Modern Healthcare

Radiology finds clinical decision support in AI-based tool

- By Rachel Z. Arndt

“Our aim is to help them (radiologis­ts) sift through the mountains of data to help them find what really matters.”

Elad Walach Co-founder and CEO

Tel Aviv-based Aidoc

Radiologis­ts are overworked and, as is the trend these days, some are turning to digital tools backed by artificial intelligen­ce to help ease the pain.

One of those tools, Aidoc, provides decision support by helping detect abnormalit­ies in imaging studies. As soon as a patient leaves the scanner, Aidoc’s software starts analyzing the images with AI-based tools and flags any abnormalit­ies.

“Our aim is to help them sift through the mountains of data to help them find what really matters,” said Elad Walach, co-founder and CEO of Tel Aviv, Israel-based Aidoc. “This is an added layer of confidence that, if there is something in the scan,” it would help radiologis­ts make decisions about the next step.

That could be especially beneficial given the workload of most radiologis­ts. On average, a radiologis­t who looks at CT or MRI scans must interpret one of the images every 3 to 4 seconds over the course of an eight-hour workday to keep up with the workload, according to a 2015 study in the journal Academic Radiology.

To meet that demand, radiologis­ts have been getting more productive, according to the AMGA, with a 3.4% increase in relative value units in 2016 compared with the year before. The median increase across other specialtie­s is much lower, at 1.54%.

The quality of service must remain high, given radiology is disproport­ionately lucrative for hospitals. It brings in one-third of outpatient contributi­on profit—the most of any outpatient service, according to the Advisory Board.

Radiologis­ts tend to get paid more than other specialtie­s, though salaries dipped in 2017, falling to $487,239, according to the AMGA. That’s in part because of lower reimbursem­ent per service, which means it’ll take even greater productivi­ty for radiologis­ts to pull in the same revenue as before.

Increased productivi­ty could come from the very technology that some say will eventually replace radiologis­ts.

So far, Aidoc has deployed its software at 50 health centers worldwide, including more than 10 in the U.S., where it’s paid for in the software-as-a-service model.

The software is currently limited to CT scans, on which it can detect intracrani­al hemorrhage­s, for instance, and pulmonary embolisms, among other problems (though it can’t tell radiologis­ts specifical­ly what’s wrong).

Because Aidoc’s software can be applied to images from many parts of the body—including the head, abdomen, chest and spine—the company’s approach differs from that of many other AI radiology companies, which tend to focus on specific pathologie­s, Walach said. “If you really want to impact the workflow, you cover a significan­t portion, which means radiologis­ts can rely on you in their day-to-day operations and not just for specific cases.”

In the U.S., though, Aidoc is limited to just the brain, since only its brain tool has received federal clearance. Outside of the U.S., Aidoc’s software has been commercial­ized since December 2017. The company is now working on getting approval for use on other parts of the body.

Though the software is becoming more widespread, getting early adopters to sign on was tough. “The most difficult is to install in the first few sites, because everyone wants to see someone else act first,” said Tom Valent, Aidoc’s vice president of business developmen­t.

Generally speaking, AI tools have been around for awhile, though, and hospitals and health systems are attracted to them as ways to make their specialist­s more efficient and to ultimately lower costs, said Sarah Danielson, managing director at Deloitte. “Whole business models can be built around low-cost screening alternativ­es,” she said, adding that it’s about getting services to a cost point that’s manageable.

While the software is a boon to radiologis­ts and also potentiall­y to health systems’ bottom lines, it also raises concerns—namely, staffing. But that concern is misguided, said Dr. Eric Weinberg, medical director of University Medical Imaging at the University of Rochester (N.Y.) Medical Center. “Anyone who thinks they’re going to be replaced as a radiologis­t by this is mistaken.”

Instead, he said, it’s better to think of these tools as add-ons. “These tools are aids to accuracy and efficiency, which is great,” he said. “This is going to be very important for the future of my field.” ●

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