The opportunities for AI across the health continuum - from healthy living and prevention to diagnosis, treatment and home care - lie in its potential to help translate large amounts of data into actionable insights. These insights can empower clinicians, hospital administrators, patients and health consumers to achieve better health outcomes at lower cost.
As the recently published 2018 Future Health Index (FHI) outlines, systems that deliver effective outcomes and high levels of healthcare professional and patient satisfaction – such as those in Singapore, Sweden and the Netherlands – tend to be those with comparatively high levels of focus on advanced data collection and analytics.
For example, out of the 16 countries in the FHI Sweden has the greatest spend on AI for therapy planning per capita compared to the 16-market average ($0.17 vs. $0.06 average) and for AI in preliminary diagnosis ($0.07 per capita vs. $0.03 on average).
Nevertheless, applying AI to healthcare and personal health requires more than just machine learning, deep learning or other statistical methods. First and foremost, it requires a deep understanding of the clinical, operational, or personal context in which such methods are used, as well as a solid framework that can ensure that AI adoption in health care is done ethically and sustainably.
Policy makers, health care professionals, industry experts and patients need to make sure the right conditions are met in terms of regulations, training and adoption.
In partnership with Politico, Philips is convening a panel of expert speakers from the public and private sectors to discuss how artificial intelligence can make health care systems fit for the 21st century and deliver better patient outcomes and more value for money.