A Data Analysis Method Of The Medical Devices Adverse Events Based On Human-Machine-Environment Interaction Model

The medical devices,due to their natural characteristics,should bring safety risks,together with health benefits,to the users.In order to reduce the application risk of medical devices and ensure the safety and effectiveness of medical devices,it is necessary to carry out risk assessment and analysis work for the post-market medical devices.The medical device adverse events refer to the qualified post-market medical devices cause a variety of harms(or potential harms)to the human body under normal operation.Medical device adverse event monitoring is the process of discovery,reporting,evaluation and control of suspicious medical device adverse events.Its purpose is to reduce or avoid the occurrence of harmful events or to reduce the risk and harm caused to human body health.Medical device adverse event monitoring can provide technical support for the re-evaluation and recall mechanism of post-market medical devices.It is an integral part of the medical device safety supervision work.The regulatory agencies in the most countries have established corresponding reporting system of the medical device adverse events to actively collect medical devices adverse events,so that monitoring can proceed smoothly.Medical device adverse event monitoring is an important means for risk management of medical devices.Carrying out the sustainable work of the post-market medical devices' quality safety and risk management scientifically and reasonably is an important means to ensure safe use of medicine in public and promote the promotion of the product quality,Which have great significance to alert the public on how to use it safely and effectively.The medical device adverse event reports provides the basis for the supervision of post-market medical devices(risk analysis,re-evaluation,recall,etc.).By analyzing the hazards of the adverse event reports and extracting the risk factors,the hidden safety risks of medical devices can be detected early,and then take appropriate control measures to reduce the use risks of medical devices.The authors defines a general hazard classification framework and a direct cause hierarchical classification of medical device hazards,and initially established a technical and methodological framework for the benefit and risk assessment of post-market medical device products.These classification are combined with the Trace Intersecting Theory to form a human-machine-environment interaction model.This paper is applied such model to empirical research the dataset of 2001~2018 class I recalls extracted from FDA website and partial medical device adverse event reports from the “national information system for monitoring adverse drug reaction”,which were collected throughout the country.Firstly,using the classification standard of "harm" and “direct cause” to find out key hazard risk factors and root causes through the analysis of adverse events reports.Then input the structured data to the risk management process.Finally,using the "three principles of benefit and risk trade-offs" and Risk-informed decision-making(RIDM)for risk assessment to achieve the ultimate goal of optimal system safety.Through empirical research,it is concluded that the proposed data analysis method,when applied to adverse event data,can help to identify the hazard forms,risk characteristics and direct causes of medical device adverse events,and also can optimize the product risk control solutions and have a positive effect on the development of public health.Moreover,the method can be used to guide the specific quality monitoring work to promote the development of national adverse drug reactions monitoring system and help to the supervision department to form a complete regulatory system of post-market medical devices.