Error reduction, systems approach

As must now be clear, error has many different facets and the subject of error, and how to reduce error, can be approached in different ways. While there are a multitude of different taxonomies and error reduction systems, we can discern some broad general perspectives or error paradigms as they are sometimes called. Following Deborah Lucas (1997) and James Reason (1997)... 

Chapter 2, Understanding Human Performance and Error, provides a comprehensive overview of the main approaches that have been applied to analyze, predict, and reduce human error. This chapter provides the reader with the vmderlying theories of human error that are needed to xmderstand and apply a systems approach to its reduction. 

FROM THEORY TO PRACTICE TURNING THE SYSTEMS APPROACH TO A PRACTICAL ERROR REDUCTION METHODOLOGY... 

In subsequent chapters, the various theories, tools, and techniques required to turn the systems approach from a concept to a practical error reduction methodology will be described. The components of this methodology are described in Figure 1.7. Each of these components will now be described in turn, together with references to the appropriate sections of the book. 

The first component of the systems approach to error reduction is the optimization of human performance by designing the system to support human strengths and minimize the effects of human limitations. The hiunan factors engineering and ergonomics (HFE/E) approach described in Section 2.7 of Chapter 2 indicates some of the techniques available. Design data from the human factors literature for areas such as equipment, procedures, and the human-machine interface are available to support the designer in the optimization process. In addition the analytical techniques described in Chapter 4 (e.g., task analysis) can be used in the development of the design. 

The last area addressed by the systems approach is concerned with global issues involving the influence of organizational factors on human error. The major issues in this area are discussed in Chapter 2, Section 7. The two major perspectives that need to be considered as part of an error reduction program are the creation of an appropriate safety culture and the inclusion of human error reduction within safety management policies. 

The first perspective is the traditional safety engineering approach (Section 2.4). This stresses the individual factors that give rise to accidents and hence emphasizes selection, together with motivational and disciplinary approaches to accident and error reduction. The main emphasis here is on behavior modification, through persuasion (motivational campaigns) or pimishment. The main area of application of this approach has been to occupational safety, which focuses on hazards that affect the individual worker, rather than process safety, which emphasizes major systems failures that could cause major plant losses and impact to the environment as well as individual injury. 

Emphasis on the Modification of System Factors as a Major Error Reduction Strategy This emphasis replaces the reliance on rewards and pLmishment as a means of error control which characterizes the TSE approach. 

Policy makers, practitioners, and scholars from a variety of disciplines have recently embraced a new approach to risk reduction in health care—a "systems approach"—without proposing any specific reforms of medical liability law. The Institute of Medicine (IOM) placed its imprimatur on this approach in its recent reports (Kohn et al., 2000 IOM, 2001). In its simplest form, a systems approach to risk reduction in health care posits that an injury to a patient is often the manifestation of a latent error in the system of providing care. In other words, a medical mishap is the proverbial "accident waiting to happen" because the injury-preventing tools currently deployed, including medical liability law, are aimed at finding the individuals at fault rather than the systemic causes of error. Coexistence of a systems approach to error reduction and medical liability law as a conceptual framework for policy makers implies that the latter is likely to evolve in an incremental fashion as the former makes more visible different aspects of the medical error problem. 

To identify opportunities for reducing medication errorS/ it is important that each error be carefully reviewed by a limited number of individuals to gain intimate knowledge of each reported incident. Collection and classification of error data must be followed by use of a careful epidemiological approach to problem solving at the system level. Narrative data which may not be seen by looking at the categorical data alone/ can be used to provide important details about proximal causes and latent error that may have contributed to the event. Success in this type of error reduction requires the reviewers to read between the lineS/ look for common threads between reports/ and link multiple errors that are the result of system weaknesses. 

Error Reduction in Health Care A Systems Approach to Improving Patient Safety Spath, P.L., Ed. Jossey-Bass Publishers San Francisco, 2000. 

Error Reduction in Healthcare A Systems Approach to Improving Patient Safety. Chicago, IL Health Forum Inc., 2000, pp. 199-234. 

There is no doubt that this approach to error management resulted in significant enhancements to safety. However, this approach failed to emphasize the inevitability of error and its spontaneous occurrence even within the best-designed systems. The next step was developing an approach that accepted both the ubiquity and inevitability of human error and therefore focnssed not only on error reduction, but also on the subsequent management of error to either mitigate or ameliorate any effects of error on system performance. 

Embrey, D.E. (1986), SHERPA A Systematic Human Error Reduction and Prediction Approach, Paper Presented at the International Meeting on Advances in Nuclear Power Systems, Tennessee Knoxville. 

Taxonomy-based HEI techniques use external error mode (EEM) taxonomies to identify potential errors within complex sociotechnical systems. Typically, EEMs are considered for each component step in a particular task or scenario to determine credible errors that may arise during human-machine interaction. Techniques such as the Systematic Human Error Reduction and Prediction Approach (SHERPA) (Embrey, 1986), the Human Error Template (HET) (Stanton et al., 2006), the Technique for the Retrospective and Predictive Analysis of Cognitive Errors (TRACEr) (Shorrock and Kirwan, 2002), and the Cognitive Reliability and Error Analysis Method (CREAM) (Hollnagel, 1998) all use domain-specific EEM taxonomies. Taxonomic approaches to HEI are typically the most successful in terms of sensitivity and are also the least expensive, quickest, and easiest to use however,... 

Embrey, D.E. 1986. SHERPA a systematic human error reduction and prediction approach. Paper presented at the International Topical Meeting on Advances in Human Factors in Nuclear Power Systems. Knoxville Tennessee. 

Both for the gravimetric method and electrogalvanic method, each of the reactions was approached from both sides, oxidation and reduction, and when the sample weights or e.m.f. were identical within experimental error, the systems were considered to have been in equilibrium states. 

The approach with the partitioning of the system into a QM and a classical molecular mechanical (MM) part, thus usually termed hybrid QM/MM procedure, provides a reasonable reduction of the computational effort by restricting the time-consuming QM calculation of forces to the most relevant part of the liquid system. The main error sources in this approach are a too small choice of the QM region, an inadequate level of theory for the QM calculation, the choice of suitable potentials for the MM part of the system, and smooth transitions of particles between QM and MM region. In conventional QM/MM procedures, the whole system is first evaluated at MM level and then corrected by the QM data. This means that classical potential functions (with all their problems and difficulty of construction) are needed for all components of the system. A recently developed methodology can reduce the need for such potentials to the solvent only, as will be outlined below. 

From the set E of equations the construction of the system matrices follow directly. The approach outlined before, making use of the classification strategy allows the general reduction of the initial balances into a set of equations smaller in size than that suggested by Vaclavek. The reduced set of balance equations given by eq. (15), or (18) define now the following weighted least squares problem for the reconciliation of the measurement errors. In the linear case... 

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