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 guidelines assume the following
steps: (1) defining policy level input; (2) checking the quality of models used
for case-mix correction; (3) examining whether the number of observations per
hospital is sufficient; (4) testing for overdispersion of the values of the
quality indicator; (5) testing whether the values of quality indicators are
associated with institutional characteristics; and (6) specifying how the funnel
plot should be constructed. We illustrate our guidelines using data from the
Dutch National Intensive Care Evaluation registry. We expect that our guidelines
will be useful to data analysts preparing funnel plots and to registries, or
other organisations publishing quality indicators. This is particularly true if
these people and organisations wish to use standard operating procedures when
constructing funnel plots, perhaps to comply with the demands of
certification.