Use of natural language programming to extract medication from unstructured electronic medical records.

The purpose of this study is to evaluate the feasibility of applying natural language processing in the automated extraction of medications information from unstructured electronic records. Sixty-two documents containing medications were subjected to both manual and automated extraction. Both were able to identify over 90% medications. The automated method identified more medications than manual review, 97% vs 92%. However, the automated extraction included a substantial percentage (17%) of non-medication items but none with manual review.