Implementation of a read priority scoring system can have a positive impact on an institution’s report turnaround time (RTAT) and RTAT variability, according to a recent study published by the American Journal of Roentgenology.

Cree M. Gaskin, MD, department of radiology and medical imaging at the University of Virginia Health System in Charlottesville, and colleagues explained that common methods for imaging exam prioritization have several limitations. Providers, technologists and radiologists often use ambiguous language, for instance, sometimes leaving the priority of exams open to interpretation. Also, when priority is assigned based on the referring physician’s perspective, potentially important updates from the technologist may get completely overlooked.

Hoping to improve upon these flawed methods, Gaskin et al. developed and implemented their new model for imaging exam prioritization in 2011.

“This model is numeric to be more clearly hierarchic, includes clinical definitions to provide guidance at the point of care, and adds a second step in prioritization termed the “read priority” to be scored by the technologist on examination completion,” the authors wrote. “This read priority score encompasses the ordering provider's order priority, incorporates additional and updated clinical information, and follows consensus-driven clinical definitions.”

This new system worked well, Gaskin and colleagues reported. Exams were all given a read priority score (1-9, with 1 being the most urgent), and the research team noted yearly improvement in RTAT numbers from 2011 to 2014.

Exams in three most urgent priority levels (1, 2, and 3) improved in RTAT by 23 percent, 5 percent, and 70 percent, respectively, and just one priority level—level 4, “outpatient urgent”—was significantly worse.

Those three most urgent levels also showed improvement in RTAT variability. The one priority level that was significantly worse in terms of RTAT variability was level 9, the least urgent exams performed at the institution.

“RTAT and RTAT variability became stratified by level of priority, as we expected, likely because of the clear hierarchy offered by the numeric system,” the authors noted. “The importance of this simple concept is that measurable improvements in RTAT and variability should occur for high-priority studies. This hypothesis was substantiated in practice by our results that showed significant improvements in RTAT and variability for high-priority studies as radiologists adopted the model. Decreasing RTATs and limiting RTAT variability for the most urgent clinical scenarios are improvements in clinical quality.”

Gaskin and colleagues added that they did search for other explanations for the improvements in RTAT and RTAT variability.

“We considered potentially confounding contributors to our documented improvements in prioritization to increase our confidence that improvements were due to adoption of the read priority system by radiologists,” the authors wrote. “Because the number of radiologists was nearly static over the 4 years and because our clinical burden (i.e., number of studies per radiologist) was slightly less in the early adoption phase, improvements cannot be attributed to changes in work load volume.”

The authors said their research had limitations, including the fact that they were unable to accurately compare pre-implementation data with post-implementation data.

“However, we were still able to show significant gains by comparing results from an early period of minimal adoption to a later period of substantial but still incomplete adoption by the radiologists,” the authors wrote. “We suspect that this limitation still favors our results, because the lesser opportunity to show a gain still produced significantly positive results.”