Lisa Szatkowski

Can data from primary care medical records be used to monitor national smoking prevalence

Background Data from primary care records could potentially provide more comprehensive population-level information on smoking prevalence at lower cost and in a more timely fashion than commissioned national surveys. Therefore, we compared smoking prevalence calculated from a database of primary care electronic medical records with that from a ‘gold standard’ national survey to determine whether or not medical records can provide accurate population-level data on smoking. Methods For each year from 2000 to 2008, the annual recorded prevalence of current smoking among patients in The Health Improvement Network (THIN) Database was compared with the ‘General Household Survey (GHS)-predicted prevalence’ of smoking in the THIN population, calculated through indirect standardisation by applying age-, sex- and region-specific smoking rates from the corresponding GHS to the THIN population. Results Completeness of smoking data recording in THIN improved steadily in the study period. By 2008, there was good agreement between recorded smoking prevalence in THIN and the GHS-predicted prevalence; the GHS-predicted prevalence of current smoking in the THIN population was 21.8% for men and 20.2% for women, and the recorded prevalence was 22.4% and 18.9%, respectively. Conclusions The prevalence of current smoking recorded within THIN has converged towards that which would be expected if GHS smoking rates are applied to the THIN population. Data from electronic primary care databases such as THIN may provide an alternative means of monitoring national smoking prevalence.

The impact of the Quality and Outcomes Framework (QOF) on the recording of smoking targets in primary care medical records: cross-sectional analyses from The Health Improvement Network (THIN) database

BackgroundSmoking is a UK public health threat but GPs can be effective in helping patients to quit; consequently, the Quality and Outcomes Framework (QOF) incentivises the recording of smoking status and delivery of cessation advice in patients’ medical records. This study investigates the association between smoking-related QOF targets and such recording, and the factors which influence these clinical activities.MethodsFor 2000 to 2008, using medical records in The Health Improvement Network (THIN) database, the annual proportions of i) patients who had a record of smoking status made in the previous 27 months and ii) current smokers recorded as receiving cessation advice in the previous 15 months were calculated. Then, for all patients at selected points before and after the QOF’s implementation, data on gender, age, Townsend score, and smoking-related morbidity were extracted. Multivariate logistic regression was used to investigate individual-level characteristics associated with the recording of smoking status and cessation advice.ResultsRapid increases in recording smoking status and advice occurred around the QOF’s introduction in April 2004. Subsequently, compliance to targets has been sustained, although rates of increase have slowed. By 2008 64.5% of patients aged 15+ had smoking status documented in the previous 27 months and 50.5% of current smokers had cessation advice recorded in the last 15 months. Adjusted odds ratios show that, both before and after the introduction of the QOF, those with chronic medical conditions, greater social deprivation and women were more likely to have a recent recording of smoking status or cessation advice. Since the QOF’s introduction, the strongest characteristic associated with recording activities was the presence of co-morbidity. An example of this was patients with COPD, who in 2008, were 15.38 (95% CI 13.70-17.27) times and 11.72 (95% CI 10.41-13.21) times more likely to have a record of smoking status and cessation advice, respectively.ConclusionsRates of recording smoking status and cessation advice plateaued after large increases during the QOF’s introduction; however, recording remains most strongly associated with the presence of chronic disease as specified by the QOF, and suggests that incentivised targets have a direct effect on clinical behaviour.

Tobacco display and brand communication at the point of sale: implications for adolescent smoking behaviour

Background In England, point-of-sale (PoS) displays in larger shops were prohibited in April 2012, with an exemption for smaller retailers until 2015. The aim of this study was to examine the association between tobacco displays and brand communication at the PoS and adolescent smoking behaviour, and to assess the potential benefits likely to accrue from this legislation. Methods Self-completion questionnaire survey in students aged 11–15 years in March 2011. Results The odds of ever-smoking doubled for those visiting shops almost daily relative to less than once a week (OR 2.23, 95% CI 1.40 to 3.55), and susceptibility increased by around 60% (OR 1.62, 95% CI 1.25 to 2.10). Noticing tobacco on display every time during store visits increased the odds of susceptibility more than threefold compared with never noticing tobacco (OR 3.15, 95% CI 1.52 to 6.54). For each additional tobacco brand recognised at the PoS, the adjusted odds of being an ever-smoker increased by 5% (OR 1.05, 95% CI 1.03 to 1.06) and of susceptibility by 4% (OR 1.04, 95% CI 1.02 to 1.05). The association between frequency of visiting stores and susceptibility was predominantly due to exposure in small shops. Conclusions Exposure to and awareness of PoS displays and brands in displays were associated with smoking susceptibility. The association between PoS display exposure and smoking susceptibility was predominantly due to exposure in small shops. These findings suggest that a one-off, comprehensive tobacco display ban is the recommended approach for countries considering a display ban.

