Artificial Intelligence (AI) is impacting healthcare and has the potential to revolutionise how it is delivered. In the second part of this short series on AI and policy we look at a report that considers the impact of AI on organisations in the healthcare sector.
13 March 2020
A report produced by the European Institute of Innovation and Technology (EIT) Health and The McKinsey Centre for Government (MCG) indicates that AI can increase productivity and the efficiency of care delivery, allowing healthcare systems to provide better outcomes for patients.
The report; Transforming healthcare with AI: The impact on the workforce and organisations asserts that while the benefits of AI are real, there is an ‘urgent need to attract, educate and train a generation of data-literate healthcare professionals and up-skill the current workforce to fully realise the transformative potential of AI.’ The report also considers the need to ‘define new organisational models and skillsets that healthcare professionals will need to support the adoption and scaling of AI.
The WHO estimates that by 2030 the world will be short of 9.9 million doctors, nurses and midwives, which adds to the challenges faced by an already overburdened healthcare system. Supporting the widespread adoption and scaling of AI could help alleviate this shortfall, the report says, by streamlining or even eliminating administrative tasks, which can occupy up to 70% of a healthcare professional’s time. Areas that AI in healthcare can impact include; chronic care management, diagnostics and self-care/prevention and wellness.
The issues highlighted, among others, means that ‘AI is now ‘top-of-mind’ for healthcare decision makers, governments, investors and innovators and the EU itself,’ the report states. But the report also highlights that public concern over AI and how healthcare data is handled has also grown. ‘Healthcare organisations should have robust and compliant data-sharing policies that support the improvements in care that AI offers, while providing the right safeguards in a cost-effective way,’ the report notes. Physicians who contributed to the findings emphasised that, given the volume of data required for AI, a poorly thought out process of anonymisation could be a major cost, making diagnostic algorithms prohibitively costly.