We propose the use of a graphical diagnostic tool (the funnel plot) to detect outliers among hospitals that treat patients affected by Acute Myocardial Infarction (AMI). We consider an application to data on AMI hospitalizations arising from administrative databases. The outcome of interest is the in-hospital mortality, a variable indicating if the patient has been discharged dead or alive. We then compare the results obtained by graphical diagnostic tools with those arising from fitting parametric mixed effects models to the same data.

Statistical Tools for Detecting and Visualizing Outliers in Provider Profiling: an effective decisional support to healthcare regulation

IEVA, FRANCESCA;PAGANONI, ANNA MARIA
2013-01-01

Abstract

We propose the use of a graphical diagnostic tool (the funnel plot) to detect outliers among hospitals that treat patients affected by Acute Myocardial Infarction (AMI). We consider an application to data on AMI hospitalizations arising from administrative databases. The outcome of interest is the in-hospital mortality, a variable indicating if the patient has been discharged dead or alive. We then compare the results obtained by graphical diagnostic tools with those arising from fitting parametric mixed effects models to the same data.
2013
Proceedings of SCo2013, 8th Conference
9788864930190
Funnel Plot; Mixed Effect Models; Overdispersion; Provider Profiling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/731978
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