What is the appropriate measure of radiology workload: Study or image numbers?
Journal Title
Journal of Medical Imaging and Radiation Oncology
Publication Type
Online publication before print
Abstract
INTRODUCTION: Previous studies assessing the volume of radiological studies rarely considered the corresponding number of images. We aimed to quantify the increases in study and image numbers per radiologist in a tertiary healthcare network to better understand the demands on imaging services. METHODS: Using the Picture Archiving and Communication System (PACS), the number of images per study was obtained for all diagnostic studies reported by in-house radiologists at a tertiary healthcare network in Melbourne, Australia, between January 2009 and December 2022. Payroll data was used to obtain the numbers of full-time equivalent radiologists. RESULTS: Across all modalities, there were 4,462,702 diagnostic studies and 1,116,311,209 images. The number of monthly studies increased from 17,235 to 35,152 (104%) over the study period. The number of monthly images increased from 1,120,832 to 13,353,056 (1091%), with computed tomography (CT) showing the greatest absolute increase of 9,395,653 images per month (1476%). There was no increase in the monthly studies per full-time equivalent radiologist; however, the number of monthly image slices per radiologist increased 399%, from 48,781 to 243,518 (Kendall Tau correlation coefficient 0.830, P-value < 0.0001). CONCLUSION: The number of monthly images per radiologist increased substantially from 2009 to 2022, despite a relatively constant number of monthly studies per radiologist. Our study suggests that using the number of studies as an isolated fundamental data set underestimates the true radiologist's workload. We propose that the increased volume of images examined by individual radiologists may more appropriately reflect true work demand and may add more weight to future workforce planning.
Keywords
burnout; picture archiving and communication system; productivity; radiology; workload
Department(s)
Cancer Imaging
Open Access at Publisher's Site
https://doi.org/10.1111/1754-9485.13713
Terms of Use/Rights Notice
Refer to copyright notice on published article.


Creation Date: 2024-07-25 05:42:23
Last Modified: 2024-07-25 05:52:23

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