By The PPH Foundation
Every year, thousands of Kenyan mothers face life-threatening postpartum haemorrhage, often before clinicians can intervene. Advances in artificial intelligence and predictive health systems are now offering a proactive approach; identifying high-risk pregnancies, anticipating complications, and enabling timely interventions. By harnessing real-time data, electronic health records, and predictive algorithms, these technologies are poised to reduce delays, optimize resource allocation, and save lives.
Across Kenya, several digital platforms are using artificial intelligence not just to analyze data, but to support proactive maternal care and real-time clinical decision-making. In Nakuru County, an AI-based SMS platform known as PROMPTS (Promoting Mothers through Pregnancy and Postpartum) is operational in over 120 health facilities and has reached nearly 14,000 pregnant women. The system provides personalized health information and allows two-way interaction with expectant mothers, alerting clinicians when danger signs are reported and answering health queries that help women seek care promptly.
In parallel, machine learning models specifically developed for predicting PPH have shown strong performance in Kenyan populations. A cohort study using antenatal and intrapartum data built predictive models, with a naïve Bayes model achieving 95 percent accuracy and 97 percent specificity in identifying women at risk of PPH. Clinical risk factors such as anemia, limited prenatal care, hemoglobin levels, and vital signs were among the strongest predictors in the Kenyan context.
These tools demonstrate the potential for AI to improve maternal care through personalized risk profiling, early alerts, and data-driven resource allocation, especially in rural and underserved settings where clinicians are often overburdened.
Prof Moses Obimbo, Project Lead of the End PPH Initiative, emphasizes that AI should enhance, not replace, clinical judgment: “Predictive systems give clinicians timely insight that complements their expertise. By identifying high-risk mothers early, we can intervene before emergencies escalate, making maternal survival more likely.”
For AI innovations to be effective at scale, Kenya will need strengthened digital infrastructure, interoperable health data systems, and investments in training clinicians to interpret and act on predictive insights. As digital health platforms proliferate, from AI-triaged SMS tools to machine learning risk models, the frontier of maternal care is shifting toward prevention and prediction, offering hope that more lives can be saved.
Sources:
• Kenyan News Agency, “County integrates Artificial Intelligence to promote maternal health care,” 2025
• Santosh Yogendra Shah et al., “Prediction of postpartum hemorrhage using machine learning algorithms in a Kenyan population,” Frontiers in Global Women’s Health, 2023
• EthicalBusiness.Africa, “Innovation is improving maternal health in Kenya,” 2026
• PMNCH/WHO news analysis on maternal mortality in Kenya
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