Using funnel plots in public health surveillance

Abstract

BackgroundPublic health surveillance is often concerned with the analysis of health outcomes over small areas. Funnel plots have been proposed as a useful tool for assessing and visualizing surveillance data, but their full utility has not been appreciated (for example, in the incorporation and interpretation of risk factors).MethodsWe investigate a way to simultaneously focus funnel plot analyses on direct policy implications while visually incorporating model fit and the effects of risk factors. Health survey data representing modifiable and nonmodifiable risk factors are used in an analysis of 2007 small area motor vehicle mortality rates in Alberta, Canada.ResultsSmall area variations in motor vehicle mortality in Alberta were well explained by the suite of modifiable and nonmodifiable risk factors. Funnel plots of raw rates and of risk adjusted rates lead to different conclusions; the analysis process highlights opportunities for intervention as risk factors are incorporated into the model. Maps based on funnel plot methods identify areas worthy of further investigation.ConclusionsFunnel plots provide a useful tool to explore small area data and to routinely incorporate covariate relationships in surveillance analyses. The exploratory process has at each step a direct and useful policy-related result. Dealing thoughtfully with statistical overdispersion is a cornerstone to fully understanding funnel plots.

Establishing achievable benchmarks for quality improvement in systemic therapy for early‐stage breast cancer

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“…20,21 For eligible institutions, the rate was defined as the percentage of patients meeting the QI recommendations and was plotted against the number of eligible patients from that institution. 20,21 For eligible institutions, the rate was defined as the percentage of patients meeting the QI recommendations and was plotted against the number of eligible patients from that institution.…”

Funnel plots and choropleth maps in cancer risk communication: a comparison of tools for disseminating population-based incidence data to stakeholders

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The significance of risk adjustment for the assessment of results in intensive care. : An analysis of risk adjustment models used in Swedish intensive care.

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