Improvement of CT Target Scanning Quality for Pulmonary Nodules by PDCA Management Method

Dongquan Liu, Shaojun Zhu, Bangquan Liu, Dechao Sun and Fangqin Fei

Mathematical Problems in Engineering, 2021, vol. 2021, 1-9

Abstract:

High CT image quality is an important guarantee for doctors to correctly diagnose pulmonary nodules. The aim of this study was to explore the application value of PDCA management method in improving the quality of CT target scanning for pulmonary nodules. We identified 480 patients’ CT image with at least one pulmonary nodule admitted in Ninghai First hospital from September 1st, 2018, to April 30th, 2019. 240 CT images are carried out by the conventional target scanning method, and we analyzed the reasons for the low quality of some CT target scanning images of pulmonary nodules in the radiology department of our hospital. We established a new process of CT target scanning for pulmonary nodules based on the PDCA method and then tested 240 patients who were checked after January 1st, 2019. The excellent rate of CT target scanning image of pulmonary nodules in our department increased from 60.0% to more than 90.0%. The patients’ satisfaction with the examination was significantly higher than that without the implementation of PDCA management. The research result indicated that the process of CT target scanning image, postprocessing reconstruction, and numerical measurement of pulmonary nodules can be improved by standardized PDCA cycle, which benefits effectively improving the theoretical and operational skills of radiologists and significantly improving the image quality rate of CT target scanning of pulmonary nodules.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6632960

DOI: 10.1155/2021/6632960

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