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A Hazard Analysis of Class I Recalls of Infusion Pumps

BACKGROUND: The adverse event report of medical devices is one of the postmarket surveillance tools used by regulators to monitor device performance, detect potential device-related safety issues, and contribute to benefit-risk assessments of these products. However, with the development of the rela...

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Detalles Bibliográficos
Autores principales: Gao, Xuemei, Wen, Qiang, Duan, Xiaolian, Jin, Wei, Tang, Xiaohong, Zhong, Ling, Xia, Shitao, Feng, Hailing, Zhong, Daidi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6524450/
https://www.ncbi.nlm.nih.gov/pubmed/31066695
http://dx.doi.org/10.2196/10366
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author Gao, Xuemei
Wen, Qiang
Duan, Xiaolian
Jin, Wei
Tang, Xiaohong
Zhong, Ling
Xia, Shitao
Feng, Hailing
Zhong, Daidi
author_facet Gao, Xuemei
Wen, Qiang
Duan, Xiaolian
Jin, Wei
Tang, Xiaohong
Zhong, Ling
Xia, Shitao
Feng, Hailing
Zhong, Daidi
author_sort Gao, Xuemei
collection PubMed
description BACKGROUND: The adverse event report of medical devices is one of the postmarket surveillance tools used by regulators to monitor device performance, detect potential device-related safety issues, and contribute to benefit-risk assessments of these products. However, with the development of the related technologies and market, the number of adverse events has also been on the rise, which in turn results in the need to develop efficient tools that help to analyze adverse events monitoring data and to identify risk signals. OBJECTIVE: This study aimed to establish a hazard classification framework of medical devices and to apply it over practical adverse event data on infusion pumps. Subsequently, it aimed to analyze the risks of infusion pumps and to provide a reference for the risk management of this type of device. METHODS: The authors define a general hierarchical classification of medical device hazards. This classification is combined with the Trace Intersecting Theory to form a human-machine-environment interaction model. Such a model was applied to the dataset of 2001 to 2017 class I infusion pump recalls extracted from the Food and Drug Administration (FDA) website. This dataset does not include cases involving illegal factors. RESULTS: The proposed model was used for conducting hazard analysis on 70 cases of class I infusion pump recalls by the FDA. According to the analytical results, an important source of product technical risk was that the infusion pumps did not infuse accurate dosage (ie, over- or underdelivery of fluid). In addition, energy hazard and product component failure were identified as the major hazard form associated with infusion pump use and as the main direct cause for adverse events in the studied cases, respectively. CONCLUSIONS: The proposed human-machine-environment interaction model, when applied to adverse event data, can help to identify the hazard forms and direct causes of adverse events associated with medical device use.
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spelling pubmed-65244502019-06-07 A Hazard Analysis of Class I Recalls of Infusion Pumps Gao, Xuemei Wen, Qiang Duan, Xiaolian Jin, Wei Tang, Xiaohong Zhong, Ling Xia, Shitao Feng, Hailing Zhong, Daidi JMIR Hum Factors Original Paper BACKGROUND: The adverse event report of medical devices is one of the postmarket surveillance tools used by regulators to monitor device performance, detect potential device-related safety issues, and contribute to benefit-risk assessments of these products. However, with the development of the related technologies and market, the number of adverse events has also been on the rise, which in turn results in the need to develop efficient tools that help to analyze adverse events monitoring data and to identify risk signals. OBJECTIVE: This study aimed to establish a hazard classification framework of medical devices and to apply it over practical adverse event data on infusion pumps. Subsequently, it aimed to analyze the risks of infusion pumps and to provide a reference for the risk management of this type of device. METHODS: The authors define a general hierarchical classification of medical device hazards. This classification is combined with the Trace Intersecting Theory to form a human-machine-environment interaction model. Such a model was applied to the dataset of 2001 to 2017 class I infusion pump recalls extracted from the Food and Drug Administration (FDA) website. This dataset does not include cases involving illegal factors. RESULTS: The proposed model was used for conducting hazard analysis on 70 cases of class I infusion pump recalls by the FDA. According to the analytical results, an important source of product technical risk was that the infusion pumps did not infuse accurate dosage (ie, over- or underdelivery of fluid). In addition, energy hazard and product component failure were identified as the major hazard form associated with infusion pump use and as the main direct cause for adverse events in the studied cases, respectively. CONCLUSIONS: The proposed human-machine-environment interaction model, when applied to adverse event data, can help to identify the hazard forms and direct causes of adverse events associated with medical device use. JMIR Publications 2019-05-03 /pmc/articles/PMC6524450/ /pubmed/31066695 http://dx.doi.org/10.2196/10366 Text en ©Xuemei Gao, Qiang Wen, Xiaolian Duan, Wei Jin, Xiaohong Tang, Ling Zhong, Shitao Xia, Hailing Feng, Daidi Zhong. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 03.05.2019. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on http://humanfactors.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Gao, Xuemei
Wen, Qiang
Duan, Xiaolian
Jin, Wei
Tang, Xiaohong
Zhong, Ling
Xia, Shitao
Feng, Hailing
Zhong, Daidi
A Hazard Analysis of Class I Recalls of Infusion Pumps
title A Hazard Analysis of Class I Recalls of Infusion Pumps
title_full A Hazard Analysis of Class I Recalls of Infusion Pumps
title_fullStr A Hazard Analysis of Class I Recalls of Infusion Pumps
title_full_unstemmed A Hazard Analysis of Class I Recalls of Infusion Pumps
title_short A Hazard Analysis of Class I Recalls of Infusion Pumps
title_sort hazard analysis of class i recalls of infusion pumps
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6524450/
https://www.ncbi.nlm.nih.gov/pubmed/31066695
http://dx.doi.org/10.2196/10366
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