As a means toward optimizing scheduling, researchers developed a model to predict study turnaround times (TAT = final report completion time) based on the scheduled complement of radiologists working in a large pediatric radiology fellowship program.

They included 397,806 radiographs in the data analysis. The team noted the model predicted an increase in the rolling seven-day mean TAT from June to September each year, which they suggest may have been due to the onboarding of new fellows. Ultimately, the model helped predict study volume with a high level of accuracy, yet prediction forecasts for shift turnaround times require further development, the team found.

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