Medical Council of Canada

PURPOSE:Licensure and certification examinations have traditionally served to ensure physicians possess the knowledge and skills required for independent practice. However, with the growing emphasis on workplace-based assessment, the role and relevance of these point-in-time examinations are increasingly debated. This systematic review aimed to explore the association between physician performance on national licensing and certification examinations and subsequent measures of quality of care in practice. METHOD:The review followed the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines. Six databases were searched through November 2025. Original research studies were included if they examined the relationship between performance on medical licensing or certification examinations and physician performance in independent practice, including patient outcomes and fitness to practice. Data were extracted and analyzed using content analysis to identify patterns and trends across studies. RESULTS:A total of 44 studies involving 1,021,187 physicians were included. The findings demonstrated that examination performance was consistently associated with quality of patient care and fitness-to-practice concerns. Better examination performance was linked to improved adherence to mammography screening recommendations, appropriate prescribing practices, improved care of patients with diabetes, lower patient morbidity and mortality, fewer complaints to regulatory bodies, and lower malpractice payments. The association was observed across examination formats and medical specialties. CONCLUSIONS:The results suggest that national licensing and certification examinations are valuable predictors of future clinical performance. They provide a uniform benchmark to ensure physicians meet rigorously defined criteria. The findings support continued use of these examinations as part of a comprehensive assessment program to promote high-quality patient care and physician competence. This is critical in an era of increased physician mobility, where many physicians have trained in jurisdictions with widely varying curricula and assessment practices. National examinations help ensure that all licensed physicians meet a consistent standard for clinical competence.

This study examined how individual, relational, and organizational factors relate to school belonging in early adolescence. Multilevel models used population-level data from 23,421 Grade 6-8 students in 365 British Columbia schools, with predictors centered within cluster and school means entered at Level 2 to separate within-from between-school associations. Belonging was lower among students in higher grades. Within schools, optimism, connectedness with adults and peers, and low victimization were associated with greater belonging, and adult and peer connectedness interacted. Between schools, school-average connectedness with adults and, especially, school-average victimization showed stronger associations than their within-school counterparts. Students in standalone middle schools reported lower belonging than students in elementary schools, whereas secondary and K-12 settings did not differ, after adjustment for grade, individual characteristics, and relational climate. The model explained 45.6% of within-school and 73% of between-school variance. Findings position belonging as co-constructed by students, school relational climate, and grade-span configuration.

At the foundation of research concerned with professional training is the idea of an assumed causal chain between the policies and practices of education and the eventual behaviours of those that graduate these programs. In medicine, given the social accountability to ensure that teaching and learning gives way to a health human resource that is willing and able to provide the healthcare that patients and communities need, it is of critical importance to generate evidence regarding this causal relationship. One question that medical education scholars ask regularly is the degree to which the unique features of training programs and learning environments impact trainee achievement of the intended learning outcomes. To date, this evidence has been difficult to generate because data pertaining to learners is only rarely systematically brought together across institutions or periods of training. We describe new research which leverages an inter-institutional data-driven approach to investigate the influence of school-level factors on the licensing outcomes of medical students. Specifically, we bring together sociodemographic, admissions, and in-training assessment variables pertaining to medical trainee graduates at each of the six medical schools in Ontario, Canada into multilevel stepwise regression models that determine the degree of association between these variables and graduate performances on the Medical Council of Canada Qualifying Examinations (Part 1, n = 1097 observations; Part 2, n = 616 observations), established predictors of downstream physician performance. As part of this analysis, we include an anonymized school-level (School 1, School 2) independent variable in each of these models. Our results demonstrate that the largest variable associated with performance on both the first and second parts of the licensing examinations is prior academic achievement, notably clerkship performance. Ratings of biomedical knowledge were also significantly associated with the first examination, while clerkship OSCE scores and enrollment in a family medicine residency were significantly associated with the Part 2. Small significant school effects were realized in both models accounting for 4

PURPOSE:In the post-COVID era, recognizing evolving physician competencies is crucial for guiding medical education and test development. This study aimed to extract valuable insights concerning emerging physician competencies from influencers' posts on X, leveraging an AI-driven approach. METHOD:Two datasets pertaining to medical competency were analyzed, with posts collected from January 1, 2020, to June 1, 2023. Social network analyses were performed to identify influencers leading medical competency conversations on X. ChatGPT was utilized for textual analyses of influencers' posts to reveal core themes of physician competencies. RESULTS:Social network analysis revealed that medical professionals played a predominant role in disseminating information on medical competency on X. Textual analysis identified six core themes in the CanMEDS dataset-clinical learning environment, anti-racism, EDI, adaptive expertise, planetary health, and leadership development-and seven in the MedEd dataset-cultural competency, structural competency, assessment models, virtual care, EDI, leadership development, and wellness. CONCLUSION:The identified themes emphasize physicians' competencies in addressing health disparities, preparing for real-world challenges, adapting to the evolving healthcare landscape, and leading effectively in diverse healthcare settings. The findings hold significant implications for medical education, test development, and the integration of artificial intelligence in physician competency assessment.

This paper reports the findings of a Canada based multi-institutional study designed to investigate the relationships between admissions criteria, in-program assessments, and performance on licensing exams. The study's objective is to provide valuable insights for improving educational practices across different institutions. Data were gathered from six medical schools: McMaster University, the Northern Ontario School of Medicine University, Queen's University, University of Ottawa, University of Toronto, and Western University. The dataset includes graduates who undertook the Medical Council of Canada Qualifying Examination Part 1 (MCCQE1) between 2015 and 2017. The data were categorized into five distinct sections: demographic information as well as four matrices: admissions, course performance, objective structured clinical examination (OSCE), and clerkship performance. Common and unique variables were identified through an extensive consensus-building process. Hierarchical linear regression and a manual stepwise variable selection approach were used for analysis. Analyses were performed on data set encompassing graduates of all six medical schools as well as on individual data sets from each school. For the combined data set the final model estimated 32% of the variance in performance on licensing exams, highlighting variables such as Age at Admission, Sex, Biomedical Knowledge, the first post-clerkship OSCE, and a clerkship theta score. Individual school analysis explained 41-60% of the variance in MCCQE1 outcomes, with comparable variables to the analysis from of the combined data set identified as significant independent variables. Therefore, strongly emphasising the need for variety of high-quality assessment on the educational continuum. This study underscores the importance of sharing data to enable educational insights. This study also had its challenges when it came to the access and aggregation of data. As such we advocate for the establishment of a common framework for multi-institutional educational research, facilitating studies and evaluations across diverse institutions. This study demonstrates the scientific potential of collaborative data analysis in enhancing educational outcomes. It offers a deeper understanding of the factors influencing performance on licensure exams and emphasizes the need for addressing data gaps to advance multi-institutional research for educational improvements.