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The Use of Funnel Plots with Regression As a Tool to Visually Compare HIV Treatment Outcomes Between Centres Adjusting for Patient Characteristics and Size: a UK Collaborative HIV Cohort Study

Overview
Journal HIV Med
Publisher Wiley
Specialty Infectious Diseases
Date 2018 Apr 16
PMID 29656588
Citations 1
Authors
M Gompels
S Michael
S Jose
T Hill
R Trevelion
C A Sabin
M T May
Affiliations
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Abstract

Objectives: A measure used for assessing the effectiveness of HIV care and comparing clinical centres is the proportion of people starting antiretroviral therapy (ART) with viral suppression (VS) after 1 year. We propose a method that adjusts for patients' demographic characteristics, and visually compares this measure between different sites accounting for centre size.

Methods: We analysed viral load measurements for UK Collaborative HIV Cohort (UK CHIC) patients starting ART between 2006 and 2013. We used logistic regression to estimate the proportion with VS after 1 year of ART adjusted for patient mix (in terms of age and a combined gender/ethnicity/acquisition mode variable) and calendar year. We compared outcomes between centres using funnel plots which account for centre size.

Results: The overall proportion of the cohort with VS 1 year after starting ART was 90% and increased from 83% to 93% between 2006 and 2013. VS was lower in younger individuals. White men who have sex with men (MSM) had the highest (94%), and black African (81%) and white (82%) heterosexual women the lowest proportions achieving VS. Comparing the unadjusted funnel plot with the adjusted, there were movements of some centres from outside to inside the 95% contour limits, which was largely explained by the patient mix of these centres.

Conclusions: VS 1 year after ART start was associated with demographic characteristics and centre size; therefore, to compare the performances of centres, adjustment for these factors is required. Adjusted funnel plot is an effective tool which accounts for both the demographic characteristics and the centre size. Social factors, rather than treatment decisions within the control of the centres, may drive differences in outcomes.

Citing Articles

Allocating treatment resources for hepatitis C in the UK: a constrained optimization modelling approach.

Han R, Liang S, Francois C, Aballea S, Clay E, Toumi M J Mark Access Health Policy. 2021; 9(1):1887664.

PMID: 33828822 PMC: 8008927. DOI: 10.1080/20016689.2021.1887664.

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