Cited by 832Healthcare Quality and ManagementStatistical Methods in EpidemiologyMeta-analysis and systematic reviews

Funnel plots for comparing institutional performance

Spiegelhalter, David J.·2005·Statistics in Medicine

Abstract

‘Funnel plots’ are recommended as a graphical aid for institutional comparisons, in which an estimate of an underlying quantity is plotted against an interpretable measure of its precision. ‘Control limits’ form a funnel around the target outcome, in a close analogy to standard Shewhart control charts. Examples are given for comparing proportions and changes in rates, assessing association between outcome and volume of cases, and dealing with over‐dispersion due to unmeasured risk factors. We conclude that funnel plots are flexible, attractively simple, and avoid spurious ranking of institutions into ‘league tables’. Copyright © 2004 John Wiley & Sons, Ltd.

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References 25 · Cited by 832

Authors
Spiegelhalter, D. J.
Affiliations
MRC Biostatistics Unit (GB)
Corresponding author
Spiegelhalter, David J.
Venue
Statistics in Medicine
Publisher
Wiley
Published
2004-11-29
Volume
24
Issue
8
Pages
1185-1202
ISSN
  • 0277-6715 (ISSN-L)
  • 1097-0258
OpenAlex
W2148621962
Cited by
832
References
25
Citations by year
2026: 37 · 2025: 27 · 2024: 29 · 2023: 27 · 2022: 48 · 2021: 49 · 2020: 64 · 2019: 50 · 2018: 55 · 2017: 57 · 2016: 54 · 2015: 54 · 2014: 40 · 2013: 63 · 2012: 38
FWCI
13.89
Type
journal article
Language
en
Open access
closed
Locations
  • Statistics in Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › Health Information Management › Healthcare Quality and Management
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords
funnel plot, control limits, Shewhart control charts, proportion, rate changes, overdispersion, league tables
MeSH terms
Adolescent, Coronary Artery Bypass, Biometry, Cross-Sectional Studies, England, Female, Cardiac Surgical Procedures, Humans, Infant, Pregnancy, Pregnancy in Adolescence, Quality Assurance, Health Care, Risk Factors, Odds Ratio, Outcome Assessment, Health Care

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