Your English writing platform
Discover LudwigExact(15)
Dispensing errors were subdivided into content errors and labelling errors, with EPSR2-specific labelling errors a further subcategory of labelling error.
An EPSR2-specific labelling error was any labelling error caused specifically by the different functionality of the EPSR2 system, when compared with a non-EPSR2 prescription.
We assumed a baseline labelling error rate of 1.6%, 2 and anticipated a minimum 50% relative reduction in the mean labelling error rate in the EPS2 pharmacies.
However, according to figure 2, a labelling error alone was recorded.
Types of labelling error are shown in table 1; these most commonly involved dose instructions and additional warning labels.
We assumed that this discrepancy was due to mismatching of specimens (i.e. comparing specimens from different patients) due to a labelling error.
Similar(45)
Categorisation of MAEs was based on established definitions, 4 9 11 18 with labelling errors considered as 'wrong preparation errors'.
Prevalence of labelling errors, content errors and labelling enhancements (beneficial additions to the instructions), as identified by researchers visiting each pharmacy.
This analysis indicated a statistically significant 46% increase (CI 21%to7676%) in labelling errors for EPSR2 items compared to non-EPSR2.
Nine further tests, which were excluded because of specimen labelling errors or inadequate personal identifying information were not analyzed.
The higher prevalence of labelling errors associated with EPSR2 prescriptions was due to errors of two subcategories: dose instructions and additional warning labels (table 1).
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com