Or listen in your favorite podcast app
Uli K. Chettipally, MD, MPH, (LinkedIn, Twitter) is a physician, an author, a speaker, and an innovator, and on this episode of IT Visionaries, he joins Ian to discuss the role of A.I. and technology in the world of healthcare. Uli has worked in a number of high-level roles both as a medical doctor and a chief innovator at hospitals as well as medical centers and institutions such as Kaiser Permanente and the University of California, San Francisco. He has led a number of initiatives to bring technology into the medical field and he is on a mission now to inform and empower people with artificial intelligence. He and Ian discuss all that and more in this episode.
The reasons behind his new book — (3:20)
Earlier this year, Uli came out with his new book, Punish The Machine!: The Promise of Artificial Intelligence in Health Care. Uli is inspired by technology, such as the A.I. that a number of hospitals are using to help bring information to patients and physicians in realtime during their appointments. The technology is also being used as a predictive tool, which can predict, with a high degree of accuracy, whether or not a patient at risk will have a heart attack in the next week. Using these technologies have not just helped save lives, but it has also helped reduce the length of hospital stays, time of visits and other metrics.
“I thought that machine learning could be a tool that could help physicians in all kinds of instances.”
The broken promise of technology in healthcare — (5:50)
For so long, many in the healthcare field have been promising to use technology to revolutionize medicine, but many of those promises never came to fruition — the amount of time doing data entry for electronic medical records being one main example of where technology has made things worse, not better.
“There have been a lot of promises that have been made with technology in general that did not come true.”
“The main purpose of technology, which is how do you improve the quality of care for the patient, is being lost in the current system.”
“We should expect more from the machines — more intelligence and much smarter machines, which will help the doctors practice better medicine, take the burden of work away from the doctors and provide good, quality care to the patients.”
The future of predictive analytics in healthcare — (8:50)
Using the technology we have today, and improving on it, Uli believes that doctors will be able to save more lives due to the power of predictive technology. Because of the immense power of computers, you can truly personalize the analysis of patients, each of whom has different risk factors and input their specific data into a machine that will then have a personal plan of action, insights, and predictions based on those metrics.
The business model of healthcare has been one of the biggest problems to overcome. The business model currently is fee-for-service, which is broken down as follows: patient gest sick, patient comes into office, doctor treats patient, doctor gets paid. For innovation to really stick, there needs to be a change in this model toward a more value-based healthcare model. This model places value on predicting and preventing bad outcomes, and that’s where technology comes into play.
“If you can predict a bad outcome, you can also potentially prevent that bad outcome.”
“In a value-based care model, the idea is to keep the patient healthy and not allow them to get to a stage that becomes very serious.”
Where are we on the timeline of the A.I. revolution in healthcare? — (20:20)
The A.I. revolution is still in its nascent stages. We’re still only at the point where we can capture and use some data, there are still many open questions about what to do with the data that is collected, whether it is significant, whether it can all be used to predict outcomes, and if those predictions can also be used in all cases for prevention to make outcomes better. There are new techniques and methodologies being used to analyze the real world data, but those methods need to keep improving in order to find the best ways to interpret and then use the data in the most efficient and responsible ways.
“We are in the very early stage of the revolution.”
“There are a lot of steps we need to take before these technologies can be used by physicians.”
The future of research — (25:00)
Collaboration needs to occur between physician-scientists, research scientists, engineers and others to come up with solutions to healthcare problems. These collaborations do not begin and end in hospitals and research centers, though. Uli believes there are opportunities for all these groups to work together in start-ups and other companies on things like wearables, fitness and other areas where research can be done and then applied in the business and in the medical field. By combining research from various fields and using data sets and advanced technologies, there is a chance to help solve or even prevent crises such as the opioid crisis.
“The future of research is based on collaboration.”
“This isn’t just fascinating for the sake of curiosity. This is the stuff that will save lives and prevent bad things from happening.”
Where A.I. can be applied — (28:10)
Medicine is an art and a science. Connecting with patients, building trust and coming together are the art pieces of the profession and those are dependant on the humans at the center. But when it comes to science, there are ways for technology to come into play and improve the process. There are three main areas Uli thinks A.I will be most useful. The first is prevention. A.I. provides the opportunity to personalize what is now a very generalized process.
The second is diagnosis. With A.I. there is a chance to identify things that might otherwise have been missed early on.
The third is in treatment. There are often dozens of drugs that can be used to treat the same condition. Currently, there is only a trial-and-error system to find the right drug for the right patient. A.I. can be used to predict which medicine would work best for each specific patient.
“Right now prevention is very generalized. What if we could personalize it?”
“Medicine is an art and a science.”