[Drug-drug interactions in multicentre polypathological polymedicated patients]

Abstract

Objective: To determine the prevalence of relevant drug-drug interactions (DDIs) and associated predictor factors in a sample of patients with multiple complex chronic diseases (polypathological patients) receiving multiple drug therapy. Our secondary objective was to determine the acceptance of a drug interaction reporting program with recommendations addressed to the prescribing physicians.

Subjects and methods: A cross-sectional study performed in three primary care centres assigned to a teaching hospital. All patients with 2 or more chronic diseases and treated simultaneously with 5 or more drugs were recruited in the study. DDIs were detected by using Drug-Reax System((R)) (Micromedex) program, the Drug Data Base (Bot) Spanish General Council of Official Colleges of Pharmacists or literature search when needed. Those DDIs which, according to the opinion of the pharmacist investigators, required any intervention were considered relevant. Acceptance of the reported DDI recommendations was evaluated by means of a survey addressed by primary care physicians ("acceptable," pertinent recommendation to modify treatment).

Results: A total of 283 polypathological polymedicated patients were included. Mean age was 74.5 years (range 43-100 years). Mean number of diseases per patient was 2.5 and prescriptions 9.7). Out of a total of 2748 drug prescriptions, 1053 DDIs in 250 patients (96.5%) were identified. Of these, 45% were filtered as relevant DDIs. The presence of ischemic heart disease, two or more hospital admissions and having received 7 or more prescriptions were associated with the presence of DDIs. 177 informs containing 473 recommendations about DDIs were sent to primary care physicians from our Pharmacy Department. 339 recommendations were answered by primary care physicians, and 84% were favourably accepted.

Conclusions: Almost every polypathological polymedicated patient is exposed to at least one DDI and about a 60% would require any intervention. Appropriate filtering and personalising recommendations in a collaborative way may represent an adequate manner to improve the risk-benefit ratio of the drug prescriptions.