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Updated: Jun 5, 2026

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

Published on: March 22, 2022

Displaying random variation in comparing hospital performance.

A M van Dishoeck¹, C W N Looman, E C M van der Wilden-van Lier

¹Department of Public Health, Center for Medical Decision Making, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands. a.m.vandishoeck@erasmusmc.nl

BMJ Quality & Safety

|January 14, 2011

Summary

Hospital performance rankings can be misleading due to random variation. Visualizing data with funnel plots helps account for this uncertainty when assessing hospital quality.

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Last Updated: Jun 5, 2026

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

Published on: March 22, 2022

Area of Science:

Healthcare quality assessment
Hospital performance metrics
Statistical analysis in healthcare

Background:

Transparency in healthcare quality is increasingly vital.
Hospital performance is often assessed using various indicators.
Rank-order comparisons can be skewed by random variation and case-mix differences.

Purpose of the Study:

To compare graphical displays for assessing the impact of random variation on Dutch hospital quality of care differences.

Main Methods:

Analysis of 2005 data for 97 Dutch hospitals across three performance indicators.
Calculation of confidence intervals (CIs) for point estimates and simulated ranks using bootstrap sampling.
Visualization of random variation's influence using forest plots, funnel plots, and rank plots.

Main Results:

Statistically significant differences were observed across most performance indicators (p<0.001).
Confidence intervals revealed few hospitals performed significantly better or worse.
Funnel plots effectively represented inter-hospital differences and associated uncertainty; rank plots indicated high uncertainty in rankings.

Conclusions:

Random variation is a critical factor in evaluating individual hospital performance, despite statistically significant differences.
Funnel plots offer interpretable insights into hospital performance, incorporating random variation effects.