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Executive Summary

Advocates have long called for the collection and responsible use of race-based data in Ontario’s health system. When collected and used in accordance with best practices, race-based data in health can be used to dismantle structural racism:

  • by uncovering inequities,
  • by developing policy and practice to tackle these inequities,
  • by monitoring and evaluating the effectiveness of interventions,
  • by holding authorities accountable for improving outcomes, and
  • ultimately by eliminating structural racism from systems.

The COVID-19 pandemic has amplified existing inequities resulting from anti-Black racism and disproportionately impacted Black communities in Ontario. Black communities experience higher infection rates, worse health outcomes, and more financial distress as a result of layoffs and reduced work hours. Ontario has mandated the collection of race-based data, for COVID-19 cases, and as part of its data collection strategy it has engaged in community consultations. However, Black communities have identified significant concerns with the process as well as who is able to access and use the data. 

The Black Health Equity Working Group, made up of Black health sector leaders and healthequity experts, began meeting early in the pandemic to develop a governance framework for health data collected from Black communities in Ontario. The objective was to address concerns from Black communities about the continued extraction of data from them without the return of tangible benefits. 

After creating a draft framework, the working group carried out a series of stakeholder consultations with Black community members, researchers and academics, public health professionals, and health system organizations in Ontario to gather critical feedback and inform revisions. This report introduces the Engagement, Governance, Access, andProtection (EGAP) Framework, which outlines guiding principles in four areas of focus:

  • ENGAGEMENT: Genuine, cyclical, accessible consultation with communities regarding data collection, management, analysis, and use.
  • GOVERNANCE: Community decision-making about engagement processes and data collection, management, analysis, and use, achieved through the establishment of Community Governance Tables.
  • ACCESS: The right of communities to access their collective data and to determine who else can access it, along with the capacity building required to enable this right. 
  • PROTECTION: The safeguarding of all individual rights and types of data, including identifiable, de-identified, and anonymized data.

The EGAP Framework envisages Black communities gaining control over their collective data. Key to this is the establishment of Community Governance Tables, decision-making bodies on the front lines of building accountability. Community Governance Tables representative of local communities must be developed in various locations across the province. External parties will be required to present plans for community engagement, data collection, data management, data analysis, and data use to the relevant Community Governance Table, which will approve or reject them. Only with approval can the external party proceed with the work. Thus, data stewards and users will be answerableto Black communities through the Community Governance Tables, which can be developed and adapted for different circumstances and organizations.

The principles in the EGAP Framework have relevance beyond the COVID-19 pandemic, and the framework will continue to evolve as a living document. This report outlines steps that are required to implement the framework. It is offered as a starting point for anyone involved in the collection, management, analysis, and use of race-based data for health purposes, including governments and related agencies, health system organizations, research institutes, and community-led organizations. It is also intended for Black community members, who are directly affected by the issues, questions, and recommendations for action raised here.

The collection of race-based data should never be the end goal: it must be used to create pathways for dismantling structural racism and advancing health equity.