The 2024 BabyChecker webinar featured Dr. Gregory Ganda, Chief Officer of Health in Kisumu County, Kenya. In his presentation, “Leveraging AI Ultrasound, Risk-Flagging, and Digitizing Health Records for Better Maternal Health Outcomes in Kisumu County”, he highlighted how innovations like BabyChecker are strengthening maternal healthcare. His insights provided a deep dive into the challenges, opportunities, and impact of integrating AI-driven fetal monitoring and digital health systems in resource-limited settings.

The maternal health challenge in Kisumu County

Maternal and newborn mortality remains a pressing concern in Kisumu County despite increased facility-based deliveries. The county, which has 338 health facilities, has seen facility-based deliveries rise from 69.5% in 2014 to 94.4% in 2022. However, maternal mortality remains high, with a reduction from 495 to 343 per 100,000 live births, a 30% decline but still far from the county’s target.

Dr. Ganda emphasized the gap between increased facility deliveries and maternal mortality rates. “If 94% of the people are delivering in facilities and you have a maternal mortality of 343, it means then that you are not offering quality, and the quality that you’re offering is not good enough.”

One of the key issues is the lack of skilled personnel in rural sub-counties, leading to delays in care and discouraging women from seeking maternal health services.

“Facilities in the periphery are inadequately staffed, and the few staff available often lack the necessary experience. When mothers get poor outcomes, they discourage others from attending those facilities,” Dr. Ganda explained.

AI-enabled maternal health: Transforming care in Kisumu

To reduce maternal and newborn mortality by 80% by 2026, Kisumu County is adopting a digitally enabled maternal healthcare model. AI-driven screening, risk-flagging, and electronic health records are at the core of this initiative, with BabyChecker playing a crucial role in improving maternal and fetal monitoring.

BabyChecker is currently being piloted in select health facilities, providing critical fetal monitoring in areas where sonographers are scarce. The AI-powered tool detects complications such as fetal distress and placental anomalies, allowing for early intervention and better outcomes.

To enhance risk detection, Kisumu has also introduced AI-powered risk-flagging systems like WANDA EMR, which categorizes pregnancies into Green (normal risk), yellow (moderate risk), and red (high risk).

This triage system ensures timely intervention by healthcare providers and helps prioritize high-risk pregnancies.

Digitizing maternal health records: The next frontier

Kisumu County is integrating BabyChecker with its expanding digital health infrastructure to ensure seamless maternal health data tracking. Through the Electronic Community Health Information System (ECHIS), healthcare workers can now monitor pregnancies from early stages through postnatal care, strengthening continuity of care.

The county is also digitizing maternal and child health clinics, connecting them to a centralized District Health Information System (DHIS), which allows for real-time monitoring and decision-making.

Dr. Ganda explained the county’s digital strategy. “Our primary health care facilities are undergoing digitization, and we actually want to digitize reproductive health. We are starting with maternal and child health clinics and linking all these facilities into one system.”

By integrating BabyChecker with these digital health innovations, Kisumu County is setting a groundbreaking precedent for AI-driven maternal care in low-resource settings.

Impact of AI on maternal health in Kisumu

The AI-powered maternal health solutions in Kisumu County are already yielding promising results:

  • 2,626 mothers attended antenatal clinics since May 2024, with 393 high-risk alerts identified through the AI system.
  • 103 ultrasound scans have been conducted in the first month of piloting BabyChecker.
  • 60+ high-risk pregnancy alerts per month enable real-time interventions by healthcare providers.

Overcoming barriers to AI adoption

Despite its success, several challenges remain in implementing AI-driven maternal healthcare in Kisumu:

  • Geographical Barriers: Many mothers still travel long distances to access adequately equipped health facilities.

“Sometimes, they don’t have transport, and that causes the first delay… they have a long distance to travel, and all these things lead to poor outcomes and delays,” Dr. Ganda noted.

  • Limited Connectivity: Unstable internet access in rural areas can delay real-time data synchronization in clinics.
  • Adoption Resistance: Some healthcare workers and patients are unfamiliar with AI-driven diagnostics, requiring additional training to build confidence in the technology.

To address these barriers, Kisumu County is prioritizing capacity building, expanding training programs, and advocating for sustainable funding models to ensure long-term success.

The Future of AI in maternal health

Kisumu County’s AI-driven maternal health initiative is setting a model for resource-limited regions worldwide. By integrating AI ultrasound, digital health records, and risk assessment tools, the county is building a stronger, data-driven maternal health system.

However, sustained progress will require collaboration between governments, healthcare providers, and innovators to scale these interventions and ensure no mother or newborn dies from preventable causes.