Evaluating the impact of an indication-based, patient-specific prescribing tool on prescribing errors in paediatrics: a non-randomised, before-and-after study

BACKGROUND: Medication errors remain a major challenge in paediatric prescribing owing to the complexities of weight-based dosing, age-specific formulations and the need for precise calculations. This study examines the association of an indication-based, patient-specific prescribing tool with prescribing errors in paediatric emergency and inpatient settings. METHODS: A non-randomised, before-and-after study was conducted at a London tertiary teaching hospital. Prescribing errors were assessed before and after implementing the intervention in the paediatric emergency department (PED) and a general paediatric ward. Errors were identified through manual review of medication orders against predefined criteria based on the British National Formulary for Children and local prescribing guidelines. Dose errors were defined as deviations of ±10% from recommended ranges, with deviations ≥25% categorised as major. Statistical analysis included descriptive comparisons, logistic regression and intention to treat analysis to assess the effect associated with the intervention. RESULTS: A total of 1808 medication orders were reviewed, including 1567 standard practice orders and 241 intervention-supported orders. When the intervention was used, the overall prescribing error rate was 1.2%, compared with 7.14% in the control orders, representing an 83% reduction in the odds of error (OR 0.17). In the general paediatric ward, errors reduced from 9.1% to 1.1% (OR 0.11), while in PED, error rates declined from 4.9% to 1.4% (OR 0.27). Errors that occurred when using the intervention were attributed to prescriber deviation from system recommendations rather than inaccuracies within the tool itself. CONCLUSIONS: These findings suggest that use of the intervention is associated with significantly lower odds of a prescribing error occurring in paediatric settings. Future work should focus on optimising prescriber adherence, enhancing system integration into clinical workflows and exploring economic and user-experience outcomes to maximise impact.