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Equity and Data Prediction

It will not be news to you that equity is a big issue in health data. There is a lot of prediction and analysis going on in the health sector right now and some of it is very biased around issues of race, gender, ethnic origin and class. And when it comes to health this is sometimes a matter of life and death. What practical steps can we take to address this? How can we work to ensure that people get the services they need, especially where that need is compounded by systemic inequities? How can avoid the pitfalls of either systematically either targeting or ignoring demographic groups in inequitable ways?

We're very excited to have Shannon Mickelson Campbell as this week's guest author talking about the steps she and her team are taking towards equity with data in the health sector. Shannon is the senior research and evaluation analyst for the Mental Health and Addiction Services Division at the Multnomah County Health Department in Portland, Oregon.

Read the full post here.
New Support for Equitable Data in Health
For those of you pushing to increase your organization's data equity around health, check out this robust piece of policy that can help you persuade your colleagues and get the resources needed.

This month the American Academy of Pediatrics put out its first policy statement on how racism affects the health and development of children and adolescents. The full statement is here. In the policy statement, they outline the details of the multitude of ways that racism is impacting the health of children right from the womb. In addition, the Academy is starting to publish guidelines on how to deal with this in medical situations. Let's use this clear statement to build support for conducting equity audits in all our health data and embedding equity measures in the analysis.
Improving the way we communicate health outcomes
One of the first things we can do to increase equity in health data is to look at the way we communicate about health outcomes. What about the difference between "Native American heritage is associated with increased risk of obesity." and "Living with the effects of colonialism is associated with increased risk of obesity."

The American Academy of Pediatrics statement we looked at above is a good example too. "Racism is a Core Determinant of Child Health" is very very different than the way we often hear it reported in the past, something along the lines of "Race is a Core Determinant of Child Health".

It makes quite the difference to communicate data findings with a different locus of agency or placement of causality. We're putting together a bunch of new resources on communicating data from an equity lens. They'll be ready in a few weeks and we'd love to hear from you before then if you have something you'd like us to add or share.

Two people I have learned a lot from on this particular topic are Dr. Onye Nnorom (@OnyeActiveMD) who works in Toronto as a physician, is the Black Health Theme Lead for the Faculty of Medicine at the University of Toronto and gives talks about racism and health. And Brittany Wenniseri:iostha Jock, PhD (@Wenniseriiostha) and Indigenous Researcher at Johns Hopkins School of Public Health who gave some excellent examples and guidance on a recent podcast with Jonathan Van Ness.  
Want to hang out IRL?

The We All Count team will be on the road this fall. We'd love to meet you in person. You can find us onstage at:
 
Consultation Chicago, September 9-13
Knack Collective Seattle, October 2
Women in Data Science Conference in Seattle, October 3-5
Notre Dame University Keough School of Global Affairs, October 10-31
The Social Finance Conference in Toronto, November 6-8
The AEA Conference in Minneapolis, November 11-15
Tableau Conference in Las Vegas, November 12-13
Ontario Non-Profit Network Conference, November 27-28
Canadian Evaluation Society, BC Chapter, January 24-25
University of Miami Symposium on Ethics in Technology, Data Science, and Visualization, February 14
Conference on Statistical Practice in Sacramento, Feb 20-22


If you're in the area and would like to host a workshop, a lunch and learn, or a tea party let us know. We'd love to meet you and your team.
 

We're looking for equity problems and successes.

If you have a story or idea you want to share, send me a note by replying to this email.

Project for Equity in Data Science
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