While predictive algorithms based on claims data are useful, additional precision can be gained by incorporating clinical data from the unstructured text of electronic health records (EHR). Rutgers’ Robert Wood Johnson Barnabas Health System (RWJBH), GSK, and Deep 6 AI conducted a study to develop an algorithm to identify COPD exacerbations via EHR data. The algorithm used artificial intelligence (AI) and natural language processing (NLP) to mine EHR data for clinical characteristics of patients with exacerbation that are not available in traditional claims data or coded EHR data. Algorithm build in Deep 6 AI softwareUsing an iterative process, initial data pulls were reviewed and the algorithm was refined to remove non-COPD cases. Learn more about how Deep 6 AI’s platform works to mine structured and unstructured EHR data to precisely match patients to trials.