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There’s no health data available by race, ethnicity or language in the health system in Nova Scotia

Even though MSI was supposed to start working on it back in 2006.

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Sharon Davis-Murdoch, co-president and founding member of the Health Association of African Canadians, says health data is not available by race, ethnicity or language in Canada’s health system. “There is research, but that is different from data,” says Davis-Murdoch. 

She and HAAC have long been advocating for the need for race-based health data in Nova Scotia. They made some recommendations and guidelines for MSI, Nova Scotia’s health insurer, way back in 2006. These guidelines were accepted by the department of health and wellness, “but action to collect MSI data by race, ethnicity and language is still in process,” Davis-Murdoch says.

Having data by race, ethnicity and language allows health leadership to make informed decisions that will support equitable health outcomes, as race-based data is not enough. This kind of data about maternal health in the US–the finding that women of colour are more likely to die during pregnancy and childbirth than white women–has led to policy decisions and public pressure to make changes. Davis-Murdoch says HAAC has never asked for only race-based data, but also ethnicity- and language-based data. “One racialized group does not encompass everybody who is brown or everybody who is Black.” 

Davis-Murdoch says although Black people are “descendants of Mother Africa,” they are of different ethnicities. “We are not a homogenous population, we’re a heterogeneous population,” she says, adding that those who have just arrived in Nova Scotia have a different lived experience from those who have been living in the province for centuries.

David Haase, a retired infectious diseases and internal medicine specialist and a member of the Health Association of African Canadians, agrees with her. He says as the COVID-19 pandemic progressed in Canada, it became apparent how disproportionately effected racialized groups were. He says a few of the provinces have started collecting the data.

Health Canada is recommending that the provinces prioritize racialized people when administering the vaccine. But Haase says despite the advice that African Nova Scotians be given priority access to the C19 vaccine, there’s still an issue of mistrust in the healthcare system. “There has to be a measured approach and a strategy in terms of how the vaccine is delivered to these communities and how the messaging is delivered and what messaging is delivered to these communities to overcome that mistrust.” Hasse says HAAC has been working with the department of health and wellness and vaccine task force strategizing on how to make this happen for the Black community.

For its part, the province told The Coast: “We are working closely with leaders in African Nova Scotian communities to determine how best to support access to the vaccine in these communities and ensure it is being offered in a culturally responsive way.”

Back when COVID-19 first hit the world and rumours of all kinds were swirling, one piece of misinformation suggested that Black people were immune to the virus. “Not only were we not immune, but we were disproportionately effected,” says Davis-Murdoch. (The City of Toronto has been releasing its own race-based pandemic data showing this; Nova Scotia has not provided such detailed data.) 

There are two ongoing studies in Nova Scotia related to C19 and race or ethnicity and language—Ingrid Waldron’s clinical services, health promotion and collection of disaggregated race-based health data study, and OmiSoore Dryden’s “Don’t Count Us Out!” research. Both researchers said they were unavailable for interviews with The Coast.

HAAC has been hosting town halls to help Black communities answer some of the impending questions they have, like the safety and the side effects of the vaccine. Davis-Murdoch says she’s proud of how people of African descent have responded and collaborated around C19 and vaccination, and she encourages Black people to self-identify when race, ethnicity and language data is being collected.

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