AI: The Tip of the Health Information System Iceberg

From predicting the effects of climate change on health systems to diagnosing TB more quickly, artificial intelligence (AI) is a rapidly evolving field that offers new possibilities for improving health outcomes and strengthening systems. But AI—which refers to computer systems that can perform tasks traditionally associated with human intelligence—is just one building block in a much larger structure that uses quality data to strengthen whole health systems and provide lifesaving care to people who need it.

MSH has a history of supporting strong and effective national data systems—work made even more relevant by the emergence of AI-assisted tools and models for analyzing those data. Our approach to digital health development is driven by two guiding principles: view health systems holistically and commit to sustainability and alignment with the national information structures of the communities we serve. Data use is at the center of all of our work, and building scalable and sustainable data systems that are interoperable with our partner countries’ national platforms is critical to our mission.

In Uganda, for example, the USAID-funded Strengthening Supply Chain Systems (SSCS) Project, led by MSH, has provided technical support for the implementation of an electronic logistics management information system (eLMIS) in more than 1,400 of the country’s 6,000+ public health facilities. This is crucial work for integrating supply chain data with other health-related information, which can lead to more stable supply chains underlying the health system.

Similarly, our work in Madagascar through the Accessible Continuum of Care and Essential Services Sustained (ACCESS) Program has strengthened that country’s national health management information system through several measures, including ways to track health worker training; capturing and reporting numbers for community levels of fevers, diarrhea and other common health issues; and monitoring various health care programs being implemented across regions. These tools make it easier for health officials to closely monitor public health activities in the country and conduct routine audits to ensure trust in the data’s accuracy and validity.

Because digital approaches need to be tailored to local realities, our work in Rwanda has focused on improving data use at the district level. To support costing for primary health care (PHC), MSH configured dashboards for already-available data that are aligned with health systems strengthening building blocks to support PHC performance management. We also adapted our LDP+ leadership program for district health management teams to cover building data entry and reporting mechanisms.

These examples all represent ways we are laying the groundwork for ensuring that high-quality data is available for decision making and potential AI-driven analyses. The diversity of the examples also shows the importance of avoiding a one-size-fits-all approach. The digital ecosystem in each country is unique, and solutions built to manage and use high-quality data might all look different.

In our experience, digital health initiatives are most successful when they are implemented as part of a broader health systems strengthening approach that looks beyond the data and technology to also take into account the governance, health financing, and human resource implications of what we are doing to enhance information systems.

We encourage the use of health systems thinking to identify opportunities to build on existing systems, leverage interoperability, and increase capacity for data use across all the health system building blocks. As we continue to incorporate AI into our digital health toolkit, we will keep rolling out approaches that put the health workforce, governance, and quality of care at the center.

AI is a promising tool that can offer global health professionals new ways to improve outcomes and strengthen health systems. Although AI poses some challenges and risks that need to be carefully considered and addressed—especially with respect to ensuring equitable access and protecting individuals’ personal data—MSH is committed to following ethical and responsible principles and ensuring that any AI application we use aligns with our strategic plan and our mission.