Literature DB >> 25712502

Detection and Correction of Laterality Errors in Radiology Reports.

Young Han Lee1, Jaemoon Yang, Jin-Suck Suh.   

Abstract

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.

Mesh:

Year:  2015        PMID: 25712502      PMCID: PMC4501963          DOI: 10.1007/s10278-015-9772-x

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


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