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Detecting and visualizing outliers in provider profiling via funnel plots and mixed effect models
Francesca Ieva1, Anna Maria Paganoni
1MOX - Modellistica e Calcolo Scientifico, Dipartimento di Matematica, Politecnico di Milano, via Bonardi 9, 20133, Milan, Italy, francesca.ieva@polimi.it.
Health Care Management Science
|January 10, 2014
Summary
This study introduces the funnel plot, a graphical tool to identify outlier hospitals treating Acute Myocardial Infarction (AMI) patients. It compares this method
Area of Science:
- Healthcare analytics
- Medical informatics
- Public health surveillance
Background:
- Acute Myocardial Infarction (AMI) patient outcomes can vary significantly between hospitals.
- Identifying performance outliers is crucial for quality improvement in cardiovascular care.
- Administrative databases offer a rich source for analyzing in-hospital mortality rates.
Purpose of the Study:
- To evaluate the effectiveness of the funnel plot as a graphical diagnostic tool for detecting outlier hospitals in Acute Myocardial Infarction (AMI) treatment.
- To compare the performance of the funnel plot with traditional parametric mixed-effects models for outlier detection.
- To apply these methods to real-world AMI hospitalization data from a regional administrative database.
Main Methods:
- Utilizing a funnel plot, a graphical method for assessing heterogeneity and identifying outliers in performance metrics.
- Applying parametric mixed-effects models to analyze in-hospital mortality data.
- Comparing the concordance and discrepancies between outlier identification using graphical tools versus statistical models.
Main Results:
- The funnel plot effectively identified potential outlier hospitals based on in-hospital mortality rates for Acute Myocardial Infarction (AMI) patients.
- Results from the funnel plot showed good agreement with, but also offered complementary insights to, those from parametric mixed-effects models.
- The graphical approach provided an intuitive visualization of hospital performance variation.
Conclusions:
- The funnel plot is a valuable and accessible tool for identifying outlier hospitals in the context of Acute Myocardial Infarction (AMI) care.
- Graphical diagnostic tools can serve as a practical complement or alternative to complex statistical models for quality monitoring.
- This approach aids in focusing quality improvement efforts on hospitals with potentially suboptimal outcomes.
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