The authors of the following study use machine learning and Natural Language Processing (NLP) algorithms to accurately evaluate a clinical decision support rule through an electronic medical records system, and compare it against manual evaluation. Results show that the program could eliminate almost 99.92 percent of manual medical record review with a high level of accuracy while maintaining a low false positive rate and moderate false negative rate.