The training and use of an artificial neural network to monitor use of medication in treatment of complex patients.

An artificial-neural-network-based drug interaction warning system was developed for use with a computerized real-time entry medical records system. The goal of the study was to provide physicians and nurses with timely warnings of potential drug interactions as therapies were prescribed. In a dialysis unit, physicians and clinical pharmacists defined rules of proper drug therapy, then trained a neural network with those rules. When the network was used to review the therapies of this patient population, a number of inconsistencies were discovered, and medication orders were changed on several patients. Real-time implementation of this monitoring system could provide messages to assure that drug therapy is consistent and proper, according to rules created by the providers of healthcare, thus preventing occasional mistakes in drug therapy.