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Effectiveness of a multiple intervention to reduce antibiotic prescribing for respiratory tract symptoms in primary care: randomised control
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     1 University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, PO Box 85060, 3508 AB Utrecht, Netherlands

    Correspondence to: I. Welschen i.welschen@med.uu.nl

    Abstract

    In the Netherlands, general practitioners prescribe almost 80% of all antibiotics, and up to two thirds of these prescriptions are issued for infections of the respiratory tract.1 These infections are often treated with antibiotics, although this has mostly not been found to be beneficial.2-6 Unnecessary use of antibiotics entails an increased risk of side effects,2 high costs,7 medicalising effects,8 and development of bacterial resistance against antibiotics.9-11 Although antibiotic prescribing rates in the Netherlands are low compared with other European countries12 and the United States, as many as 50% of such prescriptions are estimated to lack an evidence based indication.13 Non-clinical factors such as perceived patients' expectations play an important part in the decision whether or not to prescribe antibiotics.14 15

    The Dutch College of General Practitioners developed evidence based guidelines for infections of the respiratory tract.16-19 However, implementation of these guidelines remains difficult.11 20 Educational outreach visits, local opinion leaders, and combinations of interventions have been shown to have the largest impact, but the results and methodological quality of these studies are highly variable.11 21 22 In general, multiple intervention strategies—including local doctors in setting guidelines, involving a leading participant from the peer review group, training doctors in communication skills (including patient centred healthcare strategies), monitoring prescribing behaviour, and sustaining the achieved consensus by means of feedback on prescribing and reminders—are considered most effective in optimising prescribing behaviour.21 23 However, such a strategy has not been evaluated for the management of respiratory tract infections in primary care. In a randomised controlled trial we evaluated the effectiveness of such a multiple intervention aiming at reducing antibiotic prescription rates for respiratory tract symptoms in primary care: the Utrecht antibiotics and respiratory tract infections (ARTI-1) study.

    Methods

    