Development of Geriatric Competencies for Emergency Medicine Residents Using an Expert Consensus Process

The emergency department (ED) visit rate for older patients exceeds that of all age groups other than infants. The aging population will increase elder ED patient utilization to 35% to 60% of all visits. Older patients can have complex clinical presentations and be resource-intensive. Evidence indicates that emergency physicians fail to provide consistent high-quality care for elder ED patients, resulting in poor clinical outcomes.The objective was to develop a consensus document, “Geriatric Competencies for Emergency Medicine Residents,” by identified experts. This is a minimum set of behaviorally based performance standards that all residents should be able to demonstrate by completion of their residency training.This consensus-based process utilized an inductive, qualitative, multiphase method to determine the minimum geriatric competencies needed by emergency medicine (EM) residents. Assessments of face validity and reliability were used throughout the project.In Phase I, participants ( n =  363) identified 12 domains and 300 potential competencies. In Phase II, an expert panel ( n =  24) clustered the Phase I responses, resulting in eight domains and 72 competencies. In Phase III, the expert panel reduced the competencies to 26. In Phase IV, analysis of face validity and reliability yielded a 100% consensus for eight domains and 26 competencies. The domains identified were atypical presentation of disease; trauma, including falls; cognitive and behavioral disorders; emergent intervention modifications; medication management; transitions of care; pain management and palliative care; and effect of comorbid conditions.The Geriatric Competencies for EM Residents is a consensus document that can form the basis for EM residency curricula and assessment to meet the demands of our aging population.ACADEMIC EMERGENCY MEDICINE 2010; 17:316–324 © 2010 by the Society for Academic Emergency MedicinePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79220/1/j.1553-2712.2010.00684.x.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/79220/2/ACEM_684_sm_DataSupplementS1.pd