A majority of recently published imaging advances can directly contribute to patient care but nearly 50% would increase radiologists’ already growing workloads.
That’s according to Dutch researchers who analyzed a random sample of more than 400 medical imaging studies published in the field’s top peer-reviewed journals. More than 60% of all innovations could enhance care across academic and non-academic hospitals, but 48% would add to providers’ responsibilities, the team reported Tuesday in Insights into Imaging.
Artificial intelligence-related developments were significantly associated with an increase in tasks, with greater interpretation time requirements and added post-processing and acquisition times also top contributors.
The study is merely a qualitative analysis, without solid quantitative data. But authors Thomas C. Kwee, with the University of Groningen's Department of Radiology, and Robert M. Kwee, of Zuyderland Medical Center’s radiology department, both believe their investigation can serve as a baseline caution for modern radiology departments around the globe.
“Implementing recent scientific innovations and advances in knowledge in diagnostic radiology practice may benefit patient care, but, as demonstrated by the present study, further increases workload,” the pair wrote. “Without any intervention, the continuous addition of workload that aims to improve patient care will eventually turn into work overload that may jeopardize the quality and safety of patient care,” they added later.
For their analysis, the Kwees included 440 studies published in top journals such as Radiology, JACR, JAMA, Lancet, and many others, in 2019. Two radiologists assessed each case to determine if the study could directly contribute to care in their radiology practice.
About 65% of the studies would affect patients treated in academic tertiary care centers, as opposed to 63% in non-academic hospitals, the authors reported.
Across both practice types, about 46% would not change radiology department workloads, with 48% increasing duties and 4% reducing responsibilities.
In about 75% of cases, the increase was attributed to existing imaging tools requiring longer interpretation times, often accompanied by extended post-processing and acquisition needs. Up to 25% of studies involved introducing an entirely new imaging application.
Artificial intelligence tools were significantly associated with workload increases, the authors noted, with about 86% of studies boosting provider tasks.
More research will be required to back up their findings, but Kwee et al. say their results indicate a need to hire more radiologists and avoid using AI to guide future decisions.
“We believe that there is currently no scientific basis for policymakers to use AI as a reason to refrain from expanding the radiology workforce or to cut reimbursements for imaging procedures,” the pair wrote.
Read the full analysis here.
Matt joined Chicago’s TriMed team in 2018 covering all areas of health imaging after two years reporting on the hospital field. He holds a bachelor’s in English from UIC, and enjoys a good cup of coffee and an interesting documentary.