Error management

In a sense, all the incidents described so far have been management errors but this section describes two incidents which would not have occurred if the senior managers of the companies concerned had realized that they had a part to play in the prevention of accidents over and above exhortations to their employees to do better. 

These various aspects of evaluating, predicting, and reducing human error form part of a general strategy for managing error which will be described in Chapter 5. 

Non-sampling errors can be categorized into laboratory error and data management error, with laboratory error further subdivided into measurement, data interpretation, sample management, laboratory procedure and methodology errors. 

Sample management error improper sample storage analysis of samples that have reached the end of their holding time misplaced or mislabeled samples sample cross-contamination... 

Representativeness Sampling design error Field procedure error Data interpretation error Sample management error Data management error... 

Completeness Data management error Field and laboratory procedure error... 

In the course of sample tracking, data evaluation, and interpretation, field sample IDs may be entered into several different field forms, spreadsheets, and data bases, and appear on maps and figures as identifiers for the sampling points. Because the field records and computer data entry during sample receiving at the laboratory are done for the most part manually, errors in sample ID recording are common. To reduce data management errors, sample numbers must be simple, short, and consecutive. 

Example 4.1 Sample management errors during sample receiving... 

Consistent QA measures implemented at the laboratory prevent most of sample management errors during storage ... 

Data management errors that may take place during data reduction and reporting have a potential to ruin an otherwise perfect analysis. These errors may have significant effects on the accuracy, precision, and completeness of a data set as shown in Example 4.6 on page 200. 

Laboratories prevent data management errors by implementing QA policies and procedures for data reduction, verification, and software management and by establishing a high standard of professional ethics. 

The following data management errors are known to occur at the laboratories ... 

The assessment phase itself, however, is not invincible from error either. Data management errors may hinder the success of DQA, particularly for projects with insufficient planning, followed by disorderly implementation. Effective assessment is possible only when built on a foundation of solid project planning and supported by well-organized implementation of the planned data collection. 

For sample results with complete and thoughtfully compiled data packages, these questions may be answered immediately upon evaluation. However, if QC check data and support documentation are missing or are inaccurate due to data management errors at the laboratory, the chemist s decision on data quality may be delayed. The chemist will request that the laboratory provide additional data in order to evaluate them at a later date. The loss of continuity in the data evaluation process due to poor quality of data packages is counterproductive and may cause delays in the scheduled project report delivery to the client. 

A complete knowledge of the data quality that arises only from Level 4 validation enables the data user to make project decisions with the highest level of confidence in the data quality. That is why Level 4 validation is usually conducted for the data collected to support decisions related to human health. Level 4 validation allows the reconstruction of the entire laboratory data acquisition process. It exposes errors that cannot be detected during Level 3 validation, the most critical of which are data interpretation errors and data management errors, such as incorrect computer algorithms. 

The chemist interprets the results of trip and equipment blank analyses to identify sample management errors during sampling, sample handling, and decontamination procedures and to determine whether these errors may have affected the collected sample representativeness. The chemist qualifies the data according to the severity of the identified variances from the SAP specifications and may even reject some data points as unusable. Example 5.8 shows a logical approach to the interpretation of the trip and equipment blank data. 

Management error Not paying attention to worker progress... 

To communicate broadly and to educate healthcare professionals and the public about the nature of medication errors, how to prevent them, and how to manage errors that do occur. 

Serious management errors are common in patients admitted to a hospital with acute severe asthma, and most of these errors are related to patient selfmanagement behaviour. Most acute severe attacks would be preventable if physicians could induce a change in their patients behaviour [118], The better the patients and their families are informed and actively involved, the more successful is their collaboration with the physician. Self-management programmes, when coupled with regular health practitioner reviews, have improved health outcomes [119],... 

Ten Thoren C, Petennann F Reviewing asthma and anxiety. Respir Med 2000 94 409 415. Kolbe J, Vamos M, Fergusson W, Elkind GD Determinants of management errors in acute severe asthma. Thorax 1998 53 14—20. 

Of course not all users prioritise these characteristics equally. An expert user is more likely to focus on efficiency whilst a beginner will require leamability and memorability. Errors in safety-related HIT systems frequently translate into the propensity to trigger hazards. On this basis, all HIT system designers need to prioritise managing error occurrence as a design objective. 

Manager error it means manager and engineering technical personnel s mistake. It includes 4 kinds of types. That is. Training is not in place Manager s quality is low the attitude is not correct Management method is not proper. 

Pate-Comell, M.E. and Bea, R.G. (1992) Management errors and system reliability a probabilistic approach and application to offshore platforms. Risk Analysis, 12(1), 1-18. 

Our ability to prevent accidents relies on our capacity to eflfectivefy manage error. The time has arrived for a return to basics. Some form of standardization is vital in the common terminologies, methods and structure used to record and analyse those events which cause accidents and injury to people. 

We noted earlier that an accident is caused by the demands of the work system exceeding the capacity of the system to manage error. The elements that make up the work system mentioned earlier become unable to cope with the level of error in the system they create. There is a requirement on employers to provide a safe system of work. In determining if the system is safe, all five elements must be considered, not just individually, but in combination. The error occurs in the synergy, not in the individual elements. 

In some industries, conditions exist where one accident is too maty and there is a need to focus totally on error management. In a perfect world, perhaps all workplaces could enjoy the capacity to allocate the resources needed to effectively manage error. 

Safety net Redundancy Risk management Error traps Error mitigation... 

Phillips, E.H. (2000), Managing Error at Centre of Pilot Training Program, Aviation Week and Space Technology, 153, 61-62. 

Reason, J. (2005). Managing Error Management Workshop, Brisbane, Australia, May 26, 2005. 

Accident investigation is the determination by qualified personnel as to the specific causing for a particular accident or mishap. Causal factor considerations include management errors, technical design, hardware failures, procedural errors, and so on. An accident investigation can be conducted by a formal board or by an informal analysis performed by one or more individuals. 

This model, based on three tenses, is simple and tells us (1) that one cannot completely eliminate (patent) errors by people who are directly engaged in work, (2) that deep defences are needed to avoid the propagation of these errors as far as an accident, and (3) that it is necessary to be aware of organisational and management errors (latent errors) which, without being the immediate cause of accidents, increase the vulnerability of the individuals and defences directly engaged in the work by not giving them aU the resources they need to be effective. 

The creation of density stratification, with small but significant density discontinuities (of the order of 0.5-2.0 %) between layers, by custody management errors, or by unexpected auto-stratification. 

---