Full Resolution Simulation for Evaluation of Critical Care Imaging Interpretation; Part 2: Random Effects Reveal the...

To further characterize empirical data from a full-resolution simulation of critical care imaging coupled with post hoc grading of resident's interpretations by senior radiologists. To present results from estimating the random effects terms in a comprehensive mixed (hierarchical) regression model.

After accounting for 9 fixed effects detailed in Part 1 of this paper, we estimated normally distributed random effects, expressed in terms of score offsets for each case, resident, program, and grader.

The fixed effects alone explained 8.8% of score variation and adding the random effects increased explanatory power of the model to account for 36% of score variation. As quantified by intraclass correlation coefficient (ICC = 28.5%; CI: 25.1-31.6) the majority of score variation is directly attributable to the case at hand. This "case difficulty" measure has reliability of 95%. Individual residents accounted for much of the remaining score variation (ICC = 5.3%; CI: 4.6-5.9) after adjusting for all other effects including level of training. The reliability of this "resident competence" measure is 82%. Residency training program influence on scores was small (ICC = 1.1%; CI: 0.42-1.7). Although a few significantly high and low ones can be identified, reliability of 73% militates for caution. At the same time, low intraprogram variation is very encouraging. Variation attributable to differences between graders was minimal (ICC = 0.58%; CI: 0.0-1.2) which reassures us that the method of scoring is reliable, consistent, and likely extensible.

Full resolution simulation based evaluation of critical care radiology interpretation is being conducted remotely and efficiently at large scale. A comprehensive mixed model of the resulting scores reliably quantifies case difficulty and resident competence.