[An analysis of the effectiveness of external quality assurance programmes using changes in quality indicators of individual hospitals]. / Wirksamkeitsanalyse externer Qualitätssicherungsmaßnahmen anhand von Veränderungen in Qualitätskennzahlen einzelner Krankenhäuser.

Judging the effectiveness of external quality assurance programmes by comparing current performance with unadjusted regional or national crude averages is misleading because the influence of the actual size of the populations under consideration as well as the variance of performance between hospitals is underestimated. Not only do these artefacts lead to a general overestimation of changes in regional averages. They also may lead to a ranking confounded by regional size. An assessment at unit level circumvents these difficulties. The differential grading of degree of departure of a unit's performance from national targets available from funnel plots allows, in addition, for the discrimination between effects due to the monitoring institution and achievements attributable to the hospital under surveillance. A central role is played by the scoring system adopted for evaluating incremental changes of performance indicator values in successive years. The following proposal is intended to both assist the assessment of effectiveness of quality assurance programmes and identify areas requiring urgent improvement. Bavarian quality assurance data (BAQ 1995) are used to illustrate the method.

[Comparison of quality by means of funnel plots--a plea for a uniform methodology]. / Qualitätsvergleiche mit Funnelplots--Plädoyer für eine einheitliche Methodik.

Vertical bar charts depicting unit event rates sorted in ascending order enjoy widespread usage in external quality assurance. Unfortunately they suggest a spurious ranking resulting from instability in the percentile distribution chiefly caused by varying denominators. The popular remedy of simply excluding units below a minimum threshold would solve the problem only partially since units with few operations per annum may evade evaluation altogether merely by the grace of their size. Compared with alternative solutions reviewed in this article Spiegelhalter's funnel plots exhibit clear advantages over statistical control charts or Bayesian modelling. A major drawback of control charts at present is that data are still widely transferred on a yearly rather than a quarterly or even monthly basis. The chief disadvantage of Bayesian modelling lies in the difficulty of obtaining consensus on the required prior distributions. Funnel plots on the other hand provide a flexible and sample size dependent uniform approach while at the same time offering an intuitive interpretation of volume effects. The addition of control and warning limits allows for formal assessment of deviations from target values.