Systematic Review and Development of Recommended Code Lists to Identify Smoking and Vaping Status in Electronic Health Records (EHR)

Vaping and smoking are important health behaviours associated with many diseases. Evaluating the association of smoking and vaping with diseases using electronic health record (EHR) data requires accurate codelists to determine smoking and vaping status. However, codelists used in studies are not always published or consistent between studies. It is important to develop standard codelists for use in future studies, and transparency is required to ensure consistency and standardization. To provide an overview of the codes used in both peer-reviewed scientific literature and codelist repositories to identify smoking and vaping status in EHRs and derive a recommended codelist for use in EHRs to identify smoking and vaping status. Publications (MEDLINE, Embase, and Scopus) and codelist repositories (LSHTM Data Compass, OpenCodelists, and the HDR UK Phenotype Library) were searched from January 2010 to April 2024. All publications or codelist repositories with codes referring to smoking/vaping status were included in this review (search terms are further addressed in Supplementary Table 1). All codes were extracted to review the frequency and consistency between studies. There were 100 codelists across different coding systems: 55 codelists from publications and 45 codelists from codelist repository entries. For vaping status, there were 23 codelists identified, 7 from publications, and 16 from codelist repositories. Only 10% of publications included codelists. A limited number of ICD codes were used, and more were reported using the Read or SNOMED CT codes. The codelists we subsequently developed were based on those found in the review. Very few studies have reported the use of codelists despite smoking status being a widely used variable in many publications, and vaping status is increasing. Using the information from the review, we derived codelists for smoking and vaping using a transparent methodology that can be used in future studies.