A NEW KNOWLEDGE STRUCTURE FOR DRUG-DRUG INTERACTIONS

We developed a program to automatically screen patients' medication pr ofiles for pairs of interacting drugs. Since some drug-drug interactio ns are indicated by changes in physiological parameters (e.g., ciprofl oxacin and theophylline leading to an elevation of theophylline levels ), the program considered the patients' relevant laboratory parameters prior to generating the alerts. We developed an editor to facilitate maintenance of the knowledge base. We evaluated the program for 3 week s in two satellite pharmacies. The program reported 160 alerts of whic h 5 resulted in a change in the patients' therapies (one per 500 patie nt-days of care). These five interactions were potentially very seriou s. An additional 3 alerts led to changes in medication administration times. Subjectively, the program is well received and continues to be in routine clinical use.