Persistent data gaps undermine key health-related goals, new study finds

Data gaps that limit the ability to track progress towards the health-related Sustainable Development Goals (SDGs) are widespread and uneven, a new global study by WHO/Europe shows. The analysis finds that nearly one third of 43 health-related SDG target indicators face severe data shortages, with more than 90% of data points missing in some areas. This highlights systemic weaknesses in health information systems.

"When we are missing the right type of data, the most vulnerable communities become invisible to policy-makers. The SDGs were built on a promise to leave no one behind, but we cannot meet this promise without accurate data. We hope that this study will serve as a call to action for governments and partners to treat health information systems as the essential infrastructure they are," said Dr Natasha Azzopardi Muscat, Director of Health Systems at WHO/Europe.

The study, co-funded by the European Union, assessed the distribution of missing data, covering all 194 WHO Member States over the period from 2015 to 2024. It is the first global analysis to examine missing data patterns across regions, over time and by level of disaggregation.

Data collection

The percentage of missing data fluctuated significantly over time. In 2024, 41 out of 43 indicators had more than 90% of data missing, compared to 11 indicators in 2019. The way data is produced also affects how much of it is available. Nearly half of the indicators rely primarily on modelled estimates, 35% on data reported by countries and 16% on a mix of both. Indicators based on estimates tend to cover more countries, showing that many countries face difficulties in regularly collecting and reporting primary data. These trends make it harder to track real progress over time. Also, while estimates help fill some gaps, they reduce countries' ownership of the data used to guide decisions.

Variations in missing data are influenced by a range of factors. Most data are reported with a delay. Some indicators address socially or politically sensitive issues, such as violence or child abuse, where data collection and sharing may face barriers. Others are conceptually complex and rely on large-scale surveys that are conducted rarely. Shifts in foreign policy and financing further highlight the reliance of many countries on external support for such surveys.

Why data matters

"As WHO, we are mandated by Member States to compile and disseminate health statistics," said Dr David Novillo Ortiz, Regional Adviser for Data, Artificial Intelligence and Digital Health at WHO/Europe. "However, gaps in reported data make this challenging and weaken the effectiveness of countries' policy decisions, as well as WHO's work. This study shows that if we are to realize the ambitions of the SDGs or WHO's 14th General Programme of Work, sustained investment in timely and high-quality data is a must. This way, progress can be measured and inequalities are not left unseen."

Accurate and timely data is a cornerstone of effective global health governance. It helps governments and international organizations set clear goals, identify priorities, track progress and address inequalities. When health data is incomplete, outdated or inconsistent, decisions are more likely to be based on assumptions rather than evidence. This can lead to resources being misdirected, slow recognition of emerging health threats and weak monitoring of whether policies are working.

Poor data also undermines accountability: governments and institutions cannot clearly demonstrate progress or explain setbacks if the evidence base is thin. For citizens, data gaps can mean that the health needs of certain groups, such as women, older people, children, people with disabilities or those living in poverty or remote areas, are overlooked. Without reliable data, services may not reach those who need them most.

Moving forward

The study outlines key actions needed to address data gaps. It calls for strengthened data coordination, particularly between ministries of health and national statistical offices. This includes clearer legal frameworks, improved data-sharing infrastructure and sustained investment in capacity-building, alongside stronger mechanisms for sharing technical expertise among WHO, United Nations agencies and national institutions.

Improving the timeliness of data and addressing persistent gaps in disaggregation requires more standardized and regular reporting processes, incentives and accountability mechanisms, as well as context-specific approaches to collecting and reporting data on inequalities. The study further recommends the routine implementation of Health Information Systems assessments to identify political, technical and infrastructural barriers to data availability. This would support collective problem-solving and better stewardship of health data in support of the health-related SDGs and WHO's 14th General Programme of Work.

High-quality and timely data is also fundamental to the success of the Roadmap on AI for health, due to be adopted by WHO/Europe Member States at the 76th session of the Regional Committee in October 2026. WHO/Europe and the European Commission are working in partnership to strengthen health information systems and boost health data governance and interoperability in the WHO European Region.