Failure Mode And Effects Analysis Model Research Articles

Failure mode and effect analysis in anesthesia medication errors

Background Failure mode and effect analysis (FMEA) is a process in operation management for analysis of the potential failures within a system, and it can be used in healthcare to detect any errors and can find the action plans to prevent errors or risks. The aim of this study was to evaluate whether the FMEA is a useful method to predict anesthesia medication errors, identify those errors and analyze the root causes of failures, and how it can eliminate the risk. Methods A prospective study was carried out by a multidisciplinary team under the supervision of an anesthesiologist as the team leader and included an anesthesia nurse, pharmacist, and performance improvement coordinator. The FMEA model was implemented in the process of general anesthesia medications. First, the process was divided into three steps of ordering, preparation, and administration of the anesthetics. Second, identification of the failure was made (failure mode). Third, the potential effect of the failure was assessed. Fourth, criticality score was determined to detect the critical failure that was evaluated by root causes analysis, and then final recommendations or action plan were made to eliminate the risk or reduce the failure. Results There were three failures in the process of ordering, eight failures in the process of preparation, and four failures in the process of administration, a total of 15 failures; there were eight critical failures that required urgent recommendations to reduce the risk, and the remaining failures were nonhigh risk that required further recommendations. All of them were reviewed and approved by the pharmacy and therapeutic committee and hospital management. Conclusion The FMEA model by a multidisciplinary team is a useful method for detecting failures for anesthesia medication errors, and a simple way to analyze the root causes of the errors; it can also find the optimal method to eliminate the risk of failure.

Failure Mode and Effect Analysis (FMEA) for confectionery manufacturing in developing countries: Turkish delight production as a case study

The Failure Mode and Effect Analysis (FMEA) was applied for risk assessment of confectionary manufacturing, in whichthe traditional methods and equipment were intensively used in the production. Potential failure modes and effects as well as their possible causes were identified in the process flow. Processing stages that involve intensive handling of food by workers had the highest risk priority numbers (RPN = 216 and 189), followed by chemical contamination risks in different stages of the process. The application of corrective actions substantially reduced the RPN (risk priority number) values. Therefore, the implementation of FMEA (The Failure Mode and Effect Analysis) model in confectionary manufacturing improved the safety and quality of the final products.

Failure Mode and Effects Analysis: A Tool for Identifying Risk in Community Pharmacies

CANADIAN HEALTH CARE LEADERS HAVE BEGUN TO LOOK AT SAFE practices in other industries to identify those with applicability to health care. A key characteristic of high-reliability industries, such as nuclear power, aviation, automobile manufacturing, and chemical processing, is acceptance of the fact that errors will occur, that the impact of errors can be devastating, and that efforts should be made to discover system weaknesses before harm occurs. A tool that has been a cornerstone of safety efforts in these organizations is a proactive risk assessment process called failure mode and effects analysis (FMEA). Using FMEA, multidisciplinary teams first identify potential failures and their effects, and then develop strategies for improvement. FMEA focuses on how and when a system will fail, not if it will fail. The US Veterans Affairs (VA) National Center for Patient Safety has developed an FMEA model for health care environments called Healthcare Failure Mode and Effect Analysis (HFMEA). 1 As part of its role in the Canadian Medication Incident Reporting and Prevention System, the Institute for Safe Medication Practices Canada (ISMP Canada) has adapted the VA model to develop a similar FMEA framework for use in Canada.

Failure modes and effects analysis through knowledge modelling

Failure mode and effect analysis (FMEA) is a widely used quality improvement and risk assessment tool in manufacturing. Accumulated information about design and process failures recorded through FMEA provides very valuable knowledge for future product and process design. However, the way the knowledge is captured poses considerable difficulties for reuse. This research aims to contribute to the reuse of FMEA knowledge through a knowledge modelling approach. An attempt is made to shift FMEA activities to the conceptual design stage. The early warning about possible failures will enable designers to avoid costly and difficult design changes at later stages of the design process. An object-oriented approach has been used to create an FMEA model. Functional diagrams have been used for the conceptual model. The FMEA model is assisted by functional reasoning techniques to enable automatic FMEA generation from historical data. The reasoning technique also provides a means for the creation of new knowledge. The FMEA generation process has been discussed. The automatic generation replaces the traditional brainstorming process for FMEA report creation. Failure report is used as the data source for the FMEA generation. The proposed method has been evaluated with a prototype software and case studies.

A decision support system for applying failure mode and effects analysis

This study describes an alternative way of applying failure mode and effects analysis (FMEA) to a wide variety of problems. It presents a methodology based on a decision system supported by qualitative rules which provides a ranking of the risks of potential causes of production system failures. By providing an illustrative example, it highlights the advantages of this flexible system over the traditional FMEA model. Finally, a fuzzy decision model is proposed, which improves the initial decision system by introducing the element of uncertainty.