Managing Repeat Digital Radiography Images–A Systematic Approach and Improvement

doi:10.1007/s10916-011-9744-8

CNU IR > College of Smart Living > Dept. of Information Management > Periodical Articles > Item 310902800/26952

Please use this identifier to cite or link to this item: https://ir.cnu.edu.tw/handle/310902800/26952

Title:	Managing Repeat Digital Radiography Images–A Systematic Approach and Improvement
Authors:	Tzeng, Wen-Sheng Kuo, Kuang-Ming Liu, Chung-Feng Yao, Huan-Chung Chen, Chin-Yu Lin, Huang-Wei
Contributors:	資訊管理系
Date:	2011-05
Issue Date:	2013-09-28 16:25:28 (UTC+8)
Publisher:	Springer
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.
Relation:	Journal of Medical Systems 36(4), pp.2697-2704
Appears in Collections:	[Dept. of Information Management] Periodical Articles

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