Rwanda’s National Health Intelligence Centre (NHIC) is transforming the way health information is collected, analysed, and used to make decisions, with artificial intelligence (AI) at the centre of efforts to build a faster and more responsive healthcare system.
Established in April 2025 by the Ministry of Health, NHIC serves as a central platform that integrates health data from across the country, including information generated by community health workers, health facilities, hospitals, emergency services, and other health systems. The data is processed and analysed to provide evidence that supports planning, policy development, and improved service delivery.
The centre combines large volumes of health information using advanced analytics and AI technologies, enabling health authorities to monitor trends, identify challenges, and respond more quickly to emerging needs.
Health Minister Dr. Sabin Nsanzimana said NHIC has significantly changed how health information is accessed compared with previous approaches, where collecting reliable data often required lengthy processes involving multiple institutions.
“Today, we can access all information from one room,” Nsanzimana said, explaining that AI helps analyse large amounts of information within a short time.
He gave an example of monitoring childbirth data, saying information such as the number of births and newborn statistics can now be accessed within minutes, whereas previously it could take much longer to compile and analyse.
The minister added that Rwanda has moved beyond using technology only for identifying health challenges and is now advancing toward technology-supported treatment through solutions such as telemedicine, where specialists can support patients and healthcare workers remotely.
How NHIC manages health information
Data collected from health posts, health centres, district hospitals, referral hospitals, and other health institutions is digitally transmitted to NHIC, where it undergoes verification and analysis before being used for decision-making.
The system checks data quality to ensure accuracy and reliability. According to officials, the quality of information stored at NHIC has reached 90.1 percent, making it suitable for generating insights to guide interventions.
The platform maintains health records collected from different systems and follows patients’ journeys from diagnosis and treatment to follow-up care, helping health officials understand outcomes and improve services.
E-Banguka: Monitoring emergency response in real time
Among the key systems operated through NHIC is E-Banguka, a digital emergency response monitoring platform that tracks Rwanda’s ambulance fleet.
The system uses GPS technology to monitor ambulances, allowing officials to follow their locations, routes, and response times while coordinating emergency services.
NHIC Director Dr. Eric Remera said the centre has helped reduce ambulance response times, with emergency vehicles now reaching patients faster than before.
He said NHIC has also solved challenges related to scattered health information by creating a secure central system where data can be stored, accessed, and analysed.
“Previously, data was stored in different places, making it difficult to combine and sometimes putting it at risk of being lost,” Remera said.
African countries look to Rwanda’s digital health model
Rwanda’s digital health progress has attracted interest from other African countries seeking to strengthen their own health information systems.
Health officials and data experts from seven African countries — Burkina Faso, Ethiopia, Liberia, Senegal, Sierra Leone, Togo, and Zambia — are in Rwanda for discussions on the role of health data in improving healthcare systems.
Minister Nsanzimana said the countries’ decision to visit Rwanda reflects growing recognition of the country’s efforts to use technology and AI in healthcare.
Rwanda launched NHIC as part of broader efforts to use real-time data and artificial intelligence to improve health planning, disease surveillance, emergency response, and evidence-based decision-making.
