Failures organisational

Tucker, A.L. and Edmondson, A. (2003) Why hospitals don t learn from failures. Organisational and psychological dynamics that inhibit change. California Management Review, 45(2), 55-72. 

Usually, the odds relating to the test treatment group go on the top when calculating the ratio (the numerator), while the odds for the control group go on the bottom (the denominator). However there is no real convention regarding whether it is the odds in favour of success or the odds in favour of failure that we calculate. Had we chosen to calculate the odds in favour of no SAE, the odds ratio would have been which has the value 0.66(= 1/1.51) so take care that when you see an odds ratio presented you are clear how the calculation has been organised. 

II, Chapters 4, 5, and 6 give all the information regarding the theoretical aspects involved in designing a complete NMMS and ensuring its successful implementation and maintenance. A complete system to detect, describe, analyse and follow-up near misses is outlined (Chapter 4), with special emphasis on a model-based classification of system failure (Chapter 5) a number of key issues relating to organisational aspects like acceptance by employees, and safety cultures are discussed in Chapter 6,... 

In the previous chapters the purposes of near miss reporting have been outlined and a framework of designing such a safety management tool has been presented. The importance of human behaviour as a dominant factor in incident sequences was stressed by developing a system failure classification scheme largely based on a theoretical model of operator behaviour. Also an overview was given of the organisational factors necessary for a successful implementation of a NMMS. 

Organisational failure only one category used here OP, referring to the quality of not only formal and well-established, but also unofficial Operating Procedures, Work Practices, Guidelines, etc. 

In the rest of this chapter, we will discuss briefly the theoretical ideas and the models employed for the study of failure of disordered solids, and other dynamical systems. In particular, we give a very brief summary of the percolation theory and the models (both lattice and continuum). The various lattice statistical exponents and the (fractal) dimensions are introduced here. We then give brief introduction to the concept of stress concentration around a sharp edge of a void or impurity cluster in a stressed solid. The concept is then extended to derive the extreme statistics of failure of randomly disordered solids. Here, we also discuss the competition between the percolation and the extreme statistics in determining the breakdown statistics of disordered solids. Finally, we discuss the self-organised criticality and some models showing such critical behaviour. 

We discuss the various dynamical models of earthquake-like failures in Chapter 4. Specifically, the properties of the Burridge-Knopoff stick-slip model (Burridge and Knopoff 1967) and of the self-organised criticality models, the Guttenberg-Richter type power laws, for the frequency distribution of earthquakes in these models are discussed here. 

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