At HIMSS17, Internet of Business’s Juan Monge attended IBM CEO Ginni Rometty’s keynote and caught up with Travis Frosch, GE Healthcare’s director for analytics and cybersecurity.
This year’s HIMSS, the largest gathering for health IT professionals in the US, was marked both by uncertainty over the prospect of profound regulatory changes and a sense of hope, as leading tech players in the health space such as IBM Watson, GE Healthcare, Optum and InterSystems showed how AI and IoT are key in facilitating personalized and precision medicine.
For years, the main preoccupations at HIMSS have revolved around electronic health records (EHRs) and how to mitigate cyber risk, but this year, there seemed to be a clear shift in focus: the future is cognitive, and it is becoming clearer to leaders across the health spectrum that AI can be the key to some of the greatest challenges currently being faced by the industry. These include the escalating cost of treatment for chronic diseases, the need to improve diagnosis accuracy and the importance of prioritizing prevention in defining a roadmap towards value-based care.
The cognitive era is here
IBM CEO Ginni Rometty traveled to Orlando to offer one of the most hyped keynote sessions throughout these four days in February. Rometty noted this is a “a profoundly hopeful moment in time”, as the development of cognitive computing is bringing the opportunity to transform healthcare, bridging the gap between data and intelligence-informed strategies.
IBM is placing big bets on AI. “Cognitive healthcare is real, and it can change almost everything about healthcare”, Rometty said. “A competitive advantage is going to come from being cognitive. And this is not consumer-orientated, but something that really augments the intelligence on everyone in healthcare.”
Rometty went on to detail several case studies in which IBM’s Watson cognitive technology has impactfully contributed to improving patient outcomes. For instance, Barrow Neurological deployed IBM’s Watson AI solutions to identify new genes linked to Amyotrophic Lateral Sclerosis (ALS), uncovering five genes that had never before been connected to the disease.
Moreover, Rometty pointed to work already underway in China and India, densely populated nations where doctors are reducing the time it takes to gather patient data from 20 minutes to 20 seconds by using IoT.
She also highlighted IBM Watson’s partnership with the University of North Carolina’s Lineberger Comprehensive Cancer Center as a key example of the impact of cognitive computing on precision medicine: “In a thousand cases, and these were not standard cases, on almost 100 percent of the cases, doctors and Watson matched. But, in 30 percent, Watson found more clinically actionable items. That, to me, is what this is all about.”
IBM also took the opportunity to announce an agreement with Atrius Health to integrate cognitive capabilities into EHRs to deliver insights clinicians can use when treating patients at the point of care.
Building through collaboration
Every year, the leading IoT innovators gather at HIMSS’ exhibitions floor to update the medical industry on their latest achievements and developments. But as Travis Frosch, GE Healthcare’s director for analytics and cybersecurity pointed out, learning and development in healthcare IoT is a two-way street, and tech vendors know that innovation always stems from a specific problem currently faced in the medical sector.
Frosch insisted on the importance of following the money when innovating: “You really need to understand the problem you’re trying to solve. Is it a specific cost out of your system that doesn’t make sense? Are you over testing patients for no reason? Is it unnecessary visits to the Emergency Room? Is it claims denial?”
GE Healthcare has recently found that hospitals, on average, lose between 2 percent and 5 percent of net patient revenue to avoidable claims denials. Those denials are fixable with the help of DenialsIQ, an advanced analytics solution that uses machine learning capabilities to identify correctable denials and their cause.
“So one thing that is really important is the connectivity [that is necessary] to get the data, and you see a lot of start-ups that have innovative ways to connect and get data, but essentially, where we see a large competitive struggle is in the infrastructure. They [start-ups] may have the brain power, but they don’t have the body behind that. We have the industrial assets and the digital layer on top of that. We’re literally mining the industrial data from over half a million connected devices, in healthcare alone, to reduce cost and innovate on clinical effectiveness”, Frosch said.
IoT knowledge is transferable
Frosch also pointed out the importance of identifying transferable lessons across industries. “One tremendous asset we have at GE Healthcare is we’re building everything on the same platform, Predix. So that allows us to stimulate transferable lessons and learn from different industries.”
The Center for Digital Health Innovation at the University of California, San Francisco and GE Healthcare have collaborated to develop a library of deep learning algorithms that can empower clinicians to make faster and more effective decisions about the diagnosis and management of patients with some of the most common and complex medical conditions. These algorithms can be deployed worldwide via the GE Health Cloud and smart GE imaging machines.
“If we see an aviation algorithm that we think is useful, we can grab that algorithm, snap it into our solution and use the same orchestration engine. It’s like building a house out of Legos. Hey, you have a door on your part of the business – we need a door, too. Let’s grab that Lego door and snap it in there and we’re off and running. That’s one advantage we have as a big company; to utilize our breadth and our depth, but also our speed and our common infrastructure,” Frosch said.