Infographic: How to Mitigate AI Bias and Reduce Health Disparities


Artificial intelligence (AI) has emerged as a revolutionary force, driving unprecedented advancements in various sectors, including healthcare. However, as these powerful technologies become increasingly prevalent, addressing the growing concern of AI bias and its impact on health disparities is significantly important. Unchecked biases in AI-driven systems can exacerbate existing inequalities, potentially undermining the very essence of equitable healthcare.

This infographic delves into the ways we can effectively mitigate AI bias and reduce health disparities, ensuring that the benefits of these cutting-edge technologies are accessible to all, regardless of race, gender, or socioeconomic status. Join us as we explore practical strategies and solutions to tackle this pressing issue, fostering a more inclusive and fair healthcare system that harnesses the full potential of AI-powered innovations.

how to mitigate ai bias and reduce health disparities

With all the promise of AI on the horizon, healthcare providers need to understand how AI systems can discriminate against people based on factors like race and gender, and how AI can be persuaded to avoid carrying out such discriminatory behaviors. Now more than ever, we need to work together to tackle the issues that AI poses – from the perspective of fairness, equity, and social inclusion.

It's important to remember that AI systems are only as good as the data that goes into them. And the data we have about a person's race, gender, and socioeconomic status is significantly limited. In order to build AI systems capable of accurately reflecting the full diversity of the human experience, we must improve the accuracy of this data – and that means fostering partnerships – both internally and externally – that are actively working to mitigate AI bias and reduce health disparities.

The Actium Health CENTARI Approach 

Actium Health's CENTARI develops a score threshold so that no particular racial group or gender is underrepresented. For example, traditionally, women are underrepresented in cardiology service lines. Therefore, a recent CENTARI model initially identified 60% men and 40% women for outreach in cardiology. 

Using the results of those models without any adjustments would have exacerbated existing disparities in access to cardiac care for women. However, by using score thresholds, CENTARI equalized these percentages. That way, outreach results were adjusted to advance health equity and reduce existing gender disparities in heart care. 

Actium Health leverages AI to transform patient outreach. Provided are some of the ways Actium Health can transform your system or clinic. If you're interested in learning more about Actium Health, request a demo today.

  • Intelligent setup designed to break down data silos
  • Insights tailored to your unique goals
  • Prioritized patient audiences
  • Automated, always-on campaigns
  • Exportable patient lists for one-off campaigns
  • SMS communications that maximize patient activation
  • Outbound calling management to boost call team productivity
  • Dynamic throttling to drive volume where you need it — and avoid overbooking
  • Enhanced reporting and attribution for marketing ROI and direct revenue impact