Dr. Nicolaus Henke is a Senior Partner Emeritus of McKinsey & Company and the former Chair of QuantumBlack, McKinsey’s advanced analytics and AI firm. He was with Mckinsey for more than 30 years, and McKinsey’s worldwide leader both in Healthcare and in Advanced Analytics He served leading healthcare, industrial, consumer clients as well as high-performance sports teams. Since moving on from McKinsey, Nicolaus supports a small number of growth companies at the intersection of machine learning and healthcare.
One example of their current work includes to use VR and ML to make nurse and doctor training more effective and productive, deployed already in some of the world’s leading hospitals and medical schools. Another example is to reduce children’s anxiety before and during their treatment in hospital.
A further example is to better manage people’s health in their home combining advanced ML with radar and photonic chips. In the Nordics, he recently joined the board of Silo AI. Nicolaus studied operations research and economics, holds a master’s degree and PhD from the University of Münster, Germany, and a master’s from Harvard’s Kennedy School, where he was a John J. McCloy scholar.
Can ML/AI help us to tackle the biggest challenges in healthcare?
Healthcare is a huge success story as life expectancy has risen over decades, but at a cost as at $ 9 trillion consumes 10% of the world economy. Healthcarecaused cuts in other important sectors like education in the OECD, and is the leading cause for personal bankruptcy in the US and many emerging markets. The quality of care is variable in all countries. Most countries struggle to give equitable access to care to all their people. Also there is almost no country with a sustainable plan how to solve the looming workforce crisis. Across the EU, more than half of nurses and doctors report burn out symptoms resulting in mental health issues and resignations.
Some futurists argue that AI will help us tackle some of those problems and even replace some nurses and doctors – for example “Dr. Watson” interpreting cancer images, or eliminating doctor consultations with using “Dr. Chat-GPT”. Others are quite critical of those ideas, citing significant risks. In addition, some are also observing that decades of digitisation have made healthcare more complicated and contributed to an overworked workforce. Nor has the patient experience improved – many doctors look at their PC screen and not at us when we see them.
In this talk we will briefly discuss some of those arguments, but then move on to share a few examples in which some health systems already are making some good progress with ML deployments today.