The association between smoking cessation and glycaemic control in patients with type 2 diabetes: A THIN database cohort study

BACKGROUND Smoking increases the risk of developing type 2 diabetes. However, several population studies also show a higher risk in people 3-5 years after smoking cessation than in continuing smokers. After 10-12 years the risk equates to that of never-smokers. Small cohort studies suggest diabetes control deteriorates temporarily during the first year after quitting. We examined whether or not quitting smoking was associated with altered diabetes control in a population study, for how long this association persisted, and whether or not this association was mediated by weight change. METHODS We did a retrospective cohort study (Jan 1, 2005, to Dec 31, 2010) of adult smokers with type 2 diabetes using The Health Improvement Network (THIN), a large UK primary care database. We developed adjusted multilevel regression models to investigate the association between a quit event, smoking abstinence duration, change in HbA1c, and the mediating effect of weight change. FINDINGS 10 692 adult smokers with type 2 diabetes were included. 3131 (29%) quit smoking and remained abstinent for at least 1 year. After adjustment for potential confounders, HbA1c increased by 0·21% (95% CI 0·17-0·25; p<0·001; [2·34 mmol/mol (95% CI 1·91-2·77)]) within the first year after quitting. HbA1c decreased as abstinence continued and became comparable to that of continual smokers after 3 years. This increase in HbA1c was not mediated by weight change. INTERPRETATION In type 2 diabetes, smoking cessation is associated with deterioration in glycaemic control that lasts for 3 years and is unrelated to weight gain. At a population level, this temporary rise could increase microvascular complications. FUNDING National Institute for Health Research School for Primary Care Research.

Does the introduction of comprehensive smoke‐free legislation lead to a decrease in population smoking prevalence?

AIMS To investigate changes in population smoking prevalence in jurisdictions which have implemented comprehensive smoke-free legislation, taking into account long-term trends in smoking behaviour. DESIGN Interrupted time series analysis of population-level survey data using segmented regression. SETTING Twenty-one countries, American states or Canadian provinces which have implemented comprehensive smoke-free legislation. PARTICIPANTS Respondents sampled in large representative surveys of smoking prevalence. MEASUREMENTS For each jurisdiction, segmented regression models quantify any upwards or downwards trend in smoking prevalence prior to the introduction of smoke-free legislation, any immediate change in the level of smoking prevalence at the time smoke-free legislation was introduced, and any change in the trend in smoking prevalence post-legislation compared to the pre-legislation period. FINDINGS In all but three locations there was a statistically significant decline in smoking prevalence prior to the introduction of smoke-free legislation. In two locations, Washington and the Republic of Ireland, there was an immediate decline in the level of smoking prevalence at the introduction of legislation. In six American states there was a significant change in the rate of decline in smoking prevalence, with smoking prevalence declining more steeply in the post-legislation period compared to the pre-legislation period. No change in the level or trend of population smoking prevalence was seen in 13 of the 21 locations studied. CONCLUSIONS The introduction of comprehensive smoke-free legislation has increased the rate at which smoking prevalence was declining in some locations, but in the majority of jurisdictions had no measureable impact on existing trends in smoking prevalence.

Diverging Trends in Smoking Behaviors According to Mental Health Status

INTRODUCTION People with mental health disorders are much more likely to smoke compared to those who do not. This study investigates recent trends in smoking behaviors among both these populations in England. METHODS We used survey responses from adults (aged 16 years and older) living in households in England who participated in the Health Survey for England from 1993 to 2011 (n = 11,300 per year on average). Linear regression was used to quantify annual changes over the time period in smoking prevalence, daily cigarette consumption, and desire to quit among respondents with and without 2 indicators of mental disorder (self-reported longstanding mental illness and recent use of psychoactive medication). RESULTS Among survey respondents who did not report a longstanding mental illness, there were long-term declines in smoking prevalence (-0.48% per year, 95% confidence interval [CI] = -0.56 to -0.40) and daily cigarette consumption (-0.14% per year, 95% CI = -0.17 to -0.11). Similar declines were also seen among respondents not taking psychoactive medications. However, there were no long-term changes in smoking prevalence and cigarette consumption among respondents who reported these indicators of mental disorder, although smoking prevalence among those taking psychoactive medications may have declined during the later part of the study period. Smokers both with and without the 2 indicators of mental disorder showed similar levels of desire to quit smoking. CONCLUSIONS Smoking is largely unchanged since 1993 among those with indicators of longstanding mental disorders or recent psychoactive medication usage, although declines have been observed among those without such indicators of mental disorder.

Validation of The Health Improvement Network (THIN) primary care database for monitoring prescriptions for smoking cessation medications

Evaluation of tobacco policy requires high quality and timely data on smoking cessation behaviour in the general population and in relevant target groups. Electronic primary care databases have the potential to provide a valuable source of data due to their size and continuity, and the availability of demographic and socioeconomic data. We therefore sought to investigate whether The Health Improvement Network (THIN) prescribing data are complete and can therefore be used to monitor trends in the prescribing of smoking cessation medications.

