How Rwanda Is Using Data To Deliver Better Health Care

· Source: Insights | Tony Blair Institute for Global Change (TBI) · Field: Health & Wellbeing — Healthcare Systems & Policy, Medical Devices & Health Technology · Depth: Intermediate, short

Summary

Rwanda, supported by TBI, has implemented a multi-year initiative to integrate health data across its national system, aiming for faster decisions, improved care, and better outcomes. Despite significant health gains, the sector faced challenges like fragmented information systems and manual data processing, exacerbated by the Covid-19 pandemic. This led to the April 2025 launch of the National Health Intelligence Center (NHIC), a hub integrating real-time data from various sources, which has reduced the time to generate national-level insights from two months to near real-time. Additionally, King Faisal Hospital Rwanda implemented an Integrated Health Management Information System before 2024, combining administrative and clinical data, resulting in a 60 percent reduction in average patient waiting times. These projects are establishing a unified health-data infrastructure, providing a blueprint for a national electronic medical records system (e-Buzima) and laying foundations for future AI-enabled health management.

Key takeaway

For IT Professionals tasked with modernizing health information systems, Rwanda's success demonstrates the critical value of integrated data infrastructure. Your focus should be on establishing centralized data hubs like the NHIC and patient-centric platforms to reduce fragmentation. Prioritize secure data warehousing and local capacity building to ensure sustainability. This approach significantly cuts patient waiting times and accelerates national-level insights, providing a clear blueprint for future AI-enabled health management.

Key insights

Centralizing fragmented health data systems into integrated hubs dramatically accelerates decision-making and enhances patient care efficiency.

Principles

Method

Establish a centralized data hub by shaping strategic framing, advising on technical requirements, embedding data scientists for system architecture refinement, and designing secure data warehouses.

In practice

Topics

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Policy Maker, Consultant, IT Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by Insights | Tony Blair Institute for Global Change (TBI).