An older man and woman embracing, the woman in a red headscarf laughing

Governments

Rwanda Social Security Board

Supporting Rwanda’s Healthcare Reform

Data Science for Resilient Health Systems

As part of its move toward universal health coverage, Rwanda is shifting from a retrospective fee‑for‑service model to prospective capitation. Under capitation, facilities are paid in advance based among other things on the population they serve. The aim is to promote predictable spending, preventive care and system efficiency.

Causal Foundry is working with the Rwanda Social Security Board (RSSB) to develop a data‑driven design of this major financing reform, and support its implementation, monitoring and evaluation.

A doctor performing an ultrasound scan on a smiling patient

AI for good

A Fairer, More Predictable Payment Model

The success of a capitation model relies on the accurate prediction of healthcare demand. Causal Foundry worked with RSSB to design a capitation formula that takes into account not only each center’s catchment population, but also its historical service use and the number of visits by outside patients. This provides a more complete picture of healthcare demand each center serves and helps ensure that funding reflects real needs.

To minimize disruptions during the transition, the formula has been designed to keep projected payments close to each facility’s historical expenditure. For further adjustment, a monitoring system tracks key indicators such as facility utilization, service delivery or number of tests per visit. Our algorithms detect statistical outliers and flag anomalies for further investigation, helping RSSB identify potential problems and respond to them.

Data Driven

We’ve analyzed data from more than 30 million visits and 80 million procedures per year since 2023

Data Secure

No data leave the country. All patient‑level information is strictly anonymized according to national regulations

Accountable

No black boxes. Our capitation formula is fully transparent and interpretable to ensure policy accountability

AI for global impact

More Service Delivery, Fewer Referrals

As payment no longer increases with each covered service, a common concern with capitation models is that facilities provide less care or refer more patients to other centers. Causal Foundry has worked with RSSB to track how health centers perform as they transition to the new model. The goal is to investigate potential adverse effects and mitigate them before capitation is deployed nationwide.

So far, health facilities that have transitioned to capitation have seen more visits, more follow‑ups and fewer referrals.

By putting advanced data models at the service of a better healthcare system, Causal Foundry and RSSB are helping build a more sustainable foundation for health systems across Africa.

More visits

+1.20

visits per 100 members per month

More follow‑ups

+7.8%

30‑day post‑admission revisit rate

Fewer referrals

–26%

compared to control facilities