Dominic Kwabena Atweam, an expert in strategic health information systems with WHO Ghana, has revealed that Ghana has been using an intelligent maternal and child health tracking system capable of AI-like detection since 2011, yet the country still struggles to fully utilize the vast data it generates.
Speaking at the Africa Digital Dialogue, held under the theme “AI in Healthcare: Ghana’s Readiness” and hosted by MG Digital in partnership with the Digital Foundation Africa on Friday, November 14, 2025, he noted that several Community-Based Health Planning and Services (CHPS) compounds have long relied on an E-Tracker system to monitor maternal and child health.

He stressed the need to leverage Artificial Intelligence (AI) to analyze the data model and predict future immunization trends.

“When it comes to service delivery, as far back as 2011, some CHPS compounds in Ghana were already using what they called the E-Tracker for maternal and child health services and immunization. It already has an inbuilt intelligence, similar to advanced AI, so that if someone defaults, the system is able to tell. But how do we use the data generated for the entire country? How can we leverage AI to look at this model and possibly estimate what will happen in the next three to four years in terms of immunization?”

Dominic Kwabena A. explained that AI in digital health is situated within the broader health information ecosystem, which includes leadership and governance responsible for regulation and interoperability. However, he questioned how AI is currently being applied within this governance framework.

“AI in digital health falls into the health information ecosystem, and in every country, there are four components of health information systems. One component is leadership and governance that ensures regulation and interoperability. How is AI being used in that area?”

He further highlighted that Ghana’s data collection system is outdated, noting that many patients bypass the Outpatient Department (OPD), and the current paper folder system limits digital records. He pointed out that transitioning from ICD-9/10 to the AI-supported ICD-11 would significantly improve diagnostic accuracy. Although Ghana uses ICD-11 for mortality reporting, most health facilities still rely on ICD-10, which makes international data comparison difficult.

“The second component is the system that collects data. In Ghana, not everyone who visits a hospital goes through the OPD, and the current folder systems do not support digital data collection. We need to move from ICD-9 and 10, which allows a long list of diagnoses, to ICD-11 on our websites. Basically, ICD-11 uses AI to ensure that doctors are able to easily arrive at the most precise diagnosis where you can drill down and know exactly the type of illness. These simple tools allow physicians and clinicians to do proper diagnoses. But is Ghana adopting ICD-11? To some extent, yes. The aggregate platforms use it for cause-of-death and mortality reports. But when it comes to clinical care, a lot of our facilities are still using ICD-10. That means you cannot compare your data with countries using ICD-11.”

The dialogue forms part of the ongoing Africa Digital Festival (ADF) dialogue series, an annual event celebrating innovation and digital transformation across the continent. This session explored how Artificial Intelligence (AI) can transform healthcare delivery in Ghana and the capacity required to support its implementation.

 

By: Mabel Antwi