About Data Analytics, Systems, and Use (DASU)
DASU is a practical and results-oriented framework designed to strengthen health systems and other public services through effective data use, digital tools, and innovation. Grounded in three foundational elements of functional data ecosystem—data analytics, data systems, and data use, DASU enables institutions to become more responsive, transparent, and performance-driven.
- Data analytics is at the heart of DASU’s ability to convert information into impact. It involves the application of a broad range of advanced techniques (such as descriptive and inferential statistics, machine learning, artificial intelligence, geospatial modeling, and predictive analytics) to generate actionable insights from high-volume, diverse, and rapidly evolving datasets.
- Data systems serve as the digital backbone of the DASU framework, providing the infrastructure, platforms, and governance needed to collect, integrate, and manage diverse and interconnected data sources. These include routine health information, programmatic data, financial records, surveys, facility assessments, population estimates, laboratory and diagnostic data, public health emergency (PHE) data, logistics and supply chain information, and community-based data. By enabling interoperability and improving data quality, DASU-supported systems ensure timely and reliable access to information that is essential for effective planning and decision-making.
- Data use ensures that insights are translated into meaningful action, shaping policies, improving services, guiding resource allocation, and strengthening accountability. It embeds evidence into institutional planning, budgeting, and performance management processes, creating a culture of routine and impactful data use.
Objective
The objective of the Data Analytics, Systems, and Use (DASU) Initiative is to strengthen health system performance by institutionalizing the routine generation, analysis, and use of data for monitoring progress, guiding strategic decision-making, and advancing equity, quality, and efficiency at all levels of the health system.
DASU addresses critical structural and system-level challenges within the data ecosystem, such as fragmented systems, limited interoperability, governance gaps, and underinvestment in infrastructure and workforce capacity. The initiative promotes the integration and triangulation of diverse data sources—such as routine health information, program data, household surveys, facility assessments, administrative records, geospatial data, and population censuses—while fostering multi-institutional collaboration and data governance. It also supports the development of enabling environments for the adoption of emerging technologies (such as artificial intelligence and machine learning) to enhance predictive analytics, real-time insight generation, and evidence-informed policy, planning, and program monitoring.
