AI Has the Potential to Improve Efficiency of Clinical Trials

Artificial intelligence (AI) is at an inflection point in healthcare as innovative machine learning and computer vision algorithms have the potential to streamline the highly inefficient drug development process and improve access to quality clinical care, bringing precision medicine closer to reality for patients.

First and foremost, vendors increasingly recognise that their value lies in pursuing solutions that address well-defined use cases, in contrast to earlier attempts to apply AI generically across the board to healthcare. Further, a growing body of published research describes consistent methods by which the clinical applications of AI are assessed and validated, mitigating concerns about the capabilities and safety of AI in healthcare . . .

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Healthcare is one of the major success stories of our times. Medical science has improved rapidly, raising life expectancy around the world, but as longevity increases, healthcare systems face growing demand for their services, rising costs, and a workforce that is struggling to meet the needs of its patients.

Demand is driven by a combination of unstoppable forces: population aging, changing patient expectations, a shift in lifestyle choices, and the never-ending cycle of innovation being but a few. Of these, the implications from an aging population stand out. By 2050, one in four people in Europe and North America will be over the age of 65—this means the health systems will have to deal with more patients with complex needs. Managing such patients is expensive and requires systems to shift from an episodic care-based philosophy to one that is much more proactive and focused on long-term care management.

Healthcare spending is simply not keeping up. Without major structural and transformational change, healthcare systems will struggle to remain sustainable. Health systems also need a larger workforce, but although the global economy could create 40 million new health-sector jobs by 2030, there is still a projected shortfall of 9.9 million physicians, nurses, and midwives globally over the same period, according to the World Health Organization.¹ We need not only to attract, train, and retain more healthcare professionals, but we also need to ensure their time is used where it adds most value—caring for patients.

Building on automation, artificial intelligence (AI) has the potential to revolutionize healthcare and help address some of the challenges set out above. There are several definitions of AI, but this report draws from a concise and helpful definition used by the European Parliament, “AI is the capability of a computer program to perform tasks or reasoning processes that we usually associate with intelligence in a human being.”² AI can lead to better care outcomes and improve the productivity and efficiency of care delivery. It can also improve the day-to-day life of healthcare practitioners, letting them spend more time looking after patients and in so doing, raise staff morale and improve retention. It can even get life-saving treatments to market faster. At the same time, questions have been raised about the impact AI could have on patients, practitioners, and health systems, and about its potential risks; there are ethical debates around how AI and the data that underpins it should be used.

This EIT Health and McKinsey & Company report aims to contribute to the debate surrounding AI in healthcare, specifically looking at how practitioners and organizations will be affected. It aims to cast light on the priorities and trade-offs for different parts of the healthcare system in Europe and beyond. The report draws on proprietary research and analyses undertaken by EIT Health and McKinsey & Company. This includes work by the McKinsey Global Institute (MGI) on the future of work in the era of automation and AI,³ analyzing the impact on healthcare practitioners in Europe; a series of one-to-one interviews with 62 healthcare and other leaders with experience in AI and digital health, and an online survey of 175 healthcare professionals, healthcare investors, and AI startup founders and other executives. AI in healthcare being a fast-moving field, the report provides a unique vantage point from the frontline of healthcare delivery and innovation today and the latest view from a wide array of stakeholders on AI’s potential, the real state of play today, and what is holding us back.

Last, to highlight where AI is already having an impact in healthcare, the report also looks at detailed examples of existing AI solutions in six core areas where AI has a direct impact on the patient and three areas of the healthcare value chain that could benefit from further scaling of AI.

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