A health technology initiative in Kenya has deployed an artificial intelligence chatbot called PROMPTS to provide maternal health guidance through text messaging. The system emerged unexpectedly when pregnant women began responding to appointment reminder texts with medical questions, prompting Jacaranda Health to develop an automated response system.
The PROMPTS platform uses machine learning to analyze patient inquiries, prioritize them by urgency, and identify cases requiring immediate medical intervention. About 7% of messages are flagged as potentially urgent and routed directly to nursing staff. The system operates entirely over SMS, making it accessible to users with basic mobile phones and no internet connection. It currently understands English, Swahili, and Sheng, a Nairobi dialect, and is deployed across 24 Kenyan counties. Jacaranda Health has expanded the technology to Ghana, Nigeria, and Tanzania with versions supporting additional local languages.
Maternal mortality remains a significant public health challenge in Kenya, with approximately 6,000 women dying each year from childbirth or pregnancy-related causes. Nearly a third of these deaths are attributed to delays in seeking care. Health experts note that PROMPTS helps bridge access gaps by providing women in rural areas with immediate guidance on symptoms and health concerns, potentially preventing unnecessary hospital visits while identifying genuine medical emergencies.
The system also generates population-level health insights by analyzing anonymized user data from approximately 700,000 patients annually. Questions from mothers help healthcare providers identify gaps in service delivery and detect emerging health patterns, such as correlations between extreme heat and reported complications like dehydration and swelling.
However, researchers raise questions about error management and patient safety. Experts emphasize that the reliability of rapid handoff protocols to human staff is critical, and concerns about AI-driven medical decision-making—including privacy protection and preventing missed diagnoses—remain relevant as such systems expand globally.
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