Detection and Correction of Laterality Errors in Radiology Reports

Young Han Lee, Jaemoon Yang, Jin Suck Suh

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


The objectives of the study are to introduce the development of supervising software for double-checking of laterality error in radiology reports and to evaluate the usefulness of detection and correction software by applying it to radiology report systems. An AutoHotkey macro program was applied to the design for double-checking of laterality errors. The software was performed according to the flowchart below: (1) detecting laterality discrepancies between radiologic examination names and the context of the radiology report and (2) providing conditioned discrepancy correction with a pop-up window. The accuracy of the detection was evaluated with 300 radiologic examinations that include the intended discrepancies and concordance of lateralities. The number of detections and corrections were quantified, and the confidence intervals were calculated for accuracy. We also applied this module to previous radiology reports with laterality errors from the radiologic examination database to validate the module. The AutoHotkey-scripted macro program functioned well in the reading workstation, and it was acted successfully as additional software. The detection accuracy was 99.67 % (95 % CI; 99.01―%) in the 300 radiologic examinations from the radiologic reading session. There was one running failure, caused by a temporary lag in the hospital’s computer network, but no failures resulted during the second trial. We found that there were laterality errors in 0.048 % (n = 14/29,257) of the examinations from the database. We developed detection and correction software aimed at double-checking for laterality errors. This method can be successfully adopted in any hospital software and is expected to be included for a better radiologic reading environment.

Original languageEnglish
Pages (from-to)412-416
Number of pages5
JournalJournal of Digital Imaging
Issue number4
Publication statusPublished - 2015 Aug 26

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (2012R1A2A1A01011328). This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012R1A1A2042165). This work was presented at the 2013 RSNA (abstract ID, 13025220).

Publisher Copyright:
© 2015, Society for Imaging Informatics in Medicine.

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications


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