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基于智慧医疗的医院消毒供应室医用设备清洗质量控制管理

Cleaning Quality Control Management of Medical Equipment in Hospital Disinfection Supply Room Based on Smart Medicine.

机构信息

Central Sterile Supply Department, Yiwu Central Hospital, Jinhua 322000, Zhejiang, China.

出版信息

Comput Intell Neurosci. 2022 Aug 5;2022:4380735. doi: 10.1155/2022/4380735. eCollection 2022.

Abstract

With the continuous improvement of medical level, the demand for medical devices increases year by year, and it is necessary to track the quality and safety of medical devices. Establishing the cleaning quality control management of medical devices can not only reduce medical accidents and inhibit the spread of counterfeit or substandard medical devices but also help enterprises find the source of problems, determine the flow of the same batch of products, and warn relevant enterprises to take measures after the occurrence of problem products, and ultimately ensure the rights and interests of consumers. This study aims to study the cleaning quality control management of medical equipment in the hospital disinfection supply room based on smart medical care and proposes related concepts of smart medical care, as well as related theories of Internet of Things technology and medical equipment tracking system and related concepts of medical equipment cleaning. In this study, by comparing the cleaning compliance rates of the two groups of medical devices through smart medical care, it can be seen that 100% of the research group applying program-based management is significantly higher than 76.6% of the conventional management path. There was statistical significance in the data comparison between groups ( < 0.05). Therefore, programmatic management is more targeted than conventional management paths.

摘要

随着医疗水平的不断提高,医疗器械的需求逐年增加,有必要对医疗器械的质量和安全性进行跟踪。建立医疗器械清洗质量控制管理,不仅可以减少医疗事故,抑制假冒伪劣医疗器械的传播,还可以帮助企业找到问题的根源,确定同批产品的流向,并在问题产品发生后警告相关企业采取措施,最终保障消费者的权益。本研究旨在基于智慧医疗研究医院消毒供应室医疗器械的清洗质量控制管理,并提出智慧医疗的相关概念,以及物联网技术和医疗器械跟踪系统的相关理论和医疗器械清洗的相关概念。在本研究中,通过比较两组医疗器械通过智慧医疗的清洗合格率,应用基于程序的管理组的 100%明显高于常规管理路径的 76.6%。组间数据比较有统计学意义(<0.05)。因此,程序管理比常规管理路径更有针对性。

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