title: Determining the reasons for medication prescriptions in the EHR using knowledge and natural language processing.
abstract: Knowledge of medication indications is significant for automatic applications aimed at improving patient safety, such as computerized physician order entry and clinical decision support systems. The Electronic Health Record (EHR) contains pertinent information related to patient safety such as information related to appropriate prescribing. However, the reasons for medication prescriptions are usually not explicitly documented in the patient record. This paper describes a method that determines the reasons for medication uses based on information occurring in outpatient notes. The method utilizes drug-indication knowledge that we acquired, and natural language processing. Evaluation showed the method obtained a sensitivity of 62.8%, specificity of 93.9%, precision of 90% and F-measure of 73.9%. This pilot study demonstrated that linking external drug indication knowledge to the EHR for determining the reasons for medication use was promising, but also revealed some challenges. Future work will focus on increasing the accuracy and coverage of the indication knowledge and evaluating its performance using a much larger set of drugs frequently used in the outpatient population.
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY, USA.
authors.forename: Ying
authors.initials: Y
authors.lastname: Li
authors.forename: Hojjat
authors.initials: H
authors.lastname: Salmasian
authors.forename: Rave
authors.initials: R
authors.lastname: Harpaz
authors.forename: Herbert
authors.initials: H
authors.lastname: Chase
authors.forename: Carol
authors.initials: C
authors.lastname: Friedman
mesh_terms: D001185:Artificial Intelligence; D011307:Drug Prescriptions; D057286:Electronic Health Records; D006801:Humans; D051188:Knowledge Bases; D009323:Natural Language Processing; D061214:Patient Safety; D010865:Pilot Projects; D010818:Practice Patterns, Physicians'