Assessment of Possible Drug-Drug Interactions in Psychopharmacotherapy after Hospital Discharge using an Interactive Database

Introduction: Psychiatry is confronted with increasing requirements in quality management, guidelines and an increasing proportion of elderly, chronic multimorbid patients with psychiatric disorders. The latter give rise to polypharmacy which may lead to drug-drug interactions. Assessment of drug interactions is more and more difficult as the total number of drugs taken increases. In the present study hospital discharge medication was analysed semiautomatically for possible drug-drug interactions. Methods: In-hospital cases were randomly selected. Discharge medication was analysed using PsiacOnline, a large web-based database for drug interactions. Results: The selection yielded 342 cases from 213 patients (mean age 46.3 years, 53% females). 86 patients had one psychiatric diagnosis; the other patients had at least two or more diagnoses. The discharge prescription was analysed for 55 different psychotropic drugs from 4 large drug groups (18 antidepressants; 17 antipsychotic drugs; 5 mood stabilisers/epileptic drugs and 13 different hypnotic/anxiolytic drugs). Antipsychotic drugs were the most frequent drugs (n = 334); followed by antidepressants (n = 312) and mood stabilizers (n = 112). 47 patients (13.7%) were discharged with monotherapy. Mean drug number was 2.7. PsiacOnline revealed 535 hits: 126 (23.6%) combinations were non-critical, 86 (16.1%) combinations were critical based on pharmacological properties of the drugs; 232 (43.4%) combinations were critical according to in vitro studies or animal experiments; critical drug combinations in high-risk patients: 67 x (12.5%); combinations with reported risks for side effects due to interaction: 17 x (3.2%) and combinations with documented risks for severe drug interactions: 7 x (1.3%). Conclusion: Although the majority of drug combinations was considered not critical, approximately 3% of cases had an increased risk for adverse drug actions and a further 1.3% cases with a severe risk gave evidence that integration of an IT-based pharmacological expert system in a computerised physician order entry (CPOE) should be considered. Suggested beneficial effects need to be shown by an appropriately-designed clinical study.