By Aine Cryts

One of the greatest challenges facing radiologic technologists (RTs) today is the sheer amount of data they have to work with, says Mark O’Herlihy, managing director for EMEA at Cambridge, Mass.-based IBM Watson Health and a former diagnostic radiographer with the UK’s National Health Service (NHS).

His interest in physics and math—combined with a desire to work in healthcare while not wanting to be a physician—made a career as a diagnostic radiographer (the equivalent of a radiology technologist in the United States) the ideal fit, O’Herlihy tells AXIS Imaging News. No stranger to stressful work environments, he even served a stint as an advanced trauma radiographer and taught junior physicians to recognize patterns in x-rays.

An Influx of Technologies 

O’Herlihy points to the influx of new scanners and screening methodologies to highlight the complex environments that RTs routinely encounter. Plus, there are more diagnostic tests being done on patients than ever before, along with a wealth of scientific research to absorb.

Artificial intelligence can be a part of the solution for RTs who often make decisions that impact patients’ lives. Consider, for example, that most CTs are done at night after a patient experiences a potentially traumatic health emergency. And it’s at night when RTs are typically on their own, says O’Herlihy.

Artificial intelligence can serve as “another set of eyes” to look at the CT of a brain bleed, for example. It’s this real-time expert insight that can support the decision to transfer the patient to another hospital or refer them to a specialist, O’Herlihy insists.

Addressing Personnel Shortages in Healthcare

Acknowledging that RTs may be fearful that artificial intelligence platforms could displace them in their roles, O’Herlihy says one of the most profound challenges facing healthcare today is a shortage of people to treat and serve patients. He also points out that many healthcare workers aren’t operating at the top of their skill levels.

The value artificial intelligence brings to radiology is bolstering image sets and increasing the likelihood of an accurate diagnosis, he says. For example, technology is now available to track a tumor in images that have been captured over time. Making a quick and accurate assessment that a patient doesn’t need a biopsy is hugely valuable, adds O’Herlihy.

Harkening back to his comments about the vast amounts of data RTs must sort through on a regular basis, O’Herlihy notes that the more time an RT spends with the electronic health record or another technology platform means less time spent with patients.

AI will also change the practice of RTs’ radiologist colleagues, O’Herlihy predicts. Specifically, radiologists’ roles will evolve within the next five years since a majority of these physicians will be specialists, he says. And artificial intelligence will support them greatly, he projects.