Root cause analysis model

The US Department of Veterans Affairs National Center for Patient Safety (NCPS) of the US Department of Veterans Affairs, which developed a new root cause analysis model to be used in the healthcare system consisting of assigning a safety assessment code to prioritise... 

A corrective action is initiated to correct the cause of an identified nonconformity and to prevent it or similar problems from reoccurring. It may include initial and follow-up actions (e.g., conducted after root cause analysis). Current quality system models and the cGMP regulations emphasize corrective actions and require that actions be documented. Under current quality system models, preventive actions include actions taken in response to quality data to address the cause of potential nonconformities to prevent their occurrence. An effective CAPA system therefore includes both reactive and proactive components. The effectiveness of corrective and preventive actions should be evaluated using objective criteria when possible and the evaluation documented. 

The location-specific model assumes that different types of shocks occur at particular rates /Xj, for j = 1,..., i. To quantify the parameters of the location-specific model, the analyst needs to classify the failure events according to the type of failure mechanism underlying the event. This may be accomplished by performing root cause analysis. The data available and relevant to the specific k components can be written in the form... 

Frank Bird introduced his model of root cause analysis in his book, Practical Loss Control Leadership (Bird et al., 2003). The model identifies three levels of causation that must be addressed for proper countermeasure formation. Understanding and identifying factors of the incident nnder all three levels is necessary to address the incident at a root level and prevent fntnre occnrrence. 

The prototype for the sequential accident model is the Domino model. The Domino model represents simple, linear causahty, as in the case of a set of domino pieces that fall one after the other. According to the logic of this model, the purpose of event analysis is to find the component that failed, by reasoning backwards from the final consequence. This corresponds in all essentials to the principle of the Root Cause Analysis (RCA), which will be described in more detail in the following. Similarly, risk analysis looks for whether something may break, meaning... 

The natural consequence of the causality credo, combined with the Domino model, is the assumption that there is a basic or first cause, which can be found if the systematic search is continued until it can go no further. This is often called the root cause, although definitions differ. In the Domino model, the root cause was the ancestry and social environment, which led to undesirable traits of character. Since this was the fifth domino, it was not possible to continue the analysis any further. Other approaches, particular if they subscribe to some form of abstraction hierarchy, suffer from the same limitation. The type of analysis (which actually is a family of methods) that tries to find the root cause is unsurprisingly called Root Cause Analysis (RCS). 

Breakthrough Thinking— This change model utilizes purpose expansions rather than root cause analysis and has become quite popular in Japan, especially among the users of the Toyota production system. The following discusses the concept briefly. 

Engineering experience, root cause analysis skills Mathematical models ... 

For this simple example, a similar analysis could be based on a quantitative approach, namely, a dynamic model based on an unsteady-state mass balance. The level could be changing as a result of process changes or a sensor failure. However, for more complicated processes, a reasonably accurate dynamic model may not be available, and thus a qualitative approach can be used to good advantage. The diagnosis of the abnormal event could lead to a subsequent root cause analysis, where the source of the abnormality is identified and appropriate corrective actions are taken. 

The theoretical basis of the different causal models becomes more obvious at the upper management level. MORT was the first comprehensive model to include organisational and individual factors at the top management level. At this level, it draws from quality assurance management principles. The SMORT and ILCI models have been influenced by this pioneering work and represent variations on the same theme. The concept of root causes originates from the MORT model. The checklist above shows the different items of a root-cause analysis. 

Analysis of Incident Root Causes Using the Sequential Error Model... 

Traditional accident models were devised to explain losses caused by failures of physical devices (chain or tree of failure events) in relatively simple systems. They are less useful for explaining accidents in software-intensive systems and for non-technical aspects of safety such as organizational culture and human decision-making. Creation of an infrastructure based on which safety analysis can function efficiently and effectively is needed. A so called safety culture for a development company and processes associated with routine tasks there, in general, is now identified as an area of root cause of accidents and that there is the greatest... 

Fluoropol Tners are used in critical applications where failure may have serious safety, environmental, and/or financial consequences. Modeling is an important tool in determining the root cause of the failure and its correction. The modeling of fluoropolymer components, like other polymer materials, continues to evolve in sophistication. This chapter introduces current and developing methodologies for mechanical analysis. These methodologies promise increasingly accurate predictions and analysis of fluoropolymer materials. 

Most accident reports are written from the perspective of an event-based model. They almost always clearly describe the events and usually one or several of these events is chosen as the root cause(s). Sometimes contributory causes are identified. But the analysis of why those events occurred is usually incomplete The analysis frequently stops after finding someone to blame—usually a human operator—and the opportunity to learn important lessons is lost. 

Common cause failures (CCFs) are an important part of reliability analysis and engineers have been aware of these types of failures since the mid-seventies by Fleming (1974). Today there exist numerous models which explain this concept and attempt to model the impact such CCFs have on different systems. Even though this topic has been given much attention, it is still considered to be difficult and of a complex nature. CCFs are difficult to quantify correctly, i.e. it is difficult to know if a component fails due to a common root cause that affects several components, or if it fails because it is old and worn out. Usually, not much feedback data exist, so modelling this properly has proven difficult. In addition, different systems have different properties meaning that a model that may work for one system does not necessarily work for another. 

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