ORIGINAL RESEARCH article
Front. Public Health
Sec. Disaster and Emergency Medicine
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1553113
Improving Precision Instrument Cleaning with a Quality Control Module: Implementation and Outcomes
Provisionally accepted
- 1Second Affiliated Hospital of Nanchang University, Nanchang, China
- 2School of Nursing, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi Province, China
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AbstractObjective: To evaluate the effectiveness of a cleaning quality control module integrated into a hospital’s Disinfection Supply Center (DSC) for improving the cleaning quality of precision surgical instruments.Methods: In June 2023, a cleaning quality control module was implemented in our hospital’s DSC to optimize reprocessing procedures. This module recorded deviations through textual, photographic, and video records. A comparative cohort study was conducted on 3,000 instrument sets processed before (February to May 2023) and after (June to September 2023) the intervention. Additionally, 15 DCS technicians were assessed for theoretical understanding and practical proficiency. Statistical analyses compared cleaning success rates, clinical user satisfaction, and technicians’ performance.Results: Cleaning qualification rates for instrument surfaces, accessories, and lumens increased from 97.5%, 96.9%, and 95.8% to 99.9%, 99.2%, and 98.2%, respectively. ATP bioluminescence results also improved, with rates rising from 97.1%, 96.2%, and 94.9% to 99.1%, 98.7%, and 97.9%. Clinical technicians’ satisfaction rose from 91% to 99%. Technicians theoretical and operational scores improved from 89.20±3.35 to 97.10±1.55 and from 90.10±4.33 to 97.50±1.00, respectively. All differences were statistically significant (P<0.05).Conclusion: The cleaning quality control module significantly enhanced instrument cleaning quality, improved technicians training efficiency, enhanced departmental operational efficiency, extended instrument lifespan, and improved patient safety.
Keywords: Disinfection, Central Supply, Hospital, Quality control, artificial intelligence, Research
Received: 30 Dec 2024; Accepted: 24 Apr 2025.
Copyright: © 2025 Tu, Xiong, Jiang, Wan, Zuo and Rao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dong Xia Rao, Second Affiliated Hospital of Nanchang University, Nanchang, China
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