Comparative Analysis of Nuclear Event Investigation Methods, Tools and Techniques

Feedback from operating experience is one of the key means of enhancing nuclear safety and operational risk management. The effectiveness of learning from experience at NPPs could be maximised, if the best event investigation practices available from a series of methodologies, methods and tools in the form of a ‘toolbox’ approach were promoted. Based on available sources of technical, scientific, normative and regulatory information, an inventory, review and brief comparative analysis of information concerning event investigation methods, tools and techniques, either indicated or already used in the nuclear industry (with some examples from other high risk industry areas), was performed in this study. Its results, including the advantages and drawbacks identified from the different instruments, preliminary recommendations and conclusions, are covered in this report. The results of comparative analysis of nuclear event investigation methods, tools and techniques, presented in this interim report, are of a preliminary character. It is assumed that, for the generation of more concrete recommendations concerning the selection of the most effective and appropriate methods and tools for event investigation, new data, from experienced practitioners in the nuclear industry and/or regulatory institutions are needed. It is planned to collect such data, using the questionnaire prepared and performing the survey currently underway. This is the second step in carrying out an inventory of, reviewing, comparing and evaluating the most recent data on developments and systematic approaches in event investigation, used by organisations (mainly utilities) in the EU Member States. Once the data from this survey are collected and analysed, the final recommendations and conclusions will be developed and presented in the final report on this topic. This should help current and prospective investigators to choose the most suitable and efficient event investigation methods and tools for their particular needs.JRC.DDG.F.5-Safety of present nuclear reactor

Human reliability analysis: exploring the intellectual structure of a research field

Humans play a crucial role in modern socio-technical systems. Rooted in reliability engineering, the discipline of Human Reliability Analysis (HRA) has been broadly applied in a variety of domains in order to understand, manage and prevent the potential for human errors. This paper investigates the existing literature pertaining to HRA and aims to provide clarity in the research field by synthesizing the literature in a systematic way through systematic bibliometric analyses. The multi-method approach followed in this research combines factor analysis, multi-dimensional scaling, and bibliometric mapping to identify main HRA research areas. This document reviews over 1200 contributions, with the ultimate goal of identifying current research streams and outlining the potential for future research via a large-scale analysis of contributions indexed in Scopus database

A THERP/ATHEANA Analysis of the Latent Operator Error in Leaving EFW Valves Closed in the TMI-2 Accident

This paper aims at performing a human reliability analysis using THERP (Technique for Human Error Prediction) and ATHEANA (Technique for Human Error Analysis) to develop a qualitative and quantitative analysis of the latent operator error in leaving EFW (emergency feed-water) valves closed in the TMI-2 accident. The accident analysis has revealed a series of unsafe actions that resulted in permanent loss of the unit. The integration between THERP and ATHEANA is developed in a way such as to allow a better understanding of the influence of operational context on human errors. This integration provides also, as a result, an intermediate method with the following features: (1) it allows the analysis of the action arising from the plant operational context upon the operator (as in ATHEANA), (2) it determines, as a consequence from the prior analysis, the aspects that most influence the context, and (3) it allows the change of these aspects into factors that adjust human error probabilities (as in THERP). This integration provides a more realistic and comprehensive modeling of accident sequences by considering preaccidental and postaccidental contexts, which, in turn, can contribute to more realistic PSA (Probabilistic Safety Assessment) evaluations and decision making

Use of a big data analysis technique for extracting HRA data from event investigation reports based on the Safety-II concept

The safe operation of complex socio-technical systems including NPPs (Nuclear Power Plants) is a determinant for ensuring their sustainability. From this concern, it should be emphasized that a large portion of safety significant events were directly and/or indirectly caused by human errors. This means that the role of an HRA (Human Reliability Analysis) is critical because one of its applications is to systematically distinguish error-prone tasks triggering safety significant events. To this end, it is very important for HRA practitioners to access diverse HRA data which are helpful for understanding how and why human errors have occurred. In this study, a novel approach is suggested based on the Safety-II concept, which allows us to collect HRA data by considering failure and success cases in parallel. In addition, since huge amount of information can be gathered if the failure and success cases are simultaneously involved, a big data analysis technique called the CART (Classification And Regression Tree) is applied to deal with this problem. As a result, it seems that the novel approach proposed by combining the Safety-II concept with the CART technique is useful because HRA practitioners are able to get HRA data with respect to diverse task contexts

Development and piloting of a software tool to facilitate proactive hazard and risk analysis of Health Information Technology

