Artificial intelligence is the kind of topic that brings out the inner geek in all of us. There is so much excitement about its potential applications and where it will have the greatest traction to the point where the conversation inevitably gets quite philosophical and untethered to the workaday world of healthcare professionals. And yet in many ways, the various iterations of AI are still in the early stages of development for most healthcare applications and don’t yet adequately address the greatest areas of need in the industry.
In a panel discussion on AI and healthcare at the J.P. Morgan Healthcare Conference Tuesday, Andy Slavitt, who served as the acting administrator of the Centers for Medicare and Medicaid Services under the Obama Administration for a time, contrasted AI and other exciting technologies under development with the practical realities of Medicaid patients, which are so often overlooked or glossed over in these conversations. He is currently a senior adviser to the Bipartisan Policy Center.
“To some extent, [AI] is a best of times, worst of times story.” He noted that medtech advancements could lead to people using 3D bioprinting to get a new liver or use predictive analytics to figure out what is the right topic to focus on with a patient in a doctor’s office.
“The worst of times is that we have to reconcile the fact that when we chase new things, we tend to put them back on the older things and tend to add an extra layer of complexity, not simplicity.
“We know we have people in our communities today who, if we got medication to them in a timely manner, they wouldn’t end up in the emergency room.”
Later in the conversation, Slavitt noted using AI to uncover fraud, waste, and abuse in healthcare would be a “slam dunk” but the complex issue of drilling down and addressing what drives healthcare costs is where the core need is.
A Deep-dive Into Specialty Pharma
A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
“Someone with diabetes, if they have a nutrition or housing issue, it costs 65 percent more to treat them. Someone with acute behavioral issues, who lives in extreme poverty, and has an underlying disease costs more to treat. How do we solve that problem with science?”
Dr. Jordan Shlain, founder and chairman of patient engagement business HealthLoop, noted that the company was starting to program AI into treatment preferences.
“How do you understand what kind of care people want based on their age, religion, and personal preferences?”
Even Shlain, who is a practicing physician, acknowledged some of the heady assertions people have made about AI replacing physicians en masse.
“I was just interviewed by a guy who asked me ‘When are you going to be made obsolete?’ I said that by the time the physician is obsolete, so are the investment bankers and lawyers, etc.”
NuMedii CEO Gini Deshpande highlighted research and development applications. She pointed out that machine learning could be used to help spot diabetic retinopathy. Both Shlain and Jamie Heywood, founder and chairman of PatientsLikeMe, noted that machine learning is already being harnessed for medical images, using pattern recognition to detect anomalies.
Heywood acknowledged the disconnect between what they hope they can do with AI-powered technologies will take years before it becomes mainstream medicine.
“We are currently in horse and buggies, but soon we will be in helicopters.”
Photo: rianAJackson, Getty Images
