Will AI ultimately replace or assist radiologists?

by John R. Fischer, Senior Reporter | November 21, 2022
Artificial Intelligence X-Ray
From the November 2022 issue of HealthCare Business News magazine


And while CMS funding and designations such as the new technology add-on payment are a starting point, Allen says that a proper payment system is needed.

"There's not a good model for reimbursement, and CMS and other third-party payers may be questioning if AI adds value for patients in addition to what they already do. When we look at taking care of populations of people rather than our current transactional payment system, then AI becomes a resource that could make institutions more efficient. They would then gladly fund its implementation," he said.

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Additionally, most AI models are currently designed to detect only one finding, maybe two, in patients. This limits their ability to make accurate diagnoses, leading to delayed care.

“Does it just detect one thing, like pulmonary embolism, but not pneumonia if applied to the chest,” said Brink. “Is there a fracture? Is there a pulmonary embolism?” That doesn’t necessarily answer the more concrete question, “Is there an abnormality in this chest X-ray or is there an abnormality in this femur?”

Another problem, according to Erickson, is the limited ability of the technology to pull information from multiple sources. Most only use information from the pixels found in images they scan and do not incorporate background information from prior exams and medical records.

“The vast majority of radiology requires clinical information integration and/or other imaging examination information in order to really do a good job. That’s a much more challenging thing to do from an informatics perspective, and you need to train a more sophisticated AI model,” said Erickson.

Because of these limitations, many radiologists have been left scratching their heads on what true value AI offers radiology and how to incorporate it into their practice.

“All of these studies need to be looked at by a radiologist,” said Atalay. “It’s not clear to me how AI will alleviate the number of studies a radiologist has to look at or the time spent on them. But that’s the promise.”

Educating the next generation
In a study of 532 medical students, 23% said they would not pursue a career in radiology, because they believe AI will eventually replace radiologists and limit their future job prospects. One class was surveyed twice, with 50% in 2017 saying radiology was a no-go for them. This rose to 71% in 2021.

Atalay, who led the study, says this indicates a lack of awareness about the role that radiologists play and what the full scope of their work entails. In addition to interpreting images, a significant fraction of their day is spent on noninterpretive tasks such as protocoling exams; determining if a specific scan is safe, effective, and appropriate for individual patients; interacting with the technologists performing the exams; and discussing study indications and results with clinical colleagues.

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