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Radiologist Productivity Analytics: Factors Impacting Abdominal Pelvic CT Exam Reporting Times

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Abstract

The purpose is to determine factors impacting radiologist abdominal pelvic CT exam reporting time. This study was Research Ethics Board approved. Between January 2019 and March 2020, consecutive abdominal pelvic CT exams were documented as structured or unstructured based on application of templates with separate sections for different organs or organ systems. Radiologist reporting location, patient class (inpatient, Emergency Department (ED) patient, outpatient), radiologist fellowship-training, report word count, and radiologist years of experience were documented. Median reporting times were compared using the Wilcoxon Rank-sum test, Kruskal–Wallis test, and regression analysis. Spearman’s rank correlation was used to determine correlation between word count and radiologist experience with reporting time. P < 0.05 is defined statistical significance. A total of 3602 abdominal pelvic CT exam reports completed by 33 radiologists were reviewed, including 1150 outpatient and 2452 inpatient and Emergency Department (ED) cases. 1398 of all reports were structured. Median reporting time for structured and unstructured reports did not differ (P = 0.870). Reports dictated in-house were completed faster than reports dictated remotely (P < 0.001), and reports for inpatients/ED patients were completed faster than for outpatients (P < 0.001). Reporting time differences existed between radiologists (P < 0.001) that were not explained by fellowship training (P = 0.762). Median reporting time had a weak correlation with word count (ρ = 0.355) and almost no correlation with radiologist years of experience (ρ = 0.167), P < 0.001. Abdominal pelvic CT reporting is most efficient when dictations are completed in-house and for high-priority cases; the use of structured templates, radiologist fellowship training, and years of experience have no impact on reporting times.

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Data Availability

All data can be made available upon request and in accordance with our institutional research ethics board.

Code Availability

Not applicable.

Abbreviations

ACR:

American College of Radiology

ICES:

Institute for Clinical Evaluative Sciences

IQR:

Interquartile range

PACS:

Picture Archiving and Communication System

PHI:

Personal Health Information

RSNA:

Radiological Society of North America

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Author information

Authors and Affiliations

  1. Department of Diagnostic Imaging, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, 711 Concession St, Hamilton, ON, L8V 1C3, Canada

    Amar Udare, Minu Agarwal, Michael Patlas, Yoan K. Kagoma & Christian B. van der Pol

  2. Vector Institute for Artificial Intelligence, MaRS Centre, West Tower, 661 University Ave, Suite 710, Toronto, ON, M5G 1M1, Canada

    Kiret Dhindsa

  3. Thunder Bay Regional Health Sciences Centre, 980 Oliver Rd, Thunder Bay, Hamilton, ON, P7B 6V4, Canada

    Amer Alaref & Christian B. van der Pol

  4. Department of Diagnostic Imaging, St. Joseph’s Healthcare, 50 Charlton Ave E, Hamilton, ON, L8N 4A6, Canada

    Abdullah Alabousi

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  1. Amar Udare
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Corresponding author

Correspondence to Christian B. van der Pol.

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Ethics Approval

The Hamilton Integrated Research Ethics Board reviewed the protocol for this retrospective study and granted an exemption from formal ethics review.

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Not applicable.

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The authors declare no competing interests.

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Appendices

Appendix A.1:

Post-hoc power analysis for structured reporting

To establish power for the Wilcoxon rank-sum test a Monte Carlo simulation was used to empirically estimate the power. The truncated Gaussian was the best fitting distribution when using log10 of the data to account for the extreme upper end. Fit distributions, one for structured reporting and one for non-structured reporting, were used to generate the same samples sizes distributed like the real data before running a Wilcoxon rank sum test which was done 10,000 times. The medians were not significantly different 9,524 times, which suggests the power is approximately 0.9524. This implies the probability of finding a reporting time difference between structured and unstructured reporting if one existed in our cohort was >95%.

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Udare, A., Agarwal, M., Dhindsa, K. et al. Radiologist Productivity Analytics: Factors Impacting Abdominal Pelvic CT Exam Reporting Times. J Digit Imaging 35, 87–97 (2022). https://doi.org/10.1007/s10278-021-00548-w

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  • DOI: https://doi.org/10.1007/s10278-021-00548-w

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