Investment in machine learning and artificial intelligence is ramping up across the healthcare industry as multiple players all look to tap into the benefits of deep neural networks and other forms of data-driven analysis.

A number of forward-looking provider organizations made strides with AI in 2019, including Summa Health, a nonprofit health system in Northeast Ohio, and Sutter Health, a health system based in Sacramento, California, to name just two.

Administrative process improvements

Looking forward into 2020, administrative process improvements are expected to be an investment priority, including technologies to help automate business processes like administrative tasks or customer service.

Many in the healthcare ecosystem already are on their way. An October Optum survey of 500 U.S. health industry leaders from hospitals, health plans, life sciences and employers, found 22% of respondents are in the late stages of AI strategy implementation.

According to an Accenture report, growth in the AI healthcare market is expected to reach $6.6 billion by 2021 – a compound annual growth rate of 40% – and the analyst firm predicts that when combined, key clinical health AI applications could potentially create $150 billion in annual savings for the U.S. healthcare economy by 2026.

“Return on investment will be the driving force for AI investments in 2020 for health systems,” Kuldeep Singh Rajput, CEO and founder of Boston-based Biofourmis, told Healthcare IT News. “I anticipate that 2020 will be a breakout year for AI investment – but by that, I mean investment by health systems in the right types of AI-driven technology.”

AI and the Triple Aim

He said when health system leaders consider an AI-driven technology, especially in the emerging value-base care environment, they will give the highest priority to AI technologies that achieve the Institute for Healthcare Improvement’s Triple Aim: improving the patient experience of care, including quality and satisfaction; improving the health of populations; and reducing the per capita cost of healthcare.

“Generally speaking, the most powerful and effective types of AI are leveraged to power technologies that bring true clinical and financial ROI – such as digital therapeutics with AI-driven predictive analytics as well as a machine learning component,” Rajput said. “Digital therapeutics powered by AI enable more informed clinical decision making and earlier interventions.”

For example, in patients diagnosed with heart failure, health systems can leverage digital therapeutics to follow them after discharge from the hospital or following an ER visit.

By applying AI-driven predictive analytics to non-clinical and clinical parameters collected via clinical-grade sensors worn by patients in their homes, providers can predict decompensation by detecting subtle physiologic changes from a participant’s personalized baseline, he added. This means interventions can occur two to three weeks earlier than they would have otherwise, potentially preventing a major medical crisis.

Real-world AI ROI

“This real-world, rather than theoretical, application of AI also brings real-world ROI, which is attractive to clinical leaders such as CEOs, CIOs and CFOs when they are looking at potential investments in AI,” he said.

Nathan Eddy is a healthcare and technology freelancer based in Berlin.
Email the writer: nathaneddy@gmail.com
Twitter: @dropdeaded209