Lessons learned in the collection of disaggregated ethno-racial data

COVID-19’s disproportionate impact on racialized groups in Canada has catalyzed calls for the systematic collection of data disaggregated by race, a critical step in understanding inequities and developing policy decisions to address them.

Canada’s Chief Public Health Officer and British Columbia’s Human Rights Commissioner have emphasized the need for such data. Organizations like the Canadian Institute for Health Information (CIHI) have proposed data standards for the collection of race-based data. However, in our experience, many health and social organizations across the country still require the needed implementation tools to collect the data effectively, meaningfully and in a culturally safe way.

Five key lessons were learned from the collection of disaggregated ethno-racial data for COVID-19 case management (contact tracing) in Fraser Health, British Columbia’s largest regional health authority.

#1: Link the collection of race-based data to strategic organizational goals

With 42 per cent of people identifying as a member of a visible minority and 48 per cent of newcomers to B.C. initially settling here, the Fraser Health region is one of the most ethno-racially diverse in the province. 

Preliminary data from our contact tracing activities suggested a disproportionate impact of COVID-19 on racialized groups. We linked the subsequent collection of race-based data to the larger regional health authority corporate priorities of “embedding cultural safety and humility” and “strengthening pandemic preparedness and response.” This helped ensure regional health authority executive supports and provides resources for the project despite other organizational priorities during the pandemic.

#2: Ensure the data collected will be meaningful to local communities

Data standards are helpful for standardizing the collection, interpretation and evaluation of data especially for cross-jurisdictional comparisons; however, the categories may not be particularly meaningful at a local level based on the ethno-racial makeup of geographic communities served by an organization. For instance, census data demonstrate that 16.1 per cent of people in our region identify as South Asian and that there are several different ethnic groups encompassed under this term. Consultation with local community groups to validate the categories used by CIHI helped ensure the data would be meaningful to local groups. Through this, we produced data elements that were contextually relevant. For example, additional prompts were included to the “South Asian” option (e.g., Indo-Caribbean, Maldivian, Nepalese) to help clients navigate what group they identified with. Attention to the crafting of local data elements helped balance local needs while ensuring standardization and the ability for cross-jurisdictional comparison.

#3: Acknowledge discomfort and invest in staff training

Routine collection of self-reported Indigenous status is an established practice among our teams and public health staff across B.C. Staff members regularly undergo training so that they can ask questions in a culturally safe manner. We incorporated the principles of this training given that it was already a familiar practice. We recognized that some staff would feel uncomfortable asking about ethno-racial identity and that some may feel uncomfortable answering these questions. We spoke with colleagues in other provinces who had implemented the collection of race-based data and learned that the comfort level of staff in asking questions about race directly affected the comfort level of clients in answering questions. When staff members were comfortable with asking about race, clients felt more comfortable sharing information.

Therefore, we developed specific staff training webinars to foster competency and sensitivity when asking about racial identity. These sessions described the rationale for why these data were gathered, how staff could support clients in answering these questions (both with respect to comfort and interpretation), how the data would be used and counselling points that assured clients their responses would not affect the level of care and service they received. These sessions helped ensure questions were asked appropriately. Relative to other jurisdictions collecting these data, we observed high completion rates for these data fields. Despite this work being rolled out during the “third wave” when COVID-19 case volume was very high, staff asked about race 92 per cent of the time and, in the initial implementation phase, 84.5 per cent of clients who were asked were willing to answer the question. Situations for when a staff member did not ask about race included when the client interview ended prematurely (e.g., the client felt too unwell to continue with the interview), if the interview question was missed by a staff member, or a response was not recorded in the electronic health record.

#4: Involve analytics and informatics teams early

During the pandemic, there has been a substantial demand placed on our analytics and informatics teams to update electronic clinical information systems and to report on various aspects of the pandemic. Early involvement of our clinical informatics teams ensured that electronic fields for collection, entry, interpretation and evaluation of race-based data would be expedited. Also, our analytics team helped map what analyses would be possible and the types of data outputs that could be developed to help inform conversations with community groups and policymakers. The early involvement of these teams expedited discussions, averted delays with clinical information systems and accelerated the development of early data products.

#5: Persistently seek opportunities to mobilize data into action

Not surprisingly, we found that racialized groups were disproportionately represented among COVID-19 cases in our health region. While South Asian groups were the largest number of cases from a racialized group in the region, similar levels of disproportionate representation were observed among other communities like Black, Latino, Southeast Asian and Middle Eastern groups who had not been part of our early COVID-19 outreach strategies. These data helped underscore the need for targeted communications, translation of communications and outreach (for COVID-19 response but also for COVID-19 vaccination) so that we could be responsive to the needs of these communities.

And we continue learning. An area of ongoing development for us is data governance. In particular, how can we extend the Indigenous data stewardship principles of ownership, collection, access and possession to race-based data? In addition, we continue to explore best practices for mobilizing data so that we can empower communities to take action.

Health and social organizations need thoughtfully developed implementation tools to ensure data collection is linked to local communities, engages staff and clients and is effectively mobilized and governed. These tools will need the collaborative efforts of academics, community groups, data organizations, policy makers and others so that the data are collected safely, meaningfully and in ways to combat identified inequities. 

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Aamir Bharmal


Aamir Bharmal is a medical health officer with Fraser Health and a clinical assistant professor at the School of Population and Public Health at the University of British Columbia.

Tannis Cheadle


Tannis Cheadle is a policy analyst with the Health Equity and Population Health Unit at Fraser Health.

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