Nature, frequency and determinants of prescription modifications in Dutch community pharmacies

Abstract

Aims: To examine the nature, frequency and determinants of prescription modifications in Dutch community pharmacies.

Methods: A prospective case-control study comparing modified prescriptions with nonmodified prescriptions was carried out in 141 Dutch community pharmacies. 2014 modified prescriptions (cases), collected in the selected pharmacies on a predetermined day in a specific period (25th February until 12th March 1999) and 2581 nonmodified prescriptions (controls) randomly selected on the same day were studied. The nature and frequency of prescription modifications and patient, drug and prescriber related determinants for a modified prescription were assessed.

Results: The overall incidence of prescription modifications was 4.3%, with a mean of 14.3 modifications per pharmacy per day. For prescription only medicines (POM) the incidence was 4.9%. The majority of POM modifications concerned a clarification (71.8%). In 22.2% a prescription could potentially have had clinical consequences when not altered; in more than half of the latter it concerned a dose error (13.7% of all cases). POM prescriptions of patients of 40-65 years had a significantly lower chance of modification compared with those of younger people (OR = 0.74 [0.64-0.86]). With respect to medication-class, we found a higher chance of POM modifications in the respiratory domain (OR = 1.48 [1.23-1.79]) and a decreased chance for nervous system POMs (OR = 0.71 [0.61-0.83]). With regard to prescriber-related determinants modifications were found three times more often in non printed prescriptions than in printed ones (OR = 3.30 [2.90-3.75]). Compared with prescriptions by the patient's own GP, prescriptions of specialists (OR = 1.82 [1.57-2.11]), other GP's (OR = 1.49 [1.02-2.17]) and other prescribers such as dentists and midwives (OR = 1.95 [1.06-3.57]) gave a higher probability of prescription modifications. When a GP had no on-line access to the computer of the pharmacy the chance of a modification was also higher (OR = 1.61 [1.33-1.94]). Multivariate analysis revealed that a nonprinted prescription was the strongest independent determinant of prescription modifications (OR = 3.32 [2.87-3.84]), remaining so after adjustment for GP computer link to the pharmacy and for type of prescriber.

Conclusions: At least 30% of Dutch community pharmacies corrected 2.8 POM prescriptions per pharmacy per working day, which could potentially have had clinical consequences if not altered. If the study sample is representative for The Netherlands, Dutch community pharmacies correct a total of approximately 4400 of these prescriptions per working day. Using computerized systems to generate prescriptions is an important strategy to reduce the incidence of prescription errors.