Objectives: To determine to what extent underlying
data published as part of Quality and Outcomes
Framework (QOF) can be used to estimate smoking
prevalence within practice populations and local
areas and to explore the usefulness of these
estimates.
Design: Cross-sectional, observational study of QOF
smoking data. Smoking prevalence in general
practice populations and among patients with chronic
conditions was estimated by simple manipulation of
QOF indicator data. Agreement between estimates
from the integrated household survey (IHS) and
aggregated QOF-based estimates was calculated. The
impact of including smoking estimates in negative
binomial regression models of counts of premature
coronary heart disease (CHD) deaths was assessed.
Setting: Primary care in the East Midlands.
Participants: All general practices in the area of
study were eligible for inclusion (230). 14 practices
were excluded due to incomplete QOF data for the
period of study (2006/2007–2012/2013). One
practice was excluded as it served a restricted
practice list.
Measurements: Estimates of smoking prevalence in
general practice populations and among patients with
chronic conditions.
Results: Median smoking prevalence in the practice
populations for 2012/2013 was 19.2% (range
5.8–43.0%). There was good agreement (mean
difference: 0.39%; 95% limits of agreement (−3.77,
4.55)) between IHS estimates for local authority
districts and aggregated QOF register estimates.
Smoking prevalence estimates in those with chronic
conditions were lower than for the general population
(mean difference −3.05%), but strongly correlated
(Rp=0.74, p<0.0001). An important positive
association between premature CHD mortality and
smoking prevalence was shown when smoking
prevalence was added to other population and service
characteristics.
Conclusions: Published QOF data allow useful
estimation of smoking prevalence within practice
populations and in those with chronic conditions; the
latter estimates may sometimes be useful in place of
the former. It may also provide useful estimates of
smoking prevalence in local areas by aggregating
practice based data.