Like many developments in a world as complex as healthcare, the level of excitement one encounters over the development of AI really comes down to whom you to talk to. For example, many stakeholders point out that for all the hype, not a whole lot has changed yet.

On the other hand, there are those who are arguing that the hype surrounding AI isn’t so bad if you look at it from the right perspective.  One such enthusiast is Ashish Kachru, CEO and co-founder of Altruista Health, a care management and population health platform developer.

Writing recently at Forbes, Kachru sums up his enthusiasm by noting that while “the AI of any given time will never outpace the incredible capacity of the human mind to perform insanely complex tasks . . . (it) will spur us to think and act in ways that are more sophisticated once we are relieved of certain lower-complexity tasks.”

Unlike commentators who focus in on specific AI-driven changes to care delivery, Kachru takes a somewhat higher altitude view, noting that the healthcare sector “is undergoing a dramatic transformation to value-based care. Providers and health care organizations are assuming more financial risk for improving patient health outcomes, with stronger links between outcomes and reimbursement. This is a huge shift, and it’s creating enormous pressures, incentives, disincentives and unintended consequences in an already vast, fragmented and unpredictable industry that makes up nearly 18% of the U.S. economy. Information technology in this sector is attempting to leverage huge datasets in ways that create greater efficiency and better health. AI can wake up that data and bring it to life.”

Not surprisingly, given his business, Kachru lifts up the changes AI can bring to population health.

“AI works well in risk stratification for population health by teasing out the most medically complex and fragile sliver of the population accounting for the highest costs to the system,” he explains. “AI is being used to plot graphics of patient populations and focus intensive resources on the most vulnerable.”

Similarly, pointing to the focus on readmissions, Kachru reminds readers that “hospital readmissions within 30 days of discharge are one of the costliest failures of the healthcare system. In the past, the industry has used uniform discharge practices for entire patient populations, but there’s a new focus on targeting the riskiest patients for special interventions.

A current AI tool at the Children’s Hospital of Pittsburgh has been able to predict with 79% accuracy which patients are most at risk for a hospital readmission.”

Finally, for those who might succumb to sci-fi fears of an AI-darkened dystopian future, Karchru  points out that “the best way to influence patient behavior toward better health choices is to work with human emotion, which technology cannot do.”

In short, says Kachru, there are bound to be disappointments as AI makes its way into healthcare, but that doesn’t mean there’s no reason to buy the hype by keeping the longterm in sight. 

“Incremental progress for healthcare AI may not astonish,” he says with a bit of understatement, “but it is nonetheless very promising.”