HTL: Modelo para la extracción, estructuración y visualización de eventos médicos a partir de texto narrativo en historias clínicas electrónicas

摘要

Electronic medical records contain important information of patients, which can serve as input to perform a retrospective analysis in the diagnosis, follow-up and treatment of a disease. This information is recorded in a narrative form with the resulting limitation to identify medical events (such as medical appointments, drug prescriptions, treatments, surgical procedures, etc.). As it is difficult to identify medical events in medical records, it is not clear how to compare this electronic information with the treatment guidelines. Such guidelines correspond to recommendations developed systematically to assist health professionals in making appropriate decisions regarding a disease. This article presents Health Text Line Model HTL, for the extraction, structuring and visualization of medical events from narrative text in electronic medical records. The HTL model was implemented in a framework that integrates the aforementioned processes in order to identify and schedule medical events to compare them with established treatment guidelines for a specific set of diseases.