complaintAutomatable end‐of‐life screening for older adults in the emergency department using electronic health records
Haimovich A, Xu W, Wei A, Schonberg M, Hwang U, Taylor R. Automatable end‐of‐life screening for older adults in the emergency department using electronic health records. Journal Of The American Geriatrics Society 2023, 71: 1829-1839. PMID: 36744550, PMCID: PMC10258151, DOI: 10.1111/jgs.18262.Peer-Reviewed Original ResearchConceptsAdvance care planningDecision curve analysisLife screeningComorbidity indexCode statusPrognostic modelHealth systemOlder adultsCurve analysisOlder ED patientsPalliative care interventionsObservational cohort studyEmergency department visitsPalliative care servicesElixhauser Comorbidity IndexReceiver-operating characteristic curveIdentification of patientsMultivariable logistic regressionLarge regional health systemLife-limiting illnessRisk older adultsCode status ordersLife Screening ToolMortality predictive modelsElectronic health records
2021
Machine Learning in Emergency Medicine: Keys to Future Success
Taylor RA, Haimovich AD. Machine Learning in Emergency Medicine: Keys to Future Success. Academic Emergency Medicine 2021, 28: 263-267. PMID: 33277733, DOI: 10.1111/acem.14189.Peer-Reviewed Original Research
2018
Physical Restraint Use in Adult Patients Presenting to a General Emergency Department
Wong AH, Taylor RA, Ray JM, Bernstein SL. Physical Restraint Use in Adult Patients Presenting to a General Emergency Department. Annals Of Emergency Medicine 2018, 73: 183-192. PMID: 30119940, DOI: 10.1016/j.annemergmed.2018.06.020.Peer-Reviewed Original ResearchConceptsPhysical restraint useEmergency departmentRestraint ordersRestraint usePhysical restraintDrug useRegional health systemManagement of behavioral disordersAdult emergency departmentPrevent self-harmCross-sectional studyPrevalence of agitationCross-sectional study of adult patientsAssociation of alcoholAdult patientsGeneral EDHealth systemED visitsManaging agitationMedical complaintsStudy of adult patientsVulnerable populationsSelf-harmUnique patientsTotal ED visitsPredicting urinary tract infections in the emergency department with machine learning
Taylor RA, Moore CL, Cheung KH, Brandt C. Predicting urinary tract infections in the emergency department with machine learning. PLOS ONE 2018, 13: e0194085. PMID: 29513742, PMCID: PMC5841824, DOI: 10.1371/journal.pone.0194085.Peer-Reviewed Original ResearchConceptsExtreme gradient boostingGradient boostingXGBoost modelLarge diverse setHigh diagnostic error rateMachineAlgorithmXGBoostError rateDiverse setInadequate diagnostic performancePredictive modelSetPrediction toolsDiagnostic error rateBoostingCommon emergency department (ED) diagnosisFull setModelApplying advanced analytics to guide emergency department operational decisions: A proof-of-concept study examining the effects of boarding
Taylor R, Venkatesh A, Parwani V, Chekijian S, Shapiro M, Oh A, Harriman D, Tarabar A, Ulrich A. Applying advanced analytics to guide emergency department operational decisions: A proof-of-concept study examining the effects of boarding. The American Journal Of Emergency Medicine 2018, 36: 1534-1539. PMID: 29310983, DOI: 10.1016/j.ajem.2018.01.011.Peer-Reviewed Original Research
2017
Agreement Between Serum Assays Performed in ED Point-of-Care and Hospital Central Laboratories
