How Can We Fix the System If We Can’t See It? Addressing the Data Gap Facing International Medical Graduates in Canada

Across Canada, patients are waiting weeks, sometimes months, to see a family doctor, while some don’t have access to one at all. Emergency departments are stretched, and rural communities are desperate for healthcare providers. Canada ranks second-last on the Time Saved Index, despite its high health spending. As we head into 2050 with an aging population, thousands of experienced, internationally trained physicians remain sidelined. These International Medical Graduates (IMGs) represent a qualified, willing workforce, but they remain locked out of the system.

A new report by MOSAIC, funded by the World Education Services Mariam Assefa Fund, Using Disaggregated Data to Address the Systemic Discrimination Experienced by International Medical Graduates, helps explain why. The solution, which involves addressing bureaucracy, prejudice, and other barriers, requires a comprehensive understanding of the problem, which is frustrated by an absence of transparent, disaggregated data.

The Missing Data Problem

The MOSAIC report set out to do something simple but essential: identify how different groups of IMGs fare in Canada’s medical licensure system. It focused on four distinct groups: immigrant IMGs (I-IMGs) from approved jurisdictions, I-IMGs from all other countries, Canadians who studied medicine abroad (CSAs), and visa trainees sponsored by foreign governments. But this seemingly basic task proved nearly impossible due to widespread institutional opacity.

Despite requests to multiple institutions, including Canadian Resident Matching Service (CaRMS), the Medical Council of Canada (MCC), Statistics Canada, the Immigrant, Refugees, and Citizenship Canada (IRCC), all provincial and territorial colleges of physicians and surgeons, and the Canadian Post-M.D. Education Registry (CAPER), little useful data, which would enable an understanding of how the different groups fared, was shared. In many cases, institutions refused to disaggregate IMGs into meaningful subgroups or declined to share data.

“Applications for data were rarely straightforward; data requested was consistently unavailable, and communication with the data providers was often challenging,” the report notes.

Disaggregated Data: What’s the Big Deal?

Disaggregated data isn’t just a technical detail. It can allow us to see how the four subgroups of IMGs are treated, including along lines of country of origin, race, training background, and immigration status. Without this, systemic discrimination is hard to prove, and even harder to address.

As the report explains, “We cannot address what we cannot see.” Disaggregated data would allow researchers and policymakers to pinpoint which barriers disproportionately affect which groups. For example, it could illuminate why I-IMGs from non-Western countries are underrepresented in licensed practice, or why visa trainees from Saudi Arabia appear to have more access to specialty training than Canadians trained abroad.

Gatekeepers of Silence

Some of the most influential institutions in medical licensure were unwilling to cooperate. The MCC declined to share record-level data in which each record is related to a single individual because MCC was “not a member of the research.” 

CaRMS, a national organization providing application and match services to medical students and residents for medical training positions throughout Canada, provided aggregate data. This included a number of CMGs, IMGs or USMGs (United States Medical Graduates) who applied to CaRMS, the success rate of matching from 2014 through 2023, and information related to age, sex, citizenship, and quotas for each year.

However, “CaRMS advised that it was not prepared to release self-identified ethnicity data as the Board still wants to further refine the data collection and survey”. It had the ability but chose not to collect and distinguish between CSAs and I-IMGs after 2015, and would not release any of the data that they had that distinguished between them in 2015 and earlier. The report also noted inaccuracies in the data provided: “positions in the second iteration were reported as ‘competitive’ in Ontario, Manitoba, and Alberta in years when they were not”.  

CAPER and CIHI claimed their systems couldn’t differentiate between key subgroups (e.g., CSAs and I-IMGs). “None of the Colleges, except Alberta, released data,” the report notes. The data released by Alberta did not distinguish between subgroups of IMGs. Statistics Canada and IRCC data could not identify physicians who were unemployed or working outside the healthcare system. Even when some data was shared, it came with caveats and gaps that rendered it only marginally useful. 

This institutional silence has real consequences. The report’s authors note: “Each organization defined and collected data differently. As a result, the data remains siloed, and its full potential could not be realized.”

Why This Matters to Canadians

This isn’t just about fairness for IMGs. It’s about the health of every Canadian. When qualified physicians can’t get licensed due to opaque systems and discriminatory structures, everyone loses. Communities remain underserved. Hospitals operate short-staffed. Preventable illnesses go untreated.

And this is not a matter of qualification. Despite passing Canadian licensing exams and bringing years of clinical experience, they are treated as less competent than new Canadian grads, required to repeat training unnecessarily, and restricted to residency positions in lower-paid specializations like medicine, pediatrics, and psychiatry.

Worse, while CSAs and foreign visa trainees have better access to residencies, I-IMGs, many of whom are racialized, are left out. But without data, these disparities cannot be fully exposed.

A Call for Transparency and Change

The MOSAIC report concludes with a clear and reasonable set of recommendations. Chief among them: 

• All institutions involved in the pathways to medical licensure (data sources) must collect and integrate standardized disaggregated data, which is relevant to identify barriers and evaluate outcomes of medical graduates in Canada to licensure and would enable distinction between the four different groups of IMGs.
• All data sources should provide, upon request, anonymized, record-level data to institutions, the public, and equity, diversity and inclusivity (EDI) departments/organizations, including IMG-led and settlement organizations.
• All data sources should integrate, standardize, and cooperate to stop and prevent the continuation of the existing data silos that prevent the analysis of data across data sources.

This is how we evaluate systemic discrimination. This is how we reform.

At a time when health human resources are in crisis and public trust in institutions is fragile, we must demand better. Transparency is not optional. Data is not proprietary. If these institutions are truly working in the public interest, they should welcome scrutiny, not avoid it.

Because ultimately, this isn’t just about numbers. It’s about people, qualified professionals, new Canadians, and patients waiting for care. We need a system that works. And that starts with one that’s visible.