AI & ML Intelligence

Punit Soni's company is a major player in this area of artificial intelligence. Here he gives advice to healthcare CAIOs, CIOs and other IT leaders implementing the systems – and to doctors and nurses using them. He sees big change coming to healthcare over the next five years.

The patient communication system powered by artificial intelligence handles routine calls, making way for life-and-death calls for matters like organ transplant to quickly get through to people who can make a difference.

At NeoGenomics, early outcomes support faster turnaround for results, a marked increase in throughput and high satisfaction rates among pathologists interpreting next-generation sequencing results.

The new plan directs the U.S. Department of Commerce to revise artificial intelligence risk management frameworks, which could undo protections that might be seen as "woke" in order to do business with the federal government.

"Even if these systems are right 80% of the time, that still means they're wrong 20% of the time," says tech CMO Dr. Jay Anders, who describes the risks of artificial intelligence errors and outlines some protection strategies for providers.

"A use case is generating an appeal letter – a domain change is reimagining revenue cycle management," explains Jessica Lamb, a partner at McKinsey & Company. She offers a primer on the rising technology.

While the open-source Seismometer tool does not provide ROI metrics, it can surface insights on an algorithm's quality and utility, say early users at Michigan Medicine.

Ernst & Young Health AI and Data Leader Sezin Palmer advises, among other things, to be strategic and selective, build with value and scale in mind, retool available talent, and work with consultants and vendors effectively.

Dr. Matt Crowson, the genAI expert at Wolters Kluwer Health, dives into the company's new survey of caregivers and execs on the technology and explains where hospitals and health systems need to do the work of getting it up and running properly.

The burden then shifts to hospitals, which puts clinicians in a tough spot, relying on AI that might not generalize, with no real way to track performance or course correct – that's an unacceptable blind spot, says one healthcare AI governance expert.