The report

As countries digitalize their health systems, health practitioners and ministries of health are learning what makes the development and introduction of digital health tools and approaches successful. However global policies and digital health investments often do not reflect the priorities and lessons that have emerged from these countries’ experiences.

To bridge this gap, the Data Use Acceleration and Learning (DUAL) initiative collected learnings from its five focal countries and packaged them into a model for digital transformation for data use that evolves the World Health Organization (WHO) and International Telecommunication Union (ITU) eHealth Strategy Building Blocks.

The DUAL model identifies ten core elements of a comprehensive approach to transforming a country’s health data systems and digital tools to advance data use. Rather than presenting a linear, step-by-step guide for digital transformation, it provides the “ingredients” for success that depend on and enable one another toward catalytic change.

The DUAL report allows countries to identify the most appropriate starting point based on the priorities and digital maturity of their health systems. Each element is framed as a standalone chapter with key enabling factors, based on the evidence of what worked and what didn’t in the five focal countries DUAL studied. Specific actions are recommended for each enabling factor and country examples are used to illustrate the DUAL model at work.

A Collaborative Country Effort

The DUAL initiative reflects the cumulative inputs of five countries digitalizing their health systems and steady stakeholder engagement with implementers, policymakers, and other key digital health stakeholders to validate findings. Through a series of key informant interviews, country dialogues, online surveys, and webinars, DUAL developed a model that serves as a practical, comprehensive guide to advancing the use of data to achieve health equity. Countries with health systems at any stage of their digital transformation process can choose the actions that make sense for their digital health systems’ context.