AI for healthcare: creating an international approach together

Overview

The use of artificial intelligence (AI) in health systems has accelerated globally with different applications being tested and put into practice across diverse areas of health system design and delivery. The COVID-19 pandemic has led to additional deployment of AI-based data driven technologies (referred to as AI-driven technologies hereafter) in health at both national and local levels. While there is information and guidance on developing AI models for medical tasks, there is comparatively less information and guidance on supporting development and implementation of AI models within digital health technologies from a policy and regulatory perspective.

This report is a step towards providing such policy guidance to the international health community. Building upon rapid literature and policy reviews, interviews with GDHP member countries, and a focus group with experts in digital health, this report provides a set of policy recommendations on how best to support and facilitate the use of AI-driven technologies within health systems. The policy recommendations are presented at a high level, so to be applicable regardless of a country’s digital health maturity level. Through this, the authors hope the policy recommendations can provide a basis for the international health community to use as they develop national and regional approaches to developing and utilising AI-driven technologies in their healthcare system.

The report has four categories of policy recommendations and tracks policy issues raised throughout the life cycle of designing, developing and implementing AI into a health system:

1. Leadership and oversight is necessary to ensure that countries take a ‘needsbased’ approach to AI-driven technology development and use within their health systems and to ensure that AI-driven technology use creates maximal benefit when it comes to health outcomes. This vision of AI-driven technology use should direct oversight across all stages of the AI life cycle, along with supporting activities such as research, funding, and workforce development.
2. Policies should focus on the entire ecosystem of AI research and development rather than focusing on just one aspect of the life cycle. This requires measures to aggregate and link data, public-private initiatives to address skills and funding gaps, and a robust research to deployment pipeline.
3. National standards and regulatory processes should ensure interoperability, safety, and efficacy of AI-driven technologies in health settings. Regulation should recognise the distinct nature of AI within digital technologies, and should also be transparent and shared publicly to build a trustworthy environment.
4. Engagement with stakeholders such as patients, healthcare practitioners, and industry should be proactively pursued through highlighting the demonstrable benefits of specific uses of AI-driven technologies in health systems. A focus on building trust around specific uses of AI-driven technologies will ensure that AIpdriven technology development and use is informed by purposeful and educated conversations with stakeholders.

Working with healthcare professionals and the higher education sector to update medical education and accreditation for AI-driven technologies, as well as to co-design future AI-driven technologies, will help ensure a frictionless deployment of AI-driven technologies that complements healthcare professional workflows.

This content is available under the Open Government Licence v3.0

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