Background: The US Public Health Service task force on tobacco use and dependence developed an evidence-based treatment guideline for primary care (the “Five As” - Ask, Advise, Assess, Assist, Arrange). The Five As guidelines have been implemented by most primary care treatment organizations, including the six health systems in this project. Use of this guideline has been shown to substantially increase smoking-cessation rates in carefully managed research projects, however only a few assessments of implementation and effectiveness have been conducted in real-world clinical settings. Methods: Using the CER Hub, we specified operational definitions for each of the 5A’s enabling their identification in the EMR, including definitions unique to specific care settings (e.g., the names of local cessation programs). We refined an automated system, MediClass, with these definitions and used software tools on CER Hub to manually code samples of 500 test records at each site for comparison to performance by MediClass. We are using this automated data processor to assess smoking cessation care delivered to over 400,000 smokers across the six health systems during a 6-year study period. Results: Each site deployed the automated processor in their secure data environment and are generating and sharing a standardized limited dataset for analyses. The pooled dataset contains the relevant clinical events (including updates to tobacco use status as well as the Five A’s) to identify patients who smoke, those who stop smoking, and the smokers who received various types of treatment. Patients are classified as smokers if they are using tobacco at a visit, or if they were identified as a smoker at a previous visit with no change in tobacco use status noted since that visit. Smoking cessation services are being assessed for each primary care visit during the study period. Delivery of smoking cessation services will be summarized with respect to patient and provider characteristics and populations of interest, and quitting outcomes assessed. Conclusions: The CER Hub provides a common format for organizing data from multiple data systems and provides a practical and scalable method for identifying smoking counseling in the free text and coded data of electronic medical records.