Preliminary results of antibiotic prescribing errors in psychiatric setting: a prevention algorithm

Abstract Background Strengthening global surveillance for antimicrobial resistance (AMR) is critical. Our study focused on antibiotic prescribing errors (APE) in a psychiatric hospital, a possible cause for AMR. Data sets are essential, especially in negligent settings such as psychiatric hospitals. Methods An observational study was conducted at the psychiatric hospital St. Josef AMEOS, Oberhausen, Germany (Jan. 2023-2024) and approved by the ethics committee. The therapeutic protocols (TP) of all patients were collected. The frequency, location, responsible person (RP), type and reason of each APE were analyzed according to the EQUIP methodology. In addition, a clinical pharmacology specialist evaluated possible side effects and effects on the psychopathology of the patient using the FDA database drugs.com. Results Of 6805 TP, 130 included APE (51.5%male: 49.5%female, duration of antibiotic therapy: 5 ± 1.2 days, length of stay: 7.3 ± 2.4 days). 3 APE had serious side effects due to allergic reaction. 20 APE were isolated in the addiction clinic. RP were residents. 121 APE were dose-related, only 9 APE were due to writing failures. The frequency of APE according to substance was: amoxicillin (n = 42), amoxicillin/clavulanic acid (n = 31), cefuroxime (n = 28), cefpodoxime (n = 21), ciprofloxacin (n = 7), meropenem (n = 1). Pharmacological evaluation revealed an interaction between valproic acid and meropenem, and raised the adverse effect profile of ciprofloxacin administration. A drug specific algorithm was developed for the prevention of possible APE - AMR. Conclusions Although the incidence of APE in psychiatric setting is low, it remains an important issue of potential allergic reaction and AMR. Psychiatric settings need to evaluate their APE and take action on this public health issue. Key messages • Research concerning antibiotic prescribing errors is an important issue for psychiatric hospitals and has impact on public health and society. • Algorithms are important intervention to reduce antimicrobial resistance: