Determinants of pharmacists' interventions linked to prescription processing.
OBJECTIVE
The role of pharmacists in today's healthcare is changing rapidly. As they are close to the prescribing process, pharmacists are in the position to identify and adjust prescribing errors before dispensing. The objective of this study was to identify relevant determinants of interventions directly linked to prescription processing in community pharmacy.


METHODS
As part of a yearly continuing education programme, all community pharmacies in the region of 'Zealand' (N = 23) in the south-west of The Netherlands kept detailed records of all interventions directly linked to prescription processing during one week in May 1998. For every patient involved in an intervention, a control-patient was matched on pharmacy practice, date, gender and age.


RESULTS
A total of 39,357 prescriptions were evaluated by the 23 pharmacies during the one-week intervention programme. Out of these, one out of 10 resulted into an intervention. Being a first prescription in a new treatment episode was found to be a significant determinant (OR 1.75, 95 CI% 1.18-2.33). Variables reflecting drug therapy complexity (> 3 prescribers, > 15 prescriptions in 3 months before, > 3 different medications) showed all ORs higher than 1.00, but not significant. When looking at the individual drug categories, anti-infectives, respiratory drugs and cardiovascular medicines came out as important drug classes for intervention risk. We could not find any association between the number of signals per pharmacy and the number of interventions.


CONCLUSIONS
The 'whistle-blower' model of pharmacy based interventions is a valid one but needs a targeted and integral way of implemented thinking and use of information technology. In such an environment, interventions are a logical step of in-process quality control in the drug usage system.
Westein
M P
MP
Department of Pharmacoepidemiology and Pharmacotherapy, Utrecht Institute for Pharmaceutical Sciences (UIPS), PO Box 80 082, 3508 TB Utrecht, The Netherlands.
Herings
R M
RM
Leufkens
H G
HG
D000368:Aged; D016022:Case-Control Studies; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008508:Medication Errors / Q000706:statistics & numerical data; D009426:Netherlands; D016017:Odds Ratio; D010594:Pharmacies / Q000706:statistics & numerical data*; D010595:Pharmacists / Q000706:statistics & numerical data*