Evaluation of the clinical value of pharmacists' modifications of prescription errors

Abstract

Aims: Our objective was to examine the clinical value of pharmacists' interventions to correct prescription errors.

Methods: In this study, we reviewed a random sample of prescriptions that had been modified in pharmacies. These prescriptions were collected on one predetermined day between 25th February and 12th March 1999 from 141 Dutch community pharmacies. Each prescription modification was evaluated by a panel of reviewers, including representatives of five groups of health care professionals. After generally rating each modification as positive, negative, or neutral, the reviewers assessed its outcome (in terms of prevention of an adverse drug reaction [ADR], an improvement in effectiveness, both, or other), the probability and importance of improvements in effectiveness and/or the probability and seriousness of an ADR in the case of a nonintervention. Our analyses included 144 interventions from the first general assessment and a selection of 90 consistently rated 'positive' interventions (from all assessments).

Results: On average, one in 200 prescriptions (0.49%) was found to have been positively modified by Dutch community pharmacists. About half of these interventions (49.8%) were aimed at preventing ADRs; 29.2% were rated as a positive modification in the effectiveness of pharmacotherapy and 8.6% affected both effectiveness and ADR. Reviewers' ratings varied widely between different categories of drug-related problems (DRPs). The impact of individual interventions (n = 83) varied, and for 53% of these interventions it was estimated to be relatively high.

Conclusions: Pharmacists' interventions led to modification of prescriptions for an array of DRPs. Such interventions can contribute positively to the quality of pharmacotherapy. By extrapolating our data, we estimated a daily occurrence of approximately 2700 positive interventions in all Dutch pharmacies (1.6 per pharmacy per day). Reviewers rated the impact of interventions on a patient's health as significant in a substantial number of cases.

Figure 1

Algorithm representing the flow of questions for rating interventions

Figure 2

Study selection procedures

Figure 3

The average estimated impact of 83 interventions. Contra indication (n = 17) (⋄), double medication (n = 11) (), duration of use (n = 3) (), interaction (n = 9) (♦), wrong medicine (n = 13) (), dosing (n = 27) (▿), medicine obsolete (n = 3) (○)