The impact of media campaigns on smoking cessation activity: a structural vector autoregression analysis

AIMS To evaluate the effect of tobacco control media campaigns and pharmaceutical company-funded advertising for nicotine replacement therapy (NRT) on smoking cessation activity. DESIGN Multiple time series analysis using structural vector autoregression, January 2002-May 2010. SETTING England and Wales. DATA SOURCES Tobacco control campaign data from the Central Office of Information; commercial NRT campaign data; data on calls to the National Health Service (NHS) stop smoking helpline from the Department of Health; point-of-sale data on over-the-counter (OTC) sales of NRT; and prescribing data from The Health Improvement Network (THIN), a database of UK primary care records. MEASUREMENTS Monthly calls to the NHS stop smoking helpline and monthly rates of OTC sales and prescribing of NRT. FINDINGS A 1% increase in tobacco control television ratings (TVRs), a standard measure of advertising exposure, was associated with a statistically significant 0.085% increase in calls in the same month (P = 0.007), and no statistically significant effect in subsequent months. Tobacco control TVRs were not associated with OTC NRT sales or prescribed NRT. NRT advertising TVRs had a significant effect on NRT sales which became non-significant in the seasonally adjusted model, and no significant effect on prescribing or calls. CONCLUSIONS Tobacco control campaigns appear to be more effective at triggering quitting behaviour than pharmaceutical company NRT campaigns. Any effect of such campaigns on quitting behaviour seems to be restricted to the month of the campaign, suggesting that such campaigns need to be sustained over time.

The delivery of smoking cessation interventions to primary care patients with mental health problems

AIMS To quantify the extent to which smokers with indicators of poor mental health receive smoking cessation support in primary care consultations compared with those without. DESIGN Cross-sectional study within a database of electronic primary care medical records. SETTING A total of 495 general practices in the United Kingdom contributing data to The Health Improvement Network (THIN) database. PARTICIPANTS A total of 2 493 085 patients aged 16+ registered with a THIN practice for the year from 1 July 2009 to 30 June 2010. MEASUREMENTS The proportion of patients with a diagnostic Read code or British National Formulary (BNF) drug code indicating a mental health diagnosis or psychoactive medication prescription, respectively, who smoke and who have cessation advice or a smoking cessation medication prescription recorded during consultations within the 1-year study period. FINDINGS Of 32 154 smokers, 50.6% [95% confidence interval (CI): 50.0-51.2] with a mental health diagnosis and 49.3% (95% CI: 49.0-49.7) of 96 285 smokers prescribed a psychoactive medication had a record of cessation advice, higher than the prevalence of advice recording in smokers without these indicators (33.4%, 95% CI: 33.3-33.6). Similarly, smoking cessation medication prescribing was higher: 11.2% (95% CI: 10.8-11.6) of smokers with a mental health diagnosis and 11.0% (95% CI: 10.8-11.2) of smokers prescribed psychoactive medication received a prescription, compared with 6.73% of smokers without these indicators (95% CI: 6.65-6.81). Smoking cessation support was offered in a lower proportion of consultations for smokers with indicators of poor mental health than for those without. Advice was recorded in 7.9% of consultations with smokers with a mental health diagnosis, 8.2% of consultations with smokers prescribed psychoactive medication and 12.3% of consultations with smokers without these indicators; comparable figures for prescribing of cessation medication were 2.9%, 3.2% and 4.4%, respectively. CONCLUSIONS Approximately half of smokers with indicators of poor mental health receive advice to quit during primary care consultations in the United Kingdom, and one in 10 receive a cessation medication. Interventions are lower per consultation for smokers with mental health indicators compared with smokers without mental health indicators.

Prescribing of smoking cessation medication in England since the introduction of varenicline

AIMS To estimate the effect of the introduction of a new smoking cessation medication, varenicline, and the publication of guidance related to its use, on trends in prescribing of smoking cessation medications in England. DESIGN Interrupted time series analysis of primary care data on prescribing of smoking cessation medication using autoregressive integrated moving average (ARIMA) modelling. SETTING A total of 446 general practices included in The Health Improvement Network (THIN), a database of UK electronic primary care records. PARTICIPANTS All primary care patients registered with a THIN practice in England. MEASUREMENTS Monthly rates of prescribing of varenicline, nicotine replacement therapy (NRT) and bupropion per 100 000 patients registered with a THIN practice between June 2000 and June 2009. FINDINGS NRT was the most commonly prescribed stop smoking medication, and bupropion the least frequently prescribed. After its introduction in December 2006 varenicline rapidly became the second most commonly prescribed drug. There was no statistically significant change in overall prescribing for smoking cessation medications after its introduction (P = 0.760), or after the publication of the related guidance in July 2007 (P = 0.134). CONCLUSIONS Soon after being introduced in England, varenicline was widely prescribed; after nicotine replacement therapy it was the most commonly prescribed cessation medication. However, this does not appear to have increased overall rates of prescribing for smoking cessation medication.