Using Race & Ethnicity Data To Address Health Equity

Greeting Stewards, 

In case you missed it, last week's blog was a brief explanation of the difference between the term  health equity and health equality. In that same blog, we mentioned that in order to reach a healthcare system that is suitable for everyone and anyone, it is important that we reduce health disparities to reach health equity.

In relation to this important topic, we’re glad to share that health leaders in Arizona are currently using data collection on race and ethnicity to address health equity! With the aid of artificial intelligence (AI), the Arizona Department of Health Services (ADHS) is extracting data to identify and match individuals from different databases. 

Earlier this year, Matthew Isiogu, the chief revenue officer of Contexture (the major health information exchange in Arizona and Colorado) was in a meeting where he noticed that the demographics portion of when upon registering at hospitals were limited. Electronically, people had the option to select one or more races. But on paper, the hospital’s paperwork essentially forced people to only choose one race option, thereby erasing important details regarding race and patient information. 

Isiogu says, “State agencies are being very creative to come up with funding opportunities and strategic alignment across agencies, but it’s just as important—if not more important—that when we are making these decisions, the structure, the data about governments of that data, that we have a diversity of perspectives and representation at the table.” 

We wonder what other interesting ways we might see AI evolve in healthcare and health equity. If you have other examples to share, we’d love to hear about them over on Circle.

Warmly, 

Asheanna