What Is the Role of AI in Social Determinants Analysis?

By Rasit Dinc

Introduction

The social determinants of health (SDoH) are the conditions in which people are born, grow, live, work, and age. These circumstances are shaped by the distribution of money, power, and resources at global, national, and local levels. SDoH are mostly responsible for health inequities — the unfair and avoidable differences in health status seen within and between countries. In recent years, artificial intelligence (AI) has emerged as a powerful tool with the potential to revolutionize healthcare. This blog post will explore the role of AI in social determinants analysis, examining its potential to address health disparities and promote health equity.

The Power of AI in SDoH Analysis

AI, particularly machine learning (ML) and natural language processing (NLP), can analyze large and complex datasets related to SDoH with unprecedented speed and accuracy. These technologies can identify patterns, correlations, and predictive factors that may not be apparent through traditional analytical methods. For example, AI algorithms can analyze electronic health records (EHRs), socioeconomic data, environmental data, and even social media data to gain a more comprehensive understanding of the factors that influence health outcomes [1].

By automating the extraction and analysis of SDoH data, AI can significantly reduce the time and resources required for this critical task. This increased efficiency can empower healthcare providers, public health officials, and policymakers to make more informed decisions and develop more effective interventions to address health inequities.

Applications of AI in SDoH

The applications of AI in SDoH are vast and varied. In public health surveillance, AI can be used to monitor disease outbreaks, identify high-risk populations, and predict the spread of infectious diseases [2]. This information can help public health officials to allocate resources more effectively and implement targeted prevention strategies.

In the realm of personalized medicine, AI can help to develop individualized care plans that take into account a patient's unique social and environmental context. By analyzing a patient's SDoH data, AI-powered tools can identify potential barriers to care and recommend tailored interventions to address them. This can lead to improved health outcomes and a more equitable healthcare system.

Furthermore, AI can play a crucial role in informing policy and resource allocation decisions. By providing a deeper understanding of the complex interplay between social factors and health, AI can help policymakers to design more effective social and economic policies that promote health and well-being for all.

Challenges and Ethical Considerations

Despite its immense potential, the use of AI in SDoH analysis also presents a number of challenges and ethical considerations. One of the primary concerns is the potential for algorithmic bias. If AI models are trained on biased data, they can perpetuate and even amplify existing health disparities [3]. It is therefore crucial to ensure that AI systems are developed and validated using diverse and representative datasets.

Data privacy and security are also major concerns. The use of AI in SDoH analysis involves the collection and analysis of large amounts of sensitive personal data. It is essential to have robust data governance frameworks in place to protect patient privacy and prevent the misuse of this information.

Finally, it is important to remember that AI is a tool, and it should not replace the human touch in healthcare. While AI can provide valuable insights and decision support, it is no substitute for the empathy, compassion, and clinical judgment of healthcare professionals.

The Future of AI in SDoH

The future of AI in SDoH is promising. As AI technologies continue to evolve, they will become even more powerful and sophisticated. By leveraging AI responsibly and ethically, we can unlock its full potential to address the social determinants of health and create a more just and equitable world.

Achieving this vision will require a collaborative effort from researchers, policymakers, healthcare professionals, and community members. By working together, we can ensure that AI is used to empower individuals and communities, and to create a future where everyone has the opportunity to achieve their full health potential.

Conclusion

In conclusion, AI has the potential to be a transformative force in the analysis of social determinants of health. By enabling a deeper understanding of the complex factors that influence health, AI can help us to develop more effective interventions, promote health equity, and create a healthier future for all. However, it is crucial to address the challenges and ethical considerations associated with the use of AI in this context to ensure that it is used in a responsible and equitable manner.

References

[1] Davis, V. H., Qiang, J. R., MacCarthy, I. A., Howse, D., Seshie, A. Z., Kosowan, L., ... & Pinto, A. D. (2025). Perspectives on Using Artificial Intelligence to Derive Social Determinants of Health Data From Medical Records in Canada: Large Multijurisdictional Qualitative Study. Journal of Medical Internet Research, 27, e52244.

[2] Panteli, D., Adib, K., Buttigieg, S., Goiana-da-Silva, F., Ladewig, K., Azzopardi-Muscat, N., ... & McKee, M. (2025). Artificial intelligence in public health: promises, challenges, and an agenda for policy makers and public health institutions. The Lancet Public Health, 10(5), e428-e432.

[3] Yelpaala, K., Gibbons, M. C., Vigil, I. M., Leaño, J., McCall, T., Opara, I., ... & Ranney, M. (2025). The Role of Data in Public Health and Health Innovation: Perspectives on Social Determinants of Health, Community-Based Data Approaches, and AI. Journal of Medical Internet Research, 27(10), e78794.