Radiologists use “variable and complex” language to describe normal thyroid glands in chest CT reports, according to a new study published in the Journal of the American College of Radiology. Could this have a negative effect on patient comprehension?
Researchers from the department of radiology at Duke University Medical Center in Durham, North Carolina, studied data from more than 11,000 noncontrast chest CT radiology reports created in 2016. The word “thyroid” was used more than 8,000 times. After removing duplicate sentences, duplicate phrases and instances “that did not make descriptive or diagnostic statements about the thyroid,” the authors determined there were 342 unique descriptors for a normal thyroid.
Examining the sentences that include these descriptors, the authors found that the mean composite grade level (CGL) was 16.4.
“We found substantial variability in sentence and phrase length and linguistic readability indices,” wrote lead author Ryan G. Short, MD, and colleagues. “Additionally, our results suggest that, on average, descriptors for a normal thyroid gland are written at an advanced college level.”
These findings, the authors suggested, represent a significant problem with many modern radiology reports.
“Although the imaging finding of a normal thyroid gland, in general, requires no clinical action and may be of little clinical consequence, the variability and complexity of descriptors used to characterize this single and seemingly simple normal structure may be a surrogate for the broader readability of radiology reports,” the authors wrote. “That is, in current reporting practices, imaging findings are often described in obtuse and perhaps unnecessarily complex terms.”
This “variable and complex” language used by radiologists, combined with the high reading level of that language, could potentially have a negative impact on patient comprehension, Short and colleagues concluded.
“Further quantitative analysis of radiology reporting language, as well as the downstream implications of language on patient comprehension, may provide additional insight and incentive for improving radiologist-patient communication,” the authors wrote.
Michael has more than 16 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.