Improving the accuracy of automated gout flare ascertainment using natural language processing of electronic health records and linked Medicare claims data.

Adding NLP concept variables to claims variables resulted in a small improvement in the identification of gout flares. Our data-driven claims-only model and our combined claims/NLP-concept model outperformed existing rule-based claims algorithms reliant on medication use, diagnosis, and procedure codes.