Shaping quality: the use of performance polygons for multidimensional presentation and interpretation of qualitative performance data T.M. Cook, M. Coupe,

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Shaping quality: the use of performance polygons for multidimensional presentation and interpretation of qualitative performance data T.M. Cook, M. Coupe, T. Ku British Journal of Anaesthesia Volume 108, Issue 6, Pages 953-960 (June 2012) DOI: 10.1093/bja/aes026 Copyright © 2012 The Author(s) Terms and Conditions

Fig 1 Stepwise construction of a performance polygon: (a) an outcome is plotted from worst to best, (b) further outcomes are added all radiating from the same origin, (c) the maximal limits of the polygon are completed by joining points indicating ‘best outcomes’ and the index polygon is plotted by joining the performance measures on each outcome spoke (this is usually shaded but is left unshaded for clarity here), and (d) comparator polygons are added. British Journal of Anaesthesia 2012 108, 953-960DOI: (10.1093/bja/aes026) Copyright © 2012 The Author(s) Terms and Conditions

Fig 2 Performance polygon: individual anaesthetist’s performance with 95th and 5th centiles as the comparator. British Journal of Anaesthesia 2012 108, 953-960DOI: (10.1093/bja/aes026) Copyright © 2012 The Author(s) Terms and Conditions

Fig 3 Performance polygon: individual anaesthetist’s performance compared with own previous performance. British Journal of Anaesthesia 2012 108, 953-960DOI: (10.1093/bja/aes026) Copyright © 2012 The Author(s) Terms and Conditions

Fig 4 Performance polygon: individual anaesthetist’s performance with absolute or ‘benchmark’ performance as the comparator. British Journal of Anaesthesia 2012 108, 953-960DOI: (10.1093/bja/aes026) Copyright © 2012 The Author(s) Terms and Conditions

Fig 5 Performance polygon: surgical team performance for total knee arthroplasty. British Journal of Anaesthesia 2012 108, 953-960DOI: (10.1093/bja/aes026) Copyright © 2012 The Author(s) Terms and Conditions

Fig 6 Performance polygons of real postoperative data from one anaesthetist’s own data (self-collected). In (a), these data are presented as absolute data with the individual axes each ranging from 0 to 100. Percentages indicate the anaesthetist’s performance. In (b), the authors have agreed benchmarks with limits representing poor performance (small comparator polygon) and high-quality performance (large comparator polygon). The change in the shape and area of the polygons in (a) and (b) illustrates the importance of choice of comparator data and limits. British Journal of Anaesthesia 2012 108, 953-960DOI: (10.1093/bja/aes026) Copyright © 2012 The Author(s) Terms and Conditions