Rwanda: How Digital Health Is Helping Reduce Maternal Deaths
[New Times] Digital health systems are increasingly helping Rwanda identify high-risk pregnancies earlier, improve patient monitoring and connect health workers to specialist support, measures that officials say are contributing to a decline in maternal deaths.
Digital health initiatives in Rwanda are credited with cutting maternal deaths by 30 percent within the last two years, according to Minister of State for Health Dr. Yvan Butera. The country has mounted a 85 percent reduction over the past two decades, though high-risk pregnancies continue to pose a challenge.
Butera pointed to electronic medical records linking community health workers, health centers, and hospitals as a key tool. Rwanda has over 54,000 community workers equipped with smartphones running a locally adapted electronic medical record system. This system enables workers to gather patient data, spot risks, and follow up, especially on pregnant women and children.
The data from community health workers is accessible to health centers, while hospitals monitor information from their service areas. This allows for early detection of potential complications, giving health workers more time to prepare before delivery. Additionally, the use of ultrasound machines alongside information on health conditions such as high blood pressure and diabetes has helped identify high-risk pregnancies.
Rwanda has further bolstered its healthcare system with virtual hospital links connecting district hospital doctors to specialists elsewhere in the country. This system provides real-time guidance to general practitioners in remote hospitals, reducing the need for patient transfers and saving an estimated 15 maternal lives since its inception.
Beyond maternal health, Rwanda is leveraging digitally collected data at community and health facility levels to guide decision-making, enabling authorities to respond swiftly to emerging health concerns.
Written by urgent.news from AllAfrica Health's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.