🎙️ Voice is AI-generated. Inconsistencies may occur.
Health care has long been marked by disparities that affect different groups of people in various ways. Whether due to race, income, or geography, these disparities lead to unequal access to care and varying health outcomes. However, there is growing hope that artificial intelligence (AI) could be the tool we need to address these long-standing issues and create a more equitable health care system for all.
Quality of care shouldn't be influenced by external factors like a patient's background or where they live. Instead, everyone could receive a treatment plan tailored to their unique health needs, informed by a deep understanding of their genetic makeup, medical history, and lifestyle. AI offers the potential to turn this vision into reality by enhancing the precision and personalization of health care.
The problem of health care inequality is multifaceted. Minority groups often experience poorer health outcomes, not because of inherent biological differences, but due to systemic barriers such as underrepresentation in clinical trials and limited access to quality care. For instance, African American women are statistically three to four times more likely to die from pregnancy-related complications than their white counterparts, as highlighted in a study published in The Lancet in 2019. AI, when properly implemented, can help overcome these challenges by providing data-driven insights that lead to more effective interventions.
AI's ability to analyze vast amounts of data quickly and accurately is one of its greatest strengths. By examining electronic health records (EHRs), genetic information, and even social factors, AI can identify patterns that might go unnoticed by human doctors. For example, AI can detect early signs of chronic conditions like diabetes, which disproportionately affects certain minority groups. The Centers for Disease Control and Prevention (CDC) reported that non-Hispanic Black adults (12.1 percent), adults of Hispanic origin (11.7 percent), and non-Hispanic Asian adults (9.1 percent), have diabetes at higher rates compared to non-Hispanic white adults (6.9 percent).
Moreover, AI can help correct biases that have historically influenced medical research and treatment. For example, a study found that AI models trained on diverse datasets, including data from different racial and ethnic groups, performed better across various populations than models trained on less diverse datasets. This suggests that incorporating diverse data can significantly improve the accuracy and effectiveness of AI in health care.
This isn't just about expanding the scope of research—it's about improving the scientific foundation of medicine. To effectively treat diseases, it's essential to understand how they manifest in different populations. AI has the potential to make medical research more inclusive, ultimately leading to better health outcomes for everyone.
Geographic location plays a significant role in health care access. Rural areas, where many minority groups live, often lack the health care resources available in urban centers. According to the National Rural Health Association, the number of primary care physicians per capita is significantly lower in rural areas—39.8 per 100,000 people—compared to cities, where there are 53.3 per 100,000. Specialists are even rarer, and the nearest hospital might be hours away. Telemedicine, powered by AI, can help bridge this gap by enabling remote consultations and diagnostics.
AI tools can assist in diagnosing conditions, recommending treatments, and monitoring chronic diseases, making high-quality care more accessible to those living in remote areas. A study published in JAMA Internal Medicine in 2021 found that telemedicine visits increased by 154 percent during the COVID-19 pandemic, demonstrating the potential of this technology to reach underserved populations.
Additionally, AI can address language barriers that often complicate medical care for non-English-speaking patients. Natural language processing (NLP) algorithms can translate medical information in real-time, ensuring that patients fully understand their diagnoses and treatment options. According to the U.S. Census Bureau, more than 25 million people in the U.S. speak English "less than very well," which can lead to miscommunication in health care settings. AI's ability to provide accurate translations can improve health outcomes and enhance patient satisfaction.
If an AI system suggests a particular treatment plan, it's essential that the health care provider can understand and explain the rationale behind the recommendation. This transparency is vital not only for ethical reasons but also for ensuring that patients receive care they can trust. By making AI systems explainable, health care providers can make better-informed decisions and build trust with their patients.
AI can analyze data to identify communities at higher risk for certain health conditions due to environmental factors, access to nutritious food, or housing conditions. A study by the American Journal of Public Health found that addressing social determinants of health could reduce health disparities by up to 70 percent. A 2021 study published in Health Affairs found that culturally tailored health interventions led to better health outcomes in minority populations compared to standard approaches.
AI is a powerful tool that can help us make meaningful progress. To fully leverage its potential, AI must be developed and used ethically, with a focus on explainability and alignment to the patient experience.
Zack Kass is former head of go-to-market at OpenAI.
The views expressed in this article are the writer's own.
