• Br J Anaesth · Jun 2012

    Shaping quality: the use of performance polygons for multidimensional presentation and interpretation of qualitative performance data.

    • T M Cook, M Coupe, and T Ku.
    • Department of Anaesthesia, Royal United Hospital, Combe Park, Bath BA1 3NG, UK. timcook007@googlemail.com
    • Br J Anaesth. 2012 Jun 1;108(6):953-60.

    BackgroundMeasuring outcomes and quality in anaesthesia is challenging. In the UK, there is increased focus on these as a result of changes in Department of Health strategy and the imminent introduction of mandatory revalidation for all doctors. A definition of quality may differ according to the observer's standpoint and numerous performance measures may contribute to overall quality. Patients, surgeons, anaesthetic assistants, recovery nurses, managers, and anaesthetic peers are each likely to have their own perspective on 'anaesthetic quality' and would perhaps suggest different metrics to measure it. Speed, efficiency, cost, interpersonal skills, complication rates, patient recorded outcome measures, and satisfaction are all valid as quality measures, but none alone captures anaesthetic quality. Performance data are frequently presented as single-dimension measurements (e.g. pain, postoperative nausea and vomiting, patient satisfaction), but this does not address the fact that two or more domains may be closely related (e.g. use of regional anaesthesia and quality of analgesia) or in opposition (e.g. use of regional anaesthesia and speed).MethodsWe introduce the concept of a 'performance polygon' as a tool to represent multidimensional performance assessment. This method of data presentation encourages balanced appraisal of anaesthetic quality.ResultsPerformance polygons may be used to compare individual performance with peers, published outcome norms, trends in performance over time, to explore aspects of team performance and potentially capture data that are required for medical revalidation.ConclusionsPerformance polygons enable easy comparison with any relevant data set and are a visual tool that potentially has wider applications in healthcare quality improvement.

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