Transforming Maternal Care: The Power of Predictive Analytics in Bridging Black Maternal Health Disparities

Feb 14, 2024 at 11:00 am by steve

By Paris N. Johnson1∗ & Salisha Marryshow-Batson1

School of Public Health, Samford University

*Corresponding author


One of the most critical and deeply rooted issues in healthcare is the disparity in Black maternal health. The statistics reveal a harsh reality: black women in the United States face significantly higher risks of pregnancy-related complications and mortality compared to their white counterparts. Research, including studies by Petersen et al. (2019) and Howell (2018), emphasizes this situation, painting a stark picture of racial inequities that extend beyond numbers to impact real lives and families. Each statistic represents a mother, daughter, partner, or friend, making addressing these disparities with urgency imperative.

Amidst this challenging landscape, predictive analytics emerges as a beacon of hope, providing a strategic tool to promote health equity. By utilizing data from electronic health records, patient surveys, and social determinants of health, predictive models have the potential to identify high-risk pregnancies and facilitate targeted interventions. However, effectively integrating predictive analytics into healthcare is a complex process, as it involves navigating obstacles such as data privacy concerns, algorithmic bias, and the challenge of seamlessly incorporating these technologies into existing healthcare systems.

Black maternal health disparities are being addressed with growing momentum in the medical community. Initiatives led by healthcare professionals like David Jude, MD, FACOG at Marshall University Joan C. Edwards School of Medicine are testament to this progress. These efforts emphasize the critical role of education in equipping the next generation of healthcare providers with the knowledge, empathy, and tools necessary to address these issues. By integrating current research, best practices, and culturally competent care into medical education, Jude is one of many doctors across the nation laying the groundwork for a healthcare workforce that is aware of these disparities and working to eliminate them.

The integration of predictive analytics into maternal healthcare requires a commitment to policy reform and community engagement. It is crucial that we collaborate with communities afflicted by this disparity to ensure that interventions are culturally appropriate and effective, resulting in marked improvements in care. The future of predictive analytics in healthcare is bright with a plethora of advancements ranging from personalized medicine to real-time decision support, signifying a remarkable transformation in healthcare technology. These advancements pledge a more proactive, personalized, and practical approach to healthcare delivery.

As Doctor of Public Health (DrPH) students at Samford University, my cohort Salisha Marryshow-Batson and I embody the intersection of personal experience and academic pursuit. We bonded over our shared experiences of near-fatal postpartum complications and similar cultural heritage, and we share a passion for research and education. Our experiences are not isolated incidents but rather part of a broader narrative that highlights the systemic flaws in maternal healthcare for black women. Our goal is to combine our academic focus on population health and data analytics to advocate for and contribute to a future where predictive analytics and public health strategies work together to achieve health equity.

This passage transcends the boundaries of technology and data. It is an impassioned call for systematic transformation By amplifying the voices of black mothers and harnessing the power of data-driven solutions, we envision a healthcare system that guarantees safe, equitable, and dignified childbirth experiences for all women. Our advocacy for the use of predictive analytics in addressing black maternal health disparities is a step toward not only confronting current inequities, but also forging a future in which every mother, regardless of race, can have a safe and dignified childbirth experience.

The potential of predictive analytics to improve the health of Black mothers is immense. However, achieving this goal requires a collaborative effort across various fields, including advocacy, research, policy, and community engagement. It is a testament to the resilience of communities, the dedication of healthcare professionals, and the spirit of those who refuse to accept the status quo. As we approach a new era in healthcare, let us remain committed to exploring the complexities of predictive analytics, and ensuring it serves as a cornerstone for a healthcare system that values every life it touches. This exploration is not merely theoretical; it’s a crucial step in redefining maternal healthcare for the better. We encourage readers to delve deeper into this critical conversation and join us in championing a future where health equity is a reality for everyone.



  1. Petersen, E. E., Davis, N. L., Goodman, D. A., Cox, S., Syverson, C., Seed, K., . . . & Barfield, W.
  2. (2019). Racial/ethnic disparities in pregnancy-related deaths — united states, 2007–2016. MMWR. Morbidity and Mortality Weekly Report, 68(35), 762-765. mm6835a3
  3. Howell, E. A. (2018). Reducing disparities in severe maternal morbidity and mortality. Clinical Obstetrics &Amp; Gynecology, 61(2), 387-399.


Paris Johnson, MSHI, MPH is pursuing a Doctor of Public Health degree at Samford University, focusing on Population Health Analytics and Decision Making. Presently, she serves as a researcher at the Marshall University Joan C. Edwards School of Medicine, where she contributes to various projects related to addiction sciences, rural health, medical education, and public health initiatives.

Salisha Marryshow -Batson, MPH is currently pursuing a Doctor of Public Health degree with a focus on Health Policy at Samford University. She works at the Vanderbilt Institute for Medicine and Public Health where she manages a range of research and administrative tasks in Health Service Research, including clinical research for the ADOPT study.

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