Objectives Prescribing errors can lead to inconvenience, morbidity and mortality. It is therefore crucial to educate doctors to prescribe safely, efficiently and effectively. To create an effective educational programme, it is essential to understand which errors are made and by whom. The aim of this study is to explore if the experience level of the doctor influences how many and which prescribing errors are made in a European academic teaching hospital, where a computerised physician order entry system (CPOE) with a clinical decision support system (CDSS) is exclusively used.
Methods Prescriptions for all inpatients in an academic teaching hospital were collected in June 2021. All prescriptions with an alert generated by the CDSS which could not be handled by a pharmacy technician according to local protocol were checked for errors. Identified errors were categorised by type and severity.
Results A total of 130 538 prescriptions were newly made or altered by doctors. Of these prescriptions, 1914 (1.5%) were retained for a check by the pharmacist. These contained 430 prescribing errors (0.3% of total prescriptions). Doctors not in specialty training and those in specialty training made more prescribing errors than consultants (0.5% and 0.5% vs 0.1%; p<0.001). Doctors in specialty training made relatively more drug–drug interaction errors than consultants (n=31 (16%) vs n=3 (3%), p<0.05). No significant difference was found regarding the severity of the errors.
Conclusions Doctors not in specialty training and doctors in specialty training, who are the less experienced doctors, make more prescribing errors than consultants, even with the use of a CPOE combined with CDSS. The type of errors differ between doctors of different experience levels. This finding provides a solid basis for specific additional education to medical students, doctors not in specialty training and doctors in specialty training.
- Education, Pharmacy, Continuing
- EDUCATION, PHARMACY
- Education Department, Hospital
- MEDICAL ERRORS
Data availability statement
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
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