Computerized pediatric oncology prescriptions review by pharmacist: A descriptive analysis and associated risk factors. Issue 4 (18th December 2017)

• Record Type: Journal Article
• Authors: Hamel, Claire; Tortolano, Lionel; Bermudez, Elisabeth; Desmaris, Romain; Klein, Sébastien; Slimano, Florian; Lemare, François
• Is Part Of: Pediatric blood & cancer. Volume 65:Issue 4(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-12-18
• Subjects: clinical pharmacy -- medical order entry systems -- pediatric oncology -- pharmacist interventions -- prescribing errors; Tumors in children -- Periodicals; Blood -- Diseases -- Periodicals; Cancer in children -- Periodicals; 618.92
• DOI: 10.1002/pbc.26897
• Languages: English
• ISSNs: 1545-5009

Abstract

Abstract: Background: Systematic prescription analyses by clinical pharmacists result in pharmacist interventions (PIs) to reduce prescription errors and improve medication safety. PIs are particularly critical in oncology, because antineoplastic drugs are highly toxic with low therapeutic indexes especially in a pediatric population. The aim of this study is to describe PIs in a pediatric oncology department and to identify potential risk factors associated with prescription errors. Procedure: We conducted a 20‐month observational study in a pediatric oncology department concerning electronic prescription of injectable chemotherapies was conducted. PIs were analyzed for drug‐related problems (DRPs), type of intervention, population characteristics, involved drugs, and the potential risk factors. Results: Clinical pharmacists made 90 PIs for 10, 214 antineoplastic prescriptions for a rate of 88 PIs per 10, 000 prescriptions. The majority of DRPs were dosage errors (61.8%), imputable to measurements (weight and/or height) in 47.4% or unreported dose reduction. The most common patient ages were in the range 1‐10 years and the most common time for medical double checks was 2‐9 pm. There were statistically more prescription errors in standardized protocols ( P < 0.001). Conclusions: Not surprisingly, PIs were predominantly to correct dose errors, half of which related to height and weight measurements that were not updated. No significant risk factors for errors were identified for errors except in the standardized status of prescription, which appears to be linked in part to our software that did not automatically reflect dose reduction from one course to the next. Medical double‐checking followed by a clinical pharmacist's double check were effective in order to prevent prescription errors.