Ryan Brydges1, Victoria A Boyd2, Walter Tavares3, Shiphra Ginsburg4, Ayelet Kuper5, Melanie Anderson6, Lynfa Stroud7. 1. R. Brydges is research director, a scientist, and professor of technology-enabled education, Allan Waters Family Simulation Centre, St. Michael's Hospital, and associate professor, Department of Medicine and Wilson Centre for Research in Education, University of Toronto and University Health Network, Toronto, Ontario, Canada; ORCID: http://orcid.org/0000-0001-5203-7049. 2. V.A. Boyd is a PhD student, Institute of Health Policy, Management and Evaluation, University of Toronto, and a research fellow, Wilson Centre for Research in Education, University of Toronto and University Health Network, Toronto, Ontario, Canada; ORCID: http://orcid.org/0000-0003-3602-8964. 3. W. Tavares is a scientist, Wilson Centre for Research in Education, University of Toronto and University Health Network, and assistant professor, Post MD Education, Department of Medicine, Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; ORCID: http://orcid.org/0000-0001-8267-9448. 4. S. Ginsburg is professor, Department of Medicine, University of Toronto, a scientist, Wilson Centre for Research in Education, University of Toronto and University Health Network, and Canada Research Chair in Health Professions Education, Mt Sinai Hospital, Toronto, Ontario, Canada; ORCID: http://orcid.org/0000-0002-4595-6650. 5. A. Kuper is associate professor and faculty co-lead, Person-Centred Care Education, Department of Medicine, University of Toronto, a scientist and associate director, Wilson Centre for Research in Education, University of Toronto and University Health Network, and a staff physician, Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada; ORCID: http://orcid.org/0000-0001-6399-6958. 6. M. Anderson is an information specialist, University Health Network, Toronto, Ontario, Canada. 7. L. Stroud is associate professor, Department of Medicine, University of Toronto, a Centre researcher, Wilson Centre for Research in Education, University of Toronto and University Health Network, and a staff physician, Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.
Abstract
PURPOSE: As educators have implemented competency-based medical education (CBME) as a framework for training and assessment, they have made decisions based on available evidence and on the medical education community's assumptions about CBME. This critical narrative review aimed to collect, synthesize, and judge the existing evidence underpinning assumptions the community has made about CBME. METHOD: The authors searched Ovid MEDLINE to identify empirical studies published January 2000 to February 2019 reporting on competence, competency, and CBME. The knowledge synthesis focused on "core" assumptions about CBME, selected via a survey of stakeholders who judged 31 previously identified assumptions. The authors judged, independently and in pairs, whether evidence from included studies supported, did not support, or was mixed related to each of the core assumptions. Assumptions were also analyzed to categorize their shared or contrasting purposes and foci. RESULTS: From 8,086 unique articles, the authors reviewed 709 full-text articles and included 189 studies reporting evidence related to 15 core assumptions. Most studies (80%; n = 152) used a quantitative design. Many focused on procedural skills (48%; n = 90) and assessed behavior in clinical settings (37%; n = 69). On aggregate, the studies produced a mixed evidence base, reporting 362 data points related to the core assumptions (169 supportive, 138 not supportive, and 55 mixed). The 31 assumptions were organized into 3 categories: aspirations, conceptualizations, and assessment practices. CONCLUSIONS: The reviewed evidence base is significant but mixed, with limited diversity in research designs and the types of competencies studied. This review pinpoints tensions to resolve (where evidence is mixed) and research questions to ask (where evidence is absent). The findings will help the community make explicit its assumptions about CBME, consider the value of those assumptions, and generate timely research questions to produce evidence about how and why CBME functions (or not).
PURPOSE: As educators have implemented competency-based medical education (CBME) as a framework for training and assessment, they have made decisions based on available evidence and on the medical education community's assumptions about CBME. This critical narrative review aimed to collect, synthesize, and judge the existing evidence underpinning assumptions the community has made about CBME. METHOD: The authors searched Ovid MEDLINE to identify empirical studies published January 2000 to February 2019 reporting on competence, competency, and CBME. The knowledge synthesis focused on "core" assumptions about CBME, selected via a survey of stakeholders who judged 31 previously identified assumptions. The authors judged, independently and in pairs, whether evidence from included studies supported, did not support, or was mixed related to each of the core assumptions. Assumptions were also analyzed to categorize their shared or contrasting purposes and foci. RESULTS: From 8,086 unique articles, the authors reviewed 709 full-text articles and included 189 studies reporting evidence related to 15 core assumptions. Most studies (80%; n = 152) used a quantitative design. Many focused on procedural skills (48%; n = 90) and assessed behavior in clinical settings (37%; n = 69). On aggregate, the studies produced a mixed evidence base, reporting 362 data points related to the core assumptions (169 supportive, 138 not supportive, and 55 mixed). The 31 assumptions were organized into 3 categories: aspirations, conceptualizations, and assessment practices. CONCLUSIONS: The reviewed evidence base is significant but mixed, with limited diversity in research designs and the types of competencies studied. This review pinpoints tensions to resolve (where evidence is mixed) and research questions to ask (where evidence is absent). The findings will help the community make explicit its assumptions about CBME, consider the value of those assumptions, and generate timely research questions to produce evidence about how and why CBME functions (or not).