AI governance for healthcare

In this report, authors discuss how despite their potential, DHAITs continue to face systemic adoption barriers. The sector lacks robust, context-sensitive evidence demonstrating long-term value and existing evaluation models, inherited from the pharmaceutical and medical technology (including medical devices and IVD diagnostics )often prove ill-suited for digital tools. Towards AI governance for healthcare, the report provides a framework for evaluating DHAITs and a set of evidence-based policy recommendations.

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. 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 are equally important. These tools support critical functions such as risk analysis, screening, diagnosis and prognosis, but without proper evaluation, the essential piece of providing AI governance for healthcare, the full potential of DHAITs cannot be realized.

• Why do we need AI governance for healthcare?
• What would an evaluation consensus look like for digital health and AI technologies?
• How can healthcare leaders leverage this framework to scale and adopt the right digital health and AI solutions?

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