Dashevsky M, Bernstein SL, Barsky CL, Taylor RA. Agreement Between Serum Assays Performed in ED Point-of-Care and Hospital Central Laboratories. Western Journal Of Emergency Medicine 2017, 18: 403-409. PMID: 28435491, PMCID: PMC5391890, DOI: 10.5811/westjem.2017.1.30532.Peer-Reviewed Original ResearchMeSH KeywordsAdultBiological AssayBiomarkersBlood Chemical AnalysisBlood Urea NitrogenCost-Benefit AnalysisCreatinineEmergency Medical ServicesFemaleHumansLaboratories, HospitalMaleMiddle AgedPoint-of-Care SystemsPotassiumQuality Assurance, Health CareReproducibility of ResultsRetrospective StudiesSodiumUnited StatesConceptsHospital central laboratoryBlood urea nitrogenEmergency departmentED patientsCentral laboratoryLevel of agreementBlood samplesClinical information systemsConfidence intervalsLevel I emergency departmentShorter ED lengthPatient/yearHospital's clinical information systemTime-sensitive diagnosisBland-Altman plotsED lengthSerum sodiumClinical criteriaLarge cohortSerum assaysUrea nitrogenClinical judgmentPatientsSerum samplesED point
2016
Use of Point‐of‐Care Ultrasound in the Emergency Department
Hall MK, Hall J, Gross CP, Harish NJ, Liu R, Maroongroge S, Moore CL, Raio CC, Taylor RA. Use of Point‐of‐Care Ultrasound in the Emergency Department. Journal Of Ultrasound In Medicine 2016, 35: 2467-2474. PMID: 27698180, DOI: 10.7863/ultra.16.01041.Peer-Reviewed Original ResearchConceptsCare ultrasoundEmergency departmentOdds ratioHealthcare Common Procedure Coding System codesMedicaid Services feeCare ultrasound useEmergency medicine practitionersMedical school graduation yearUse of pointPatient outcomesUltrasound examinationMedicare beneficiariesEM residenciesMedicare Part B feeUltrasound useMedicine practitionersPart B feePractice locationProvider UtilizationB feeService reimbursementEM practitionersReimbursementUltrasoundLower ratesDetermination of a Testing Threshold for Lumbar Puncture in the Diagnosis of Subarachnoid Hemorrhage after a Negative Head Computed Tomography: A Decision Analysis
Taylor RA, Gill H, Marcolini EG, Meyers HP, Faust JS, Newman DH. Determination of a Testing Threshold for Lumbar Puncture in the Diagnosis of Subarachnoid Hemorrhage after a Negative Head Computed Tomography: A Decision Analysis. Academic Emergency Medicine 2016, 23: 1119-1127. PMID: 27378053, DOI: 10.1111/acem.13042.Peer-Reviewed Original ResearchConceptsProbabilistic sensitivity analysesNegative head CTAneurysmal subarachnoid hemorrhageSubarachnoid hemorrhageLumbar punctureNegative CTTesting thresholdHead CTNormal neurologic findingsContrast-induced nephropathyNonaneurysmal subarachnoid hemorrhageLong-term morbidityHead Computed TomographyTwo-way sensitivity analysesDecision analytic modelProbability of deathNeurologic findingsRenal failureClinical variablesCurrent guidelinesPretest probabilityComputed tomographySecondary aimCTHemorrhageThe Association Between Physician Empathy and Variation in Imaging Use
Melnick ER, O'Brien EG, Kovalerchik O, Fleischman W, Venkatesh AK, Taylor RA. The Association Between Physician Empathy and Variation in Imaging Use. Academic Emergency Medicine 2016, 23: 895-904. PMID: 27343485, PMCID: PMC5884096, DOI: 10.1111/acem.13017.Peer-Reviewed Original ResearchConceptsCT utilizationEmergency physician performanceEmergency physiciansPhysician performanceCT utilization ratesEmergency Department CTPhysician survey respondentsPatient-level variablesCross-sectional studyCohort of physiciansPhysician empathyLarge health systemPsychometric testsMixed effects regression modelsPhysician-based factorsPsychometric scalesSurvey response rateAcademic EDSubset analysisPhysician demographicsHead CTInterphysician variationResponse rateImaging useRTS score