In this work 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 recorded in the administrative databases of our regional district. 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.

Detecting and visualizing outliers in provider profiling via funnel plots and mixed effect models / F. Ieva, A.M. Paganoni. - In: HEALTH CARE MANAGEMENT SCIENCE. - ISSN 1386-9620. - 18:2(2015 Jun), pp. 166-172. [10.1007/s10729-013-9264-9]

Detecting and visualizing outliers in provider profiling via funnel plots and mixed effect models

F. Ieva
Primo
;
2015-06

Abstract

In this work 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 recorded in the administrative databases of our regional district. 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.
acute myocardial infarction; funnel plots; generalized linear mixed models; in-hospital survival; provider profiling
Settore SECS-S/01 - Statistica
Settore MED/01 - Statistica Medica
10-gen-2014
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/232843
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