There are some limitations to this things analysis. The EMR Health Factors data are collected during face-to-face interactions and may be subject to underreporting. Our ��gold standard�� measurements for smoking are based on self-completed survey data rather than a biological assessment for smoking and may also be subject to underreporting. Another limitation is that some of the Health Factors prompts to providers are inquiring about tobacco use, which can include smokeless tobacco, pipes, and cigars and are not necessarily restricted to cigarette smoking. However, we were careful to not include Health Factors data that explicitly specified smokeless tobacco use to define smoking status. Additionally, we acknowledge that our approach of using the most frequent Health Factors data entry can result in potential for misclassification, particularly of recent quitters as current smokers.

For many health studies in which adjusting for smoking is important, this misclassification may be acceptable, especially as many of the benefits of smoking cessation take place in the long-term rather than in the short-term. We included a long timeframe to create the EMR Health Factors smoking variable based on most frequent observation, comparing it with cross-sectional report of smoking from surveys because limiting the Health Factors data to a shorter timeframe closer to the survey dates resulted in a large amount of missing Health Factors data. For this to be a meaningful validation, we chose to maximize available data. However, we do not necessarily recommend that all researchers use the most frequent observation as we did.

For example, for studies that involve assessing quit rates over time, researchers may wish to use the most recent rather than the most frequent Health Factors entry, which we demonstrate performs as well or better than the most frequent Health Factors entry when available. The choice of most frequent versus most recent observation should be based on what is most relevant to a particular research question. Despite these limitations, we found that agreement is nonetheless substantial between Health Factors data and self-reported smoking variables. Additionally, although there is variation in how the Health Factors smoking data are collected by sites, there is not substantial variation between agreement between sites.

Despite the potential misclassification, we believe it is important to describe and assess the three smoking categories (current, former, and never) as many analyses will benefit from using all three categories. We additionally provide data on Anacetrapib agreement between two categories of smokers (current vs. noncurrent and ever vs. never). With these results, researchers who use the Health Factors smoking data in the future can make a more informed decision on whether and how to create smoking groups based on what is relevant to their particular study.