2017
DOI: 10.1177/0962280217700169
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Guidelines on constructing funnel plots for quality indicators: A case study on mortality in intensive care unit patients

Abstract: Funnel plots are graphical tools to assess and compare clinical performance of a group of care professionals or care institutions on a quality indicator against a benchmark. Incorrect construction of funnel plots may lead to erroneous assessment and incorrect decisions potentially with severe consequences. We provide workflow-based guidance for data analysts on constructing funnel plots for the evaluation of binary quality indicators, expressed as proportions, risk-adjusted rates or standardised rates. Our gui… Show more

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Cited by 36 publications
(38 citation statements)
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“…For creating funnel plots, we used the funnelcompar command in stata statistical package version 15 (which is based on Spiegelhalter), 23 we identified whether SMR relative to the number of index admissions 24 was within acceptable limits (i.e. within 2 SD; 95%), between 2 and 3 SD, or beyond 3 SD (99.8%).…”
Section: Methodsmentioning
confidence: 99%
“…For creating funnel plots, we used the funnelcompar command in stata statistical package version 15 (which is based on Spiegelhalter), 23 we identified whether SMR relative to the number of index admissions 24 was within acceptable limits (i.e. within 2 SD; 95%), between 2 and 3 SD, or beyond 3 SD (99.8%).…”
Section: Methodsmentioning
confidence: 99%
“…The 95% (2SD) and 99.8% (3SD) control limits were constructed using the exact binomial methods to identify outliers. 14,15 These control limits reflect 'moderate' and 'moderate to strong' evidence, respectively, against the null hypothesis that the proportions adhering to NICE by practice are as expected, given…”
Section: Discussionmentioning
confidence: 96%
“…This method is based on scatter plots of the treatment effect estimated by individual studies vs. a measure of study size or precision. In this graphical representation, larger and more precise studies are plotted at the top, near the combined effect size, while smaller and less precise studies show a wider distribution below (17). All statistical tests were two sided, and differences were considered significant if p < 0.05.…”
Section: Discussionmentioning
confidence: 99%