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The collection and analysis research of quality control data for using ventilator in hospital / 中国医学装备
China Medical Equipment ; (12): 18-21, 2017.
Article in Zh | WPRIM | ID: wpr-612788
Responsible library: WPRO
ABSTRACT
Objective:To collect and analyze the quality control data of ventilator, so as to apply these statistical data to guide the maintenance and management of ventilator.Methods: The displayed value and monitoring value of the tidal volume, respiratory frequency, inspiratory oxygen concentration, inspiratory pressure level and positive end expira tory pressure (PEEP) under different setting of 50 using ventilators in hospital were collected by using PF-300 gas analyzer, and then each parameter was analyzed as classification.Results: The total quality rate of ventilators was 80%, the ranking of quality rate as different brand was: brand B>brand A>brand C, and it was as different department: department 5>department 4=department 3>department1>department2, and the quality rates of less than 3 years and more than 3 years were 87% and 77%, respectively, as service life of ventilator. And the ranking of quality rates as parameters of ventilator was: PEEP=respiratory frequency >peak pressure>tidal volume >oxygen concentration. It was as accuracy of monitoring: brand A>brand C>brand B. It was as stability of monitoring: brand A>brand B=brand C. On the other hand, it was as the accuracy of displayed value: brand A>brand B>brand C, while it was as the stability of displayed value: brand A>brand C>brand B.Conclusion: The analysis of quality control data only suits to the ventilator which is used in our hospital. The engineer can targeted to strengthen the ventilator maintenance work and improve the quality and safety of equipment, so as to give the better service for patients according to quality control data of using ventilators in hospital.
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Full text: 1 Index: WPRIM Language: Zh Journal: China Medical Equipment Year: 2017 Type: Article
Full text: 1 Index: WPRIM Language: Zh Journal: China Medical Equipment Year: 2017 Type: Article