A review of techniques used to reduce medication errors in pediatrics. Within the limitations of the heterogeneous system that makes up information technology for child health, the authors conclude that CPOE and accompanying decision support can help but also creates new types of error (World Journal of Pediatrics).
Ruano 2015 (Link) | PubMed 26684316 | Author SearchDescribes an effort to reduce alert rates from drug-drug interactions, with some evidence that fewer alerts led to increased salience (lower override rates). Rates for pharmacists fell from 58.74 alerts per 100 orders to 25/100 orders. For providers, the drop in rates was less dramatic (~20 to 15/100 orders) but they were getting far fewer alerts in the first place. Pharmacists’ rate of alert overrides fell, but providers’ rates stayed the same. The basic methodology used was a visualization tool developed in a commercially available data-visualization application.
Simpao 2015 (JAMIA) | PubMed 25318641 | Author SearchCompared rates of errors between handwritten and computerized orders in a pediatric intensive are unit. CPOE resulted in errors (of omission in 22% of cases), but at a far lower rate than in handwritten orders (66%). Drug dosing error rates were similar for both methods (21%) and largely involved under-dosing. (Intensive Care Medicine)
Maat 2014 (Link) | PubMed 24352486 | Author SearchDescribes development (via delphi methods) of a tool intended to detect inappropriate or missing pediatric prescriptions. Takes the technique as far as content validation, but not reliability. (PLOS One, June 2014)
Prot-Labarthe 2014 (Link) | PubMed 24978045 | Author SearchStudy from the Netherlands showing that pharmacists in a children’s hospital had to correct 1577 (1.1%) of 138449 prescriptions. The biggest category of corrections concerned wrong doses (45%). It is worth noting that the electronic system used to create the prescriptions did not actually provide dosing decision support.
Maat 2013 (Arch Dis Child) | PubMed 23184352 | Author Search