These findings indicate that useful phenotypes for complex behaviors like alcohol use can be obtained using longitudinal EHR data, but the quality of the phenotype may depend upon the length of the observation period and the statistical approach used to calculate the metric. Our sample had an average of 7 AUDIT-C measurements collected over an average of more than 6 years. While our sample size did not allow us to explore the extent to which the more robust associations with PEth and ADH1B seen with the trajectories depended upon the number of observations or the time interval covered, we were able to demonstrate the superiority of trajectories over both single measure metrics. Of note, while the majority of healthcare systems have adopted EHRs and many use the AUDIT-C to screen for harmful drinking, the VAHS is one of the few healthcare systems that currently have longitudinal data spanning more than 6 years.
