Impact of pharmacist interventions on medication errors in hospitalized pediatric patients: a systematic review and meta-analysis.
Lina Mohammad NaseralallahTarteel Ali HussainMyriam JaamShane Ashley PawlukPublished in: International journal of clinical pharmacy (2020)
Background Medication errors are avoidable events that may occur at any stage of the medication use process. Implementing a clinical pharmacist is one strategy that is believed to reduce the number of medication errors. Pediatric patients, who are more vulnerable to medication errors due to several contributing factors, may benefit from the interventions of a pharmacist. Aim of the review To qualitatively and quantitatively evaluate the impact of clinical pharmacist interventions on medication error rates for hospitalized pediatric patients. Methods PubMed, EMBASE, Cochrane Controlled Trials Register and Google Scholar search engines were searched from database inception to February 2020. Study selection, data extraction and quality assessment was conducted by two independent reviewers. Observational and interventional studies were included. Data extraction was done manually and the Crowe Critical Appraisal Tool was used to critically appraise eligible articles. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using a random-effects model for rates of medication errors. Results 19 studies were systematically reviewed and 6 studies (29,291 patients) were included in the meta-analysis. Pharmacist interventions involved delivering educational sessions, reviewing prescriptions, attending rounds and implementing a unit-based clinical pharmacist. The systematic review indicated that the most common trigger for pharmacist interventions was inappropriate dosing. Pharmacist involvement was associated with significant reductions in the overall rate of medication errors occurrence (OR 0.27; 95% CI 0.15 to 0.49). Conclusion Pharmacist interventions are effective for reducing medication error rates in hospitalized pediatric patients.
Keyphrases
- adverse drug
- systematic review
- electronic health record
- physical activity
- healthcare
- patient safety
- meta analyses
- emergency department
- risk assessment
- ejection fraction
- newly diagnosed
- end stage renal disease
- chronic kidney disease
- case control
- drug induced
- machine learning
- big data
- patient reported outcomes
- artificial intelligence