During a CTO and CIO roundtable discussion at Medecision’s Liberation conference this past year, some of the industry’s brightest technology leaders discussed how modern technology is changing the healthcare landscape. Srini Gurrapu, vice president of products and design at Claris, discussed how big tech and artificial intelligence are disrupting healthcare.
Can machines think? English mathematician Alan Turing first asked that question in a 1950 paper titled, “Computing Machinery and Intelligence.” In that landmark paper, he proposed what’s now known as the “Turing Test”—a practical way of determining whether a computer has achieved human levels of intelligence. Now, 70 years later, machine learning and artificial intelligence (AI) are used in almost every sector of the $3.7 trillion healthcare industry to automate many administrative, financial and operational tasks.
It’s safe to say that AI and machine learning are disrupting the way healthcare is delivered. During a CTO and CIO roundtable discussion at Medecision’s Liberation conference this past year, some of the industry’s brightest technology leaders discussed how modern technology is transforming the healthcare landscape.
To kick off his turn at the mic, Srini Gurrapu, vice president of products and design at Claris, asked the audience Turing’s same question—“Can machines think?”
“With all the advancements happening with Siri, Alexa and Google, I believe we’re getting very close to this reality,” Gurrapu suggested.
In his presentation, Gurrapu discussed what he referred to as “big tech’s disruption in healthcare” or, rather, advancements in the healthcare industry that are driven by modern technology.
“Healthcare is going to be largely defined by data and practitioners coming together to facilitate better opportunities,” he said.
“Big tech” is a term commonly used to describe major technology companies, such as Facebook, Apple, Google, Amazon and Microsoft. These companies are “accelerating their pursuit of the healthcare market,” according to a report in Business Insider Intelligence. Among Fortune 500 companies, 84% now have healthcare capabilities. Consumers already trust companies like Apple and Amazon for products and rely on their solutions. However, the healthcare industry has been notoriously slow in adopting new technology for a myriad of reasons, including but not limited to, opposition from physicians, concerns about patient safety and exorbitant costs.
During his presentation, Gurrapu highlighted three themes found in big tech’s disruption of the industry as companies look to innovate via diagnostics, clinical trials and value-based care.
Disruption in Diagnostics
The use of AI software for clinical imaging and diagnostics is on the rise, due in part to the Food and Drug Administration (FDA) fast-tracking the approval process for AI and machine-learning devices. In the past, any new algorithm had to obtain permission or certification from the FDA—a lengthy process, Gurrapu explained. Now, fast-tracking regulatory approval is opening the door for many AI imaging and diagnostics companies, Gurrapu said.
Today, AI-powered medical devices and software are aiding physicians in making diagnoses, Gurrapu explained. “New AI-centric companies are developing algorithms to help with the detection of conditions such as heart disease, lung problems or other diseases,” he said. For example, Viz.ai uses AI to analyze CT scans and notify healthcare providers of patients in danger of strokes—reducing the delays that stand between patients and life-saving treatments.
Gurrapu also shared how neural networks—a set of algorithms modeled loosely after the human brain designed to recognize patterns and interpret sensory data—have the potential to spot atypical risk factors and identify unknown risk factors. For instance, researchers at Google used neural networks trained on retinal images to identify risk factors for cardiovascular disease. Another example is Cardiogram, which turns your wearable device into a continuous health and heart rate monitor. The app is trained to help detect conditions such as hypertension, sleep apnea, diabetes and atrial fibrillation.
Disruption in Clinical Trials
AI is also being used to revolutionize clinical trials. Despite efforts to digitize electronic health records, challenges with interoperability remain, Gurrapu explained. This can make it difficult to match patients with the right clinical trial, for instance.
Occasionally, a patient may get a recommendation or referral for a clinical trial from the physician. But more often, the patient is responsible for seeking the relevant clinical trials for their condition. However, Apple is seeking to make that process easier and open up new opportunities for patients looking to participate in clinical trials.
In 2015, Apple launched ResearchKit and CareKit, open-source frameworks that allow researchers to create medical apps to monitor daily lives—such as steps taken, heart rate and exercise—which can help clinical trial researchers more easily recruit patients and monitor their health remotely, Gurrapu explained.
The ResearchKit can also link to an individual’s HealthKit, and researchers can access relevant data needed for clinical trials, such as calorie counts, daily steps taken and resting heart rate. For instance, Novartis, a Switzerland-based pharmaceutical company, collaborated with Apple in 2018 to use the ResearchKit in clinical trials. FocalView, an ophthalmic digital research app created by Novartis with Apple ResearchKit, collects real-time, self-reported data from consenting patients to track and measure ocular disease progression.
Disruption in Value-based Care
AI is also changing the way the healthcare industry quantifies the quality of care patients receive in the hospital. As the healthcare industry shifts to a value-based care model—where healthcare providers are incentivized to provide the highest quality of care at the lowest possible cost—providers have been challenged with meeting quality performance measures. For example, in a value-based care model, hospitals have a financial incentive to reduce unnecessary medical or laboratory tests prescribed by physicians.
Gurrapu referenced Qventus, a startup that partnered with Arkansas-based Mercy Hospital, which is shifting to a value-based care model. Qventus developed an AI-based platform that helps reduce inpatient and emergency department stays and close the loop on medical operations. After working with Qventus, Mercy Hospital was able to save more than $3.5 million by reducing unnecessary lab tests—and prevent patients from undergoing unnecessary tests.
It’s hard to know just how much technology disruption we’ll see in healthcare, but as Gurrapu said, “this is a fascinating time to be in the software and technology industry.”
“I truly believe that the future of the healthcare industry is going to be a data scientist and doctor working together to create better outcomes for patients,” he said. “Five or 10 years from now, we’ll see that big tech means better outcomes for patients, better outcomes for insurance providers and happier doctors. Physicians will see their patients achieving better health outcomes.”