The Role of Algorithms in Advancing Black Health
How to Ensure Health Equity Organizations Use Tech For Good
In an era where algorithms increasingly shape our healthcare decisions, their role in advancing Black health cannot be overstated. While algorithms can potentially enhance medical care, they also risk perpetuating existing disparities if not carefully managed. A striking example is how algorithms assessing kidney transplant viability have historically undervalued kidneys from Black donors, leading to inequitable treatment outcomes. Hence, it’s become even more pertinent to ensure that health equity organizations use technology for patients' good. Therefore, algorithms must serve as tools for progress, not additional barriers to achieving health equity.
Just as there has been a push for “Responsible AI,” I argue that we need that same focus on “Responsible Algorithms.” By this, I mean that algorithm design needs more intentionality, especially in healthcare. Due to unrepresentative datasets or flawed information, bias can be unknowingly built into the algorithms, potentially impacting clinical decision-making. Therefore, being mindful of how data is collected, used, and tested is essential when designing algorithms.
Ensuring Algorithms Advance Rather Than Harm Black Health
When used intentionally, algorithms in healthcare can optimize decision-making and improve patient outcomes. However, without rigorous oversight, these systems can unintentionally reinforce disparities. That’s why healthcare equity organizations and providers, in general, must ensure that the algorithms they’re designing aren’t perpetuating the inequalities they focus on combating.
Here’s how we can ensure algorithms play a positive role in advancing Black health:
1. Data Inclusivity and Representation
Algorithms are only as practical as the data they use. To avoid perpetuating disparities, it’s essential to include diverse data that accurately represents Black patients. This means gathering comprehensive data from varied populations and ensuring that algorithms are trained on this diverse dataset to avoid biased outcomes. If data isn’t available, it’s even more critical that we advocate for more inclusive research of diverse populations. Without the research, we cannot draw helpful insights that include the most marginalized and underserved populations.
2. Addressing Algorithmic Bias
Algorithms that assess risks and outcomes must be scrutinized for potential biases. For example, algorithms that inaccurately predict the success rates of kidney transplants from Black donors can lead to unjust transplant denials. This is why we must regularly review and update algorithms to eliminate biases. Even though “this is the way things have been done,” it doesn’t mean that this is the way that we should continue doing things. Ensuring equitable treatment of all patients requires acknowledging and addressing algorithmic bias.
3. Transparency and Accountability
Transparency in algorithmic decision-making processes helps build trust and allows for better oversight. Clear documentation on how algorithms make decisions and involve feedback from diverse stakeholders can help identify and rectify biases. I will take it a step further and say that training to rectify biases is vital as identifying harm is one step, but rectifying it is another. To rebuild the trust that has been sadly lost in our healthcare system, we must establish accountability mechanisms to ensure algorithms are continually evaluated. By doing so, healthcare organizations and providers can promote fairness while keeping themselves accountable for transparency in decision-making.
4. Ethical Algorithm Design
Ethics in medicine is critical, so it should be considered when developing and deploying healthcare algorithms. Ethical considerations entail engaging diverse teams in the design process to address potential disparities and ensure that algorithms are tested across different populations before implementation. That last part is the most important, as you don’t want to implement a process with an inherent design bias. This helps prevent losing trust and unintentionally exacerbating health disparities.
5. Ongoing Education and Training
As a healthcare educator, I would be remiss if I didn’t mention the importance of ensuring healthcare professionals understand and address algorithmic biases. This includes training on the ethical use of algorithms, recognizing potential biases, and implementing best practices to ensure algorithms contribute positively to patient care. Whether designing or utilizing algorithms, don’t underestimate the importance of educating yourself on the essentials. Doing so can ensure that your algorithm does not harm.
By addressing these key areas, healthcare organizations can leverage algorithms to support, rather than hinder, Black health. Implementing these strategies will help ensure that technological advancements translate into real-world patient benefits.
The role of algorithms in healthcare is evolving, and they must advance health equity for Black patients. Your organization can use algorithms for equitable care by focusing on data inclusivity, addressing biases, ensuring transparency, guiding ethical design, and fostering ongoing education.
Ready to transform your healthcare delivery and improve patient outcomes? Book a consultation today to learn how we can help your organization implement strategies for responsible algorithmic decision-making. We can ensure that technology supports health equity and enhances patient care.
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Thank you for your commitment to advancing Black health and for being part of this critical conversation. Let’s continue working together to create a more equitable healthcare system.
Warm regards,
Tomesha R. Campbell, MA
Enhance Black Women's Health