Dr. Aalpen Patel, a medical director of artificial intelligence at Geisigner Medical Center, is working with an AI company to identify high-risk patients and screen them early. (Source: Geisinger)

Medical Director: AI Program Uses Medical Test Data to Treat Serious Conditions Early

A new AI program is helping to identify life-threatening conditions much faster than hospitals are currently doing so, according to Dr. Aalpen Patel, the Medical Director of AI and Chair of Radiology at Geisinger Medical Center, who was interviewed by Bill Siwicki of healthcareitnews.com. The program has been instituted at Geisinger.

Dr. Patel said the institution is applying algorithms in analyzing screening tests with tremendous results. The screenings identify patients with higher risks and then they are scanned for such conditions as abdominal aortic aneurysms (AAA), lung cancer, colorectal cancer, breast cancer and strokes. Identifying these at-risk patients is already having results. Since January, the hospital developed a system using lab parameters, demographics and electronic health record data, working with the AI platform Medial EarlySign. After reviewing scans of 500 AAA patients, the program has accurately identified 40 patients with the dangerous condition.

“For example, when we risk stratified the patients, it’s one in 13 patients who have some positive finding in doing a colonoscopy, that is about eight times higher than the average population,” Dr. Patel said. “Similarly, we have a program where we look at abdominal aortic aneurysm (AAA), where we look at some labs and some EHR data to see who’s at risk for developing or having AAA, and when we do ultrasound screening on those folks.”

Dr. Patel said he thinks the AI model makes it four times more likely that conditions in at-risk patients will be discovered early.

Because the systems use generative AI, Patel said he thinks it will work more effectively to find new ways of using data to follow up with patients beyond initially identifying an issue.

Geisinger physicians have developed a collaborative program called STAIR (System to Track Abnormalities of Importance Reliably).

“The STAIR program, for example, will make sure if a lung nodule is 4mm big, that patient does not get a follow-up. If there is a low risk, then that person just goes to their primary care doctor. Or if it does require follow-up, then STAIR reschedules a CT scan. But if it requires a visit to the pulmonologist, then STAIR will schedule that, as well.”

This referral system will lead to more comprehensive and effective care, Patel said.

“What it also does is not only take care of patients well longitudinally and make sure we’re not dropping the ball on this patient, but also allows us to reduce the unnecessary referrals to our specialty care and allow us to improve access,” he said. “No. 1, we’re doing longitudinal care better. No. 2, we’re improving access for those patients and using resources appropriately.”

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