A novel approach to Data Driven Preventive Maintenance Scheduling of medical instruments

Justin Joseph, S. Madhukumar
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引用次数: 6

Abstract

The objective of this endeavor has been to develop a Preventive Maintenance Index (PMI) for each instrument in the clinical engineering inventory to assign a preventive maintenance interval (PMInterval), in what the safety tests most be applied as well as to prioritize the PM procedure. This numerical index has been synthesized based on Risk Level Coefficient (RLC) of the instrument. The equipment inventory has been categorized as per the recommendations of International Electro safety Commission (IEC), Federal Drug Agency (FDA) and Hill into various risk groups as Type C, B, H, Class I, II, III, General, Susceptible, Critical and so on. Relevance factor has been imposed to each aspect analyzed. Static Risk of specific medical equipment is assessed through the factors Physical Risk (PR), Equipment Function (EF), and Hazard Potential (HP).The Hazard Potential of each equipment is extracted from the outcome of a pilot survey conducted at national level, so as the system to be evidence based. The Risk Level Coefficient of equipments are derived by statistically integrating individual relevance coefficients and static risk (SR). A standard audit interval is inadequate; hence PMInterval is designed to be adaptive based on the Interval Adaptation Coefficient (IAC) which in turn points Failure / accident history of the equipment. An attempt to incooperate the PM Due Factor (DF), Age Ratio (AR) and Usability Ratting (UR) also has been made. The proposed ‘Data Driven Preventive Maintenance Scheduling’, is in par and comply with, ISO 14971, IEC 60601 Series and JCAHO regulations.
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一种数据驱动的医疗器械预防性维护调度新方法
这项工作的目标是为临床工程清单中的每个仪器制定预防性维护指数(PMI),以分配预防性维护间隔(pmininterval),在哪些安全测试最适用,以及优先考虑预防性维护程序。该数值指标是在仪器风险水平系数(RLC)的基础上合成的。根据国际电工安全委员会(IEC)、美国联邦药品管理局(FDA)和Hill的建议,将设备库存分为C类、B类、H类、I类、II类、III类、一般类、易感类、关键类等各种风险组。对所分析的各个方面都施加了相关因素。特定医疗设备的静态风险通过物理风险(PR)、设备功能(EF)和潜在危害(HP)等因素进行评估。每种设备的潜在危险是从国家一级进行的试点调查的结果中提取的,因此该系统是基于证据的。通过对个体相关系数和静态风险进行统计积分,得到设备的风险等级系数。标准的审计间隔是不够的;因此,PMInterval被设计为基于区间适应系数(IAC)的自适应,该系数轮流指向设备的故障/事故历史。我们还尝试将PM Due Factor (DF)、Age Ratio (AR)和Usability Ratting (UR)结合起来。拟议的“数据驱动预防性维护计划”符合ISO 14971, IEC 60601系列和JCAHO法规。
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