Access and Selection: Canadian Perspectives on Who Will Be Good Doctors and How to Identify Them

Acad Med. 2015 Jul;90(7):946-52. doi: 10.1097/ACM.0000000000000683.


Purpose: How to best select future doctors and the implications of selection for equity and access are timely, relevant, and complex issues that fundamentally affect other aspects of medical education such as curriculum design and social accountability. The authors thus conducted an environmental scan of practices related to access and selection in Canadian medical schools.

Method: The authors drew and built on a literature review, key informant interviews, and expert panel discussions conducted as part of the 2008-2009 Future of Medical Education in Canada project to detail the empirical basis for prioritizing the study of access and selection, the evidence base of current practices, and implications for medical schools.

Results: Data clustered around four principles: (1) selection criteria must address current attributes and future potential, (2) access to medical school and diversity within the class are linked to a school's social accountability framework, (3) sound instruments and protocols are necessary to maximize reliability and validity, and (4) medical schools must be accountable for the effectiveness of their admissions processes. Although initiatives addressing barriers exist, ongoing challenges include recruitment and selection for overall diversity, adoption of better criteria for nonacademic achievement, and empirical validation of selection processes.

Conclusions: Evidence-based selection processes can optimize the provision of broadly competent physicians for a given population. Schools must work to minimize systematic barriers for specific groups. Although this analysis provides a Canadian perspective, the principles and implications are relevant to medical education institutions elsewhere.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Canada
  • Curriculum
  • Education, Medical, Undergraduate / organization & administration*
  • Education, Medical, Undergraduate / statistics & numerical data
  • Humans
  • School Admission Criteria / statistics & numerical data*
  • Schools, Medical / organization & administration*
  • Schools, Medical / statistics & numerical data
  • Social Responsibility