Details on the validation and psychometric properties of this phenotype are reported in our recent publication23. In brief, we used manual chart review (n = 500) as the gold standard. For both the algorithm and chart review, three classifications were possible: likely PTSD, possible PTSD, or no PTSD. We used Lasso regression with cross-validation first to select statistically significant predictors of PTSD from the electronic health record (EHR) and then to generate a predicted probability score of being a PTSD case for every participant in the study population. Probability scores ranged from 0–1.00. Comparing the performance of our probabilistic approach (Lasso algorithm) to a rule-based approach (ICD algorithm), the Lasso algorithm showed modestly higher overall percent agreement with chart review compared to the ICD algorithm (80% vs. 75%), higher sensitivity (0.95 vs. 0.84), and higher overall accuracy (AUC = 0.95 vs. 0.90). For purposes of the case-control binary EHR-derived phenotype used here, we applied a 0.7 probability cut point to the Lasso results to determine final PTSD case and control status; we also selected a threshold score of 30 on
