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Managing Repeat Digital Radiography Images—A Systematic Approach and Improvement

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Abstract

Repeat analysis is an important issue for improving image quality in the field of radiology. However, the required data for repeat analysis is not easy to collect, and the accuracy of the analysis results remains controversial. The main purpose of this study is to introduce a systematic approach and, with the assistance of information technology, to improve the accuracy of data collection methods and repeat analysis in a fully digital environment. Another purpose of the study was to reduce the human resources required to maintain image quality on a daily basis. The main participant in this study is the radiology department of a medical center in Taiwan. The hospital had previously implemented a Picture Archiving and Communication Systems (PACS), which was seamlessly integrated with Radiology Information Systems (RIS) and Hospital Information Systems (HIS). A comprehensive mechanism was built for repeat analysis. The analysis was primarily achieved through comparing the difference between the amount of accumulated digital radiography (DR) images and uploaded PACS images with data mining tools. Initially, the radiologic technologists seemed to be resistant to the new quality assurance mechanism, which introduce inaccuracy into the collected data. However, after introducing the improved standard operating procedures with the proposed approach for radiologic technologists, the number of DR images generated became optimal for comparison with the number of PACS images, which made this mechanism feasible. Furthermore, information was collected regarding the reasons for repeat images and was used for improving image quality. The results revealed that the new mechanism was both effective and accurate in the analysis of repeat images.

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Correspondence to Huang-Wei Lin.

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Tzeng, WS., Kuo, KM., Liu, CF. et al. Managing Repeat Digital Radiography Images—A Systematic Approach and Improvement. J Med Syst 36, 2697–2704 (2012). https://doi.org/10.1007/s10916-011-9744-8

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  • DOI: https://doi.org/10.1007/s10916-011-9744-8

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