Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions
Taylor R, Sangal R, Smith M, Haimovich A, Rodman A, Iscoe M, Pavuluri S, Rose C, Janke A, Wright D, Socrates V, Declan A. Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions. Academic Emergency Medicine 2024 PMID: 39676165, DOI: 10.1111/acem.15066.Peer-Reviewed Original ResearchClinical decision supportEmergency departmentArtificial intelligencePatient safetyDiagnostic errorsImplementing AIImprove patient safetyClinical decision support systemsEnhance patient outcomesReducing diagnostic errorsLeverage artificial intelligenceEmergency medicineHealth careTargeted educationReduce cognitive loadQuality improvementEmergency cliniciansData retrievalReal-time insightsDecision supportPatient outcomesCognitive overloadInformation-gathering processPatient detailsCliniciansFormative 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