Health Information Technology is now widely promoted as a means for improving patient safety. The technology could also, under certain conditions, pose hazards to patient safety. However, current definitions of hazards are generic and hard to interpret, particularly for large Health Information Technology in complex socio-technical settings, that is, involving interacting clinical, organisational and technological factors. In this article, we develop a new conceptualisation for the notion of hazards and implement this conceptualisation in a tool-supported methodology called the Safety Modelling, Assurance and Reporting Toolset (SMART). Safety Modelling, Assurance and Reporting Toolset aims to support clinicians and engineers in performing hazard identification and risk analysis and producing a safety case for Health Information Technology. Through a pilot study, we used and examined Safety Modelling, Assurance and Reporting Toolset for developing a safety case for electronic prescribing in three acute hospitals. Our results demonstrate the ability of Safety Modelling, Assurance and Reporting Toolset to ensure that the safety evidence is generated based on explicit traceability between the clinical models and Health Information Technology functionality. They also highlight challenges concerning identifying hazards in a consistent way, with clear impact on patient safety in order to facilitate clinically meaningful risk analysis

An investigation into error detection and recovery in UK National Health Service screening programmes

The purpose of this thesis is to gain an understanding of the problems that may impede detection and recovery of NHS laboratory screening errors. This is done by developing an accident analysis technique that isolates and further analyzes error handling activities, and applying it in four case studies; four recent incidents where laboratory errors in NHS screening programmes resulted in multiple misdiagnoses over months or even years. These errors resulted in false yet plausible test results, thus being masked and almost impossible to detect in isolated cases. This technique is based on a theoretical framework that draws upon cognitive science and systems engineering, in order to explore the impact of plausibility on the entire process of error recovery. The four analyses are then integrated and compared, in order to produce a set of conclusions and recommendations. The main output of this work is the “Screening Error Recovery Model”; a model which captures and illustrates the different kinds of activities that took place during the organizational incident response of these four incidents. The model can be used to analyze and design error recovery procedures in complex, inter-organizational settings, such as the NHS, and its Primary/Secondary care structure

Examining the application of STAMP in the analysis of patient safety incidents

This thesis examines the application of Systems-Theoretic Accident Model and Processes (STAMP) in healthcare and the analysis of patient safety incidents. Healthcare organisations have a responsibility for the safety of the patients they are treating. This includes the avoidance of unintended or unexpected harm to people during the provision of care. Patient safety incidents, that is adverse events where patients are harmed, are investigated and analysed as accidents are in other safety-critical industries, to gain an understanding of failure and to generate recommendations to prevent similar incidents occurring in the future. However, there is some dissatisfaction with the current quality of incident analysis in healthcare. There is dissatisfaction with the recommendations that are generated from healthcare incident analysis which are felt to produce weak and ineffective remedial actions, often including retraining of individuals and small policy change. Issues with current practice have been linked to the use of Root Cause Analysis (RCA), an analysis method that often results in the understanding of an accident as being the result of a linear chain of events. This type of simple linear approach has been the target of criticism in safety science research and is not felt to be effective in the analysis of incidents in complex systems, such as healthcare. Research in accident analysis methods has developed from a focus on technical failure and individual human actions to consideration of the interactions between people, technology and the organisation. Accident analysis methods have been developed that guide investigations to consideration of the whole system and interactions between system components. These system approaches are judged to be superior to simple linear approaches by the research community, however, they are not currently used in healthcare incident investigation practice. The systems approach of STAMP is felt to be a promising method for the improvement of healthcare incident analysis. STAMP strongly embodies the concepts of systems theory and analyses human decision-making. The application of STAMP in healthcare was investigated through three case studies, which applied STAMP in: 1. The analysis of the large-scale organisational failure at Mid-Staffordshire NHS Trust between 2005-2009. 2. The analysis of a common small-scale hospital-based medication prescription error. 3. The analysis of patient suicide in the community-based services of a Mental Health Trust. The effectiveness of the STAMP applications was evaluated with feedback from healthcare stakeholders on the usability and utility of STAMP and discussion of the STAMP applications against criteria for accident analysis models and methods. Healthcare stakeholders were generally positive about the utility of STAMP, finding it to provide a system view and guide consideration of interactions between system components. They also felt it would help them generate recommendations and were positive about the future application of STAMP in healthcare. However, many felt it to be a complicated method that would need specialist expertise to apply. The STAMP applications demonstrated the ability of STAMP to consider the whole system and guide an analysis to the generation of recommendations for system measures to prevent future incidents. From the findings of the research, recommendations are made to improve STAMP and to assist future applications of STAMP in healthcare. The research also discusses the other factors that influence incident analysis beyond that of the analytical approach used and how these need to be considered to maximise the effectiveness of STAMP