Challenges of defining and classifying errors

The discourse of definitions of errors is an important background for any medication error study as presented in this section. For example, defining the term ‘prescribing error’ may appear relatively simple. However, practitioners and researchers may disagree about what constitutes an error. As Charles Vincent noted, achieving agreement on a working definition of a prescribing error once required a full primary study and an outline of scenarios that should be included or excluded as prescribing errors, even with room for disagreement (Dean

errors in general practice (PRACtISE) study, Avery and colleagues provided a detailed analysis of the issues around defining an error as examined below (Avery, Barber, et al., 2012).

Classifying an act as an error is a value judgement; it is subjective in that the training and experience of the person(s) making such judgement cannot be ignored and will always influence their decision. If an error judgement is based solely on scientific facts, such as drug-receptor interactions, it is expected to fail because, “as Aristotle pointed out, the worlds of facts and values are different” (Avery, Barber, et al., 2012). The researchers noted that the use of expressions, which suggest value judgments such as “’failure’, ‘inappropriate’,

‘should’, etc.” should therefore be explained to reduce inconsistencies in their interpretation i.e. an error definition should not be so broad to give rise to different interpretations,

nevertheless not so specific that it becomes useless or impractical. An error definition should be fairly widely applicable within and across healthcare systems if sufficient information is provided to extrapolate its rules to different situations.

The researchers highlighted three important points in relation to error definitions:

 The suitability of a definition for the purpose for which it is intended (differences between an error definition in practice for incident reporting versus the extent and detail of a definition used in quantitative research);

 The need to separate definition, which comes first, from classification (which may include types of errors or potential outcome for example); and

 The confusion generated by researchers when they use different words for similar purposes and/or similar words for different purposes in their publication.

Senders and Moray suggested that an error should be interpreted as something done, which

 A set of rules or external observer did not desire

 Moved an outcome beyond acceptable limits; and

 Was not intended by the actor (Senders et al., 1991) as cited in Vincent, 2010).

These two schools of thought, and probably others, suggest that a set of criteria is required for defining an error. The requirements for an error to be workable therefore are the need for a

set of standards against which there must be some sort of failure, albeit without the intention of the actor to do so. What these criteria do not point out readily is that the divide between these principles in practice is very blurred as exemplified in the succeeding paragraphs (Vincent, 2010).

Dean and colleagues used the Delphi technique to develop and validate an operational

definition of a prescribing error for research use when they studied prescribing errors in a UK hospital:

“A clinically meaningful prescribing error occurs when, as a result of a prescribing decision or prescription-writing process, there is an unintentional significant

 Reduction in the probability of treatment being timely and effective, or

 Increase in the risk of harm when compared with generally accepted practice.”

This definition was developed following a Delphi process, which involved 34 judges:

physicians, surgeons, pharmacists, nurses and risk managers. Lists of 27 scenarios, which should be included as prescribing errors, 8, which should not, and 7, for which judgement will depend on the individual situation, accompanied this definition. The scenarios included in the list were not meant to be comprehensive, but rather to explain a sample of potentially equivocal cases to facilitate decision on whether those scenarios should be classed as errors or not (Dean et al., 2000).

The authors pointed out three important aspects of this definition:

 “Unintentional” – this definition is based on theories of human error and would exclude any risk of harm due to deliberate acts

 “Compared with generally accepted practice” – From the work of Bates et al (1995), a medication error is classified as a preventable adverse drug event (ADE) (Bates et al., 1995). The reference to “generally accepted practice” is based upon the preventability of errors i.e. errors are not acceptable practices. Avery et al (2013) noted that some authors set very high standards for practice, which leads to incredibly high error rates with no acceptability to healthcare professionals (HCP) or policy makers. Using their example, all cases of penicillin allergy could be avoided by never using drugs with a penicillin

structure in patients who have never used penicillin. However, the use of penicillin is

would not lead to an error as long as it was suitable for them (Avery, Barber, et al., 2012;

Avery et al., 2013).

 “Significant” – the Delphi panel felt this word should be included for two reasons:

o It was thought important to clarify between clinically-meaningful prescribing errors and those scenarios where it could not be judged that an error has occurred but where treatment optimization was possible

o It was included to allow for rational errors in the prescribing process, which would not lead to adverse events for the patient. The word “significant” was therefore included to clarify that the definition is of a “clinically meaningful” prescribing error.

Although this definition is now widely used, a small number of critiques of this definition have been published. Avery and colleagues (2012) have responded to critiques of their definition by Ferner and Aronson, who have suggested that developing definitions using consensus-based methods such as the Delphi technique is defective in that it is a definition by committee (Aronson, 2009a; Ferner, 2009; Ferner & Aronson, 2006). The authors of the definition have argued that credibility of research findings is important to practitioners if they are to consider them seriously and use findings meaningfully. They reason that consensus of healthcare professionals provide a validity element to the definition, and that the Delphi technique overcomes the problem of dominance by one or more individuals and eliminates peer pressure – issues commonly associated with committee-based decision-making.

Furthermore, some authors have criticised the inclusion of only “clinically meaningful”

prescribing errors based on the argument that when an error occurs, it may be a pointer to a weakness in the system, and that and that the risk of harm cannot be extrapolated from a single patient to the population(Ferner, 2009; Ferner & Aronson, 2006). However, the term

“clinically meaningful” indicates that there is s category of “clinically insignificant” errors, or errors with minimal risk of harm to the patient, as such this definition does not appear to completely ignore clinically insignificant errors. Perhaps this may be an indication that reported error rates should include an element of severity assessment to increase their clinical relevance (Garfield et al., 2013).

Ferner and Aronson have also suggested that an “attainable standard” should be used in place of “generally accepted practice” because “generally accepted practice” may be poor (Ferner

& Aronson, 2006). Avery and colleagues (2012) have questioned what that attainable standard should be, and by who should such standards are set.

Attainable standards or generally accepted practice however both have something in common – the need to be measured against some form of “good” practice. Patients’

confidence in healthcare and use of medicines, especially at the healthcare professional end of the system, is directly related to how safe clinical practice is. Users of healthcare would expect that any principle and/or policy, which would contribute to the safety and integrity of healthcare and medication use would be attainable and acceptable.

1.4.1.1 Classifying errors

Error classification can be done in many ways. An error can be understood with respect to the behaviour involved, the underlying psychological processes, and in relation to the factors, which contributed to it: a classification such as ‘wrong drug’ describes behaviour of issuing the wrong drug. Such an error will be psychologically classed as a slip (Vincent, 2010).

Classification schemes have been proposed in high-risk industries to aid the preparation of a safety case that outlines what errors might occur. The Predictive Human Error Analysis (PHEA) technique has been generally developed for use in high-risk industries where the actions of single person can be fairly outlined (Vincent, 2010). PHEA uses six main

categories or errors: planning, operation, checking, retrieval, communication, and selection errors. Classifications of errors in healthcare can readily draw from schemes like PHEA. To be useful in practice, error classifications, like definitions should be clear. Clarifying

classifications used is important to facilitate interpretation and usefulness of error data. Error data, which are intended to provide feedback to healthcare providers, need to be relevant to daily practice and facilitate or provide a basis for behaviour or cultural change. It is therefore not surprising that many UK studies sensibly classify errors using the behaviours involved (Avery, Barber, et al., 2012; Barber et al., 2009; Dean et al., 2000; Ghaleb et al., 2010).

Though it may be useful to map such behavioural classifications onto other schemes, such as psychological processes or even a system like PHEA for comparison, this classification appear to communicate more relevantly with healthcare stakeholders.