Discussion

The national smoking prevalence estimates derived from the primary care electronic medical records in THIN have been comparable to those produced by the current gold standard, the GHS, since 2006. This suggests that using the THIN dataset as either an alternative means of monitoring national smoking trends in Britain or to complement national survey data would be valid. The demonstrated comparability between THIN and GHS data suggests that routinely collected smoking information held in all general practices throughout the UK (not just those contributing to THIN) may be useful for monitoring local trends in smoking prevalence, though further work is needed to evaluate the validity of these data for this particular use.

There are several advantages to using THIN over national survey data to monitor national smoking trends—THIN is larger, is released three or four times annually and has a lag of only 3–8 months before clinical data become available. The standard error of the national smoking prevalence estimate derived from THIN is considerably smaller than that derived from the GHS (eg, 0.26 in THIN in 2008 compared with 0.48 in the GHS5), and thus, THIN can potentially provide more precise smoking prevalence estimates nationally and at the level of government office regions. THIN is also much larger than the new Integrated Household Survey and thus again is likely to be able to provide more accurate estimates of smoking prevalence than this new survey. Two postcode-level indicators of deprivation, Townsend Index and Mosaic type, are attached to each patient's records in THIN, and thus, the dataset could also be used to monitor progress towards reducing socioeconomic inequalities in smoking prevalence and health. Also, health-related information may be more complete in primary care data than survey responses, offering a valuable opportunity to use primary care data to investigate relationships between smoking and health outcomes. Conversely, surveys can provide objective detailed contextual information about smoking behaviour, such as the numbers of cigarettes smoked and of quit attempts made; such data may not be available in primary care data, and both data sources are likely to prove complementary. Datasets of primary care records from other countries are available to researchers,13 and similar methods to those employed here could be used to assess the completeness of smoking status recording and the utility of such data for monitoring national smoking prevalence in these countries.

Our assumption that all patients with no smoking status recorded in their THIN records are not current smokers may lead to the underestimation of smoking prevalence, though, as noted already, other work suggests that this assumption is valid.17 Similarly, that a substantial minority of patients′ most recent smoking status was recorded several years before the index may also bias our estimates of the prevalence of current smoking, as some smokers may have since quit and vice versa. However, this is perhaps not a problem in older patients recorded many years previously as never-smokers, as very few people begin smoking after the age of 25 years.4 It is recognised that reliance upon self-reported measures of smoking behaviour in national household surveys such as the GHS may underestimate smoking prevalence, particularly among younger age groups. Although 16- and 17-year-olds complete the GHS questionnaire in private, this is unlikely to be totally successful in encouraging honest answers, and rates of under-reporting might not be constant over time,4 especially given reductions in the social acceptability of smoking. However, if patients misrepresented their smoking behaviour to their doctor, there could also be a degree of under-reporting in primary care data. Observed individual-level agreement between smoking status recorded in patients' medical records and that ascertained through questionnaires suggests that there are minimal data entry errors in primary care records.19 However, the lack of biochemical data to validate patients′ self-recorded smoking status in THIN (and similarly in the GHS) means that we cannot be sure whether smoking status records in either data source are a true reflection of reality. It is unlikely, however, that validated smoking outcomes would ever be used routinely in national population surveys due to the expense incurred.

Young adults are slightly less well represented in the THIN dataset, perhaps because this age group are least likely to be registered with a GP. In addition, the practices contributing to THIN marginally under-represent those serving more deprived populations.15 Smoking prevalence is highest among young adults and lower socioeconomic groups,4 and therefore use of THIN data may slightly underestimate national smoking prevalence, but the comparability between THIN-recorded smoking prevalence and the published national prevalence estimates from the GHS suggests that this is not a major issue. However, the differences between predicted and recorded smoking prevalence in some population subgroups (see supplementary information) suggest that primary care data may not be able to provide accurate prevalence estimates for such subgroups, such as young men. This is perhaps because young men visit their GP relatively infrequently,4 and thus GPs have fewer opportunities to record their smoking status.

General practices that contribute to the THIN dataset undergo assessment to ensure they are using their computer systems correctly, and thus they may not be representative of all British practices. The substantial variation in the completeness of recording in individual practices warrants further investigation and may, at least in part, be explained by differences in the social class structure of their patient populations. The lack of a comparable indicator of social class in the GHS and THIN data means that this could not be used as a variable in the standardisation procedure, though part of the effect of social class is likely to be accounted for by using government office region as a standardisation variable.

A major government-commissioned report in England, the Wanless report, called for the organisations responsible for delivering community health services to make better use of data from primary care to help understand the prevalence of disease risk factors within their local populations.20 THIN practices are not identifiable at a geographical level finer than that of government office regions, and so THIN data cannot be used to monitor local smoking prevalence. Given the observed variation in THIN practices' recording of smoking status, it is not clear whether data from all British practices could be accurate enough for local smoking prevalence monitoring; further research is required. However, the methods used in this study provide a way to compare smoking prevalence estimates from local surveys with data recorded in local GP practices to assess the quality of recorded smoking information. It is possible that practice data in some localities would not be sufficiently complete and, in such areas, practices may need support to optimise their recording of smoking status before their data could be used to monitor smoking prevalence locally. However, once the quality of smoking status recording is deemed acceptable, data from all practices throughout the UK may offer a less costly means of monitoring smoking prevalence than commissioned surveys.

In conclusion, this study shows that primary care medical records data from THIN may be useful for monitoring national smoking prevalence in Britain, and the strengths of the THIN dataset mean that it could potentially complement the use of national surveys. Further work is needed to determine whether primary care data from practices not included in the THIN database are of sufficient quality for monitoring trends in smoking prevalence and, in particular, whether such data are appropriate for monitoring prevalence in smaller localities.