Why systems fail

Across Africa, millions still cannot get the healthcare they need: the care exists, but the way it's organized is failing them. People still mostly pay out of pocket when they fall sick, and healthcare providers can't plan or invest because their revenue is unpredictable. As a result, the quality of care suffers and trust erodes.

Healthcare works best when people prepay and share costs, allowing care to be planned collectively. Without collective financing, everything fragments. Investment feels too risky, quality becomes impossible to sustain, and people lose faith in systems that can't deliver.

For decades, the assumption has been that economic growth would solve this. But even wealthier nations now face rising costs and mounting inefficiencies. More money isn't enough; what matters is how care is financed, purchased, and organized.

Data as the fuel for better health systems

B­etter health systems need better information. Today, most health systems pay for output — consultations, procedures, prescriptions — rather than outcomes. This creates a fundamental misalignment: the system rewards doing more, not achieving more. Real-time, high-quality data changes that equation. When payment can reflect whether a patient actually got better, stayed healthy, or avoided a preventable hospitalization, the entire logic of the system shifts from treating disease to maintaining health.

This is not a marginal improvement. Outcome-based payment models, enabled by richer data, reduce uncertainty for payers, create clearer incentives for providers, and make resources go further. Instead of funding inputs, health systems can fund results. Instead of reacting to illness, they can invest in prevention.

Real-time data also supports smarter planning: identifying where demand is growing, where interventions work, and where spending is producing little measurable benefit. The result is less waste, and funding directed toward care that genuinely delivers. This directly contributes to better functioning, inclusive health insurance.

Digital technology has already driven this kind of transformation across other sectors — through real-time services, AI-driven tools, and transactions that are transparent and verifiable at scale. Yet healthcare remains fragmented. Why?

The answer lies in who controls data and on what terms. Health data is uniquely sensitive, and it sits at the intersection of three parties with different and often conflicting interests: patients, doctors, and payers. Patients must share their data to receive care, but that same data can be used against them by insurers, to raise premiums, restrict coverage, or discriminate. These risks are real, and they produce predictable consequences: information gaps, exclusion, and a deep mistrust that slows the adoption of the very tools that could improve care.

The core problem, then, is not technical. It is a problem of trust and governance. The rules around data ownership and access in healthcare were not designed for the digital age, and until they are reformed, the potential of data to transform health systems will remain largely unrealized.

Getting this right requires more than better technology. It requires rethinking the patient's role from passive data subject to active participant — someone with meaningful rights over their own health data, and a genuine stake in how it is used. Digital tools can support better care pathways, extend reach beyond clinic walls, and power the shift from reactive treatment to proactive health management. But they will only do so at scale if the institutions deploying them have the trust of the people they serve.