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使用混合方法对药物不良事件改善优先级中的人为错误进行的调查。

An Investigation of Human Errors in Medication Adverse Event Improvement Priority Using a Hybrid Approach.

作者信息

Hsieh Min-Chih, Chiang Po-Yi, Lee Yu-Chi, Wang Eric Min-Yang, Kung Wen-Chuan, Hu Ya-Tzu, Huang Ming-Shi, Hsieh Huei-Chi

机构信息

Department of Industrial Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 30013, Taiwan.

出版信息

Healthcare (Basel). 2021 Apr 9;9(4):442. doi: 10.3390/healthcare9040442.

DOI:10.3390/healthcare9040442
PMID:33918754
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8069284/
Abstract

The aim of this study was to analyze and provide an in-depth improvement priority for medication adverse events. Thus, the Human Factor Analysis and Classification System with subfactors was used in this study to analyze the adverse events. Subsequently, the improvement priority for the subfactors was determined using the hybrid approach in terms of the Analytical Hierarchy Process and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution. In Of the 157 medical adverse events selected from the Taiwan Patient-safety Reporting system, 25 cases were identified as medication adverse events. The Human Factor Analysis and Classification System and root cause analysis were used to analyze the error factors and subfactors that existed in the medication adverse events. Following the analysis, the Analytical Hierarchy Process and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution were used to determine the improvement priority for subfactors. The results showed that the decision errors, crew resource management, inadequate supervision, and organizational climate contained more types of subfactors than other error factors in each category. In the current study, 16 improvement priorities were identified. According to the results, the improvement priorities can assist medical staff, researchers, and decisionmakers in improving medication process deficiencies efficiently.

摘要

本研究的目的是分析药物不良事件并提供深入的改进优先级。因此,本研究采用带有子因素的人为因素分析与分类系统来分析不良事件。随后,运用层次分析法和模糊理想解排序法相结合的方法确定子因素的改进优先级。从台湾患者安全报告系统中选取的157起医疗不良事件中,有25例被确定为药物不良事件。采用人为因素分析与分类系统和根本原因分析法,分析药物不良事件中存在的错误因素和子因素。分析之后,运用层次分析法和模糊理想解排序法确定子因素的改进优先级。结果表明,决策错误、团队资源管理、监督不足和组织氛围在每一类中包含的子因素类型比其他错误因素更多。在本研究中,确定了16个改进优先级。根据结果,改进优先级可帮助医护人员、研究人员和决策者有效改善用药流程缺陷。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d75b/8069284/f0b4621eb192/healthcare-09-00442-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d75b/8069284/45c3c6ababfc/healthcare-09-00442-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d75b/8069284/89503aba6dd1/healthcare-09-00442-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d75b/8069284/f0b4621eb192/healthcare-09-00442-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d75b/8069284/45c3c6ababfc/healthcare-09-00442-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d75b/8069284/89503aba6dd1/healthcare-09-00442-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d75b/8069284/f0b4621eb192/healthcare-09-00442-g003.jpg

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