Human reliability assessment for medical devices based on failure mode and effects analysis and fuzzy linguistic theory

Abstract

Medical device systems have become increasingly complex, interconnected, and interoperating. A major challenge is how to ensure and improve the safety, security, and reliability of medical devices. An efficient human reliability analysis and assessment for medical devices is essential for improving the quality of medical treatment and preventing an iatric accident. This paper explores qualitative and quantitative methods to analyze human reliability for medical devices. First, the SHELL (named after the initial letters of its components’ names, Software, Hardware, Environment, Live-ware and Central Live-ware) model is developed to make a qualitative analysis for human reliability of medical devices. The SHELL model is to consider human as an integrated and inseparable component of the productive system. After that, failure modes and effects analysis (FMEA) is proposed to evaluate the potential failures in human reliability of medical devices. Failure mode and effects analysis (FMEA) is a method to assess a system, design, process or service for possible ways, in which failures (problems, errors, risks and concerns) can occur. The most important issue of FMEA is the determination of risk factors like the occurrence, severity, and detection using the opinions of different experts. This paper applies fuzzy linguistic theory to convert the subjective cognition of experts into an information entity to obtain the numerical values of risk factors. The aim of this study is to analyze and build an assessment model for human reliability of medical devices to improve the safety of medical devices.