‘Inclusive design’ needed if technology is to improve, not worsen, health disparities

‘Inclusive design’ needed if technology is to improve, not worsen, health disparities

September 25, 2024

3 min read


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Key takeaways:

  • Technological advancements in cardiology and other health specialties may amplify existing disparities.
  • To prevent that, technologies must be designed with data drawn from diverse populations.

Health care has experienced a wave of technological advancements — such as AI, machine learning and wearables — in recent years, but if unchecked, they may exacerbate existing disparities in treatment and care.

At HRX 2024, the Heart Rhythm Society’s meeting on digital health advancements, experts conducted a session on ethical concerns about digital technologies being used in cardiovascular care, and shared ideas about solutions that could improve health disparities.



Graphical depiction of source quote presented in the article



Healio spoke to one panelist, Aubrey J. Grant, MD, FACC, sports cardiologist at MedStar Union Memorial Hospital in Baltimore and MedStar Health at Lafayette Centre in Washington, D.C., and co-founder and chief equity officer of Equity Commons, a firm that offers virtual reality training solutions to reduce implicit bias, about how technology can widen biases and equity gaps, how improving diversity in data gathering can mitigate those problems and the commitments required to ensure technology promotes health equity.

Healio: What are some examples of recent technological advancements that have put stresses on equity in health care?
Technological advancements like AI-driven diagnostics, digital health platforms and telemedicine have expanded access to care, but they also amplify existing disparities. For example, rural communities and low-income populations may struggle with internet access, preventing full utilization of telemedicine. AI models trained on nondiverse datasets often misrepresent marginalized populations, leading to suboptimal care. These innovations, while promising, can widen the equity gap if not implemented with a focus on inclusivity.

Healio: What are some of the concerns related to AI and machine learning?
Grant: A primary concern is the risk of bias in AI algorithms. If training data lack diversity, AI models can produce inaccurate or harmful outcomes, particularly for racial and ethnic minorities. Additionally, the “black box” nature of machine learning makes it difficult for clinicians to understand and trust AI decisions. Without proper transparency, validation and accountability, AI risks perpetuating inequities in diagnosis and treatment decisions, especially for underrepresented groups.

Healio: What are some of the concerns related to wearables?
Grant: Wearables, though transformative in monitoring health, often exacerbate disparities. These devices are more accessible to higher-income populations, leaving underserved communities with limited access to the health benefits they provide. Moreover, wearables tend to perform less accurately on individuals with darker skin tones, a technical limitation that can lead to misinterpretation of health data. This lack of inclusivity in device design could unintentionally harm patient outcomes.

Healio: What are some of the potential solutions to health equity challenges in this new era of technology?
Grant: A core solution is ensuring diversity in the data used to develop AI, wearables and other technologies. Stakeholders should prioritize inclusive design by incorporating input from racially, ethnically and socioeconomically diverse populations. Collaboration with community leaders and leveraging social determinants of health in tech design can also bridge gaps. Finally, establishing regulatory standards for fairness in technology will promote equity and ensure that advancements improve care for all.

Healio: What needs to be done to implement these solutions?
Grant: We need top-down support from health care institutions and policymakers to prioritize equity-driven innovation. Standardizing diverse data collection, providing financial incentives for equitable tech development, and establishing clear guidelines for transparency and accountability in AI and wearables are essential steps. Equally important is fostering diversity within development teams to ensure that new technologies reflect the needs of all patients, especially the most vulnerable.

Healio: What were some of the other important insights learned from this session at HRX?
Grant: One key insight was the importance of having a diverse team from the start of technological development to prevent bias from being embedded into solutions. The session also emphasized that the pursuit of equity in health care innovation requires long-term commitment, both in leadership and in how we approach the integration of technology. This isn’t just a technological issue — it’s an ethical one, demanding accountability and inclusivity at every level.

Healio: Is there anything else you would like to mention?
Grant: The integration of technology into health care is inevitable, but it’s our responsibility to ensure that these tools uplift all populations, not just the privileged. We have a unique opportunity in this era of rapid innovation to address long-standing disparities and create a more equitable health care system. It requires a concerted effort, from engineers to policymakers, to ensure technology promotes health equity.

Reference:

  • Grant A, et al. Ensuring techquity in healthcare innovation and implementation: Challenges & opportunities. Presented at: HRX 2024; Sept. 5-7, 2024; Atlanta.

For more information:

Aubrey J. Grant, MD, FACC, can be reached at [email protected]; X (Twitter): @aubjgrantmd.

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