Healthcare systems around the world are facing mounting financial pressure and are increasingly being stretched across competing priorities. At the same time, the global shortage of healthcare workers is accelerating. These challenges are compounded by the persistent rise in noncommunicable diseases (NCDs), which are now responsible for 41 million deaths annually – 74% of all global mortality. Digital health and artificial intelligence technologies (DHAITs) hold considerable promise in addressing these pressures. By enabling more accessible, sustainable, efficient and higher quality care. While attention often centers on patient-facing tools, digital solutions used by healthcare professionals (HCPs)—including clinicians, nurses, managers, and administrators—are equally important. These tools support critical functions such as risk analysis, screening, diagnosis and prognosis, treatment choices, and patient monitoring, with potential to optimise workflows, reduce unwarranted variation in care, and improve both provider efficiency and patient outcomes.
Despite their potential, DHAITs continue to face systemic adoption barriers. Many healthcare providers and patients lack the necessary digital literacy to effectively use these tools, and infrastructure constraints and resource limitations are widespread. Even though the implementation of the European Health Data Space aims to create a common framework for the use and exchange of health data across the European Union (EU), the current absence of standardised frameworks for data access, sharing, and governance contributes to fragmentation across systems globally. The lack of interoperability between different systems complicates their integration and discourages healthcare professionals to adopt DHAITs. Most significantly, the sector lacks robust, context-sensitive evidence demonstrating long-term value. Existing evaluation models, inherited from the pharmaceutical and medical technology (including medical devices and IVD diagnostics) sector, often prove ill-suited for digital tools, which tend to be iterative, adaptive, and fastermoving. As a result, many digital solutions fail to achieve scale, leading to a proliferation of short-lived, low-value tools that never realise their intended impact.
The aim of this report is two-fold:
- First, an evidence-based taxonomy for healthcare professionals facing DHAITs has been developed to enable the development of more targeted and appropriate evaluation methods.
- Second, to inform the evidence assessment framework for HCPs-facing DHAIT, a policy analysis was conducted to assess the current evidence requirements for medical devices and technologies as a whole and the requirements explicitly developed for DHAITs.