Counting what Counts – Predictive Analytics & Artificial Intelligence in Healthcare with Len D’Avolio
In this episode of Creating a New Healthcare, Dr. Zeev Neuwirth interviews Len D’Avolio, CEO and founder of Cyft – an organization that uses data and Artificial Intelligence (AI) I to make value-based care wildly successful. Dr. Len D’Avolio has spent the past 13 years – in government, academia, philanthropy and industry – attempting to transform healthcare into a “learning healthcare system”. He is clearly one of our country’s most talented minds and experienced practitioners in the use of predictive analytics and machine learning as applied to healthcare.
His resume and portfolio are impressive – as an academic and an entrepreneur. Len is an assistant professor of medicine at the Brigham & Women’s Hospital and the Harvard School of Medicine. He has worked with superstars like Atul Gawande, deploying global healthcare projects. Len also created the infrastructure for the world’s largest genomic medicine cohort; and embedded the first clinical trial within an electronic medical record system for the Department of Veterans Affairs. He’s a highly sought after and nationally recognized keynote speaker, and serves as an advisor to numerous healthcare start-ups.
If you want to understand AI in healthcare – both the opportunities and the limitations – you’ll want to listen to Dr. D’Avolio’s deep knowledge and honest practical take on things. Len characterizes healthcare largely as treating data as ‘exhaust’, whereas other industries treat data like it’s their oxygen or their life blood. Whereas other industries understand how to use advanced data analytics to inform their daily decisions for the purpose of optimizing performance, healthcare remains years behind.
What we’re talking about here is ‘moneyball’ – using advanced mathematical algorithms embedded in software programs that affords practitioners in any field the ability to make much more informed decisions – whether that field is finance, sports, retail, social media or medicine. The ‘machine learning’ or ‘neural network’ part of it speaks to the capacity of these software programs to create probabilistic inductive hypothesis from enormous amounts of data – clearly something the unaided human mind can not do. This may be the ‘rocket science’ of our era; but it’s not magic. In this interview Len dispels the mystery & myths surrounding AI. He likens it to a tool. A hammer does not build a house – carpenters do; and so-called AI or supervised machine learning does not cure cancer – scientists and physicians do.
According to Dr. D’Avolio – and his expert colleagues, there is no magic to AI. This is not some plug-and-play ‘black box’ that can be let loose to solve all the problems in healthcare. It is not an independent sentient ‘artificial intelligence’ that will somehow supercede and substitute for physicians or physician scientists. To anthropomorphize this technology is fantasy. These tools require tremendous amounts of human expertise & attention – both technical and clinical – to program and manage – hence the term ‘supervised’. Len also dispels the myth that one algorithm can be applied across the board to numerous use-cases. The current reality is that it might require a team weeks, if not months, to create a program for a specific condition or situation.
On the other hand, what these tools can help us accomplish is profound and amazing. There is little doubt that this field will transform healthcare delivery – allowing us to deliver much better care at a much lower cost – optimizing outcomes and customizing medical care. There is little doubt that this field will transform the way medicine is practiced – assisting physicians and other providers in ways unimaginable. And, this is not the future – it’s now. Len shares some examples of these benefits.
This is an enlightening and inspiring interview in which we synthesize and distill the years of Len’s hard-earned practical wisdom into an hour’s time. You will leave the interview with a greater understanding of machine learning, predictive analytics, and AI in healthcare; and will now be aware of and connected to one of the leading figures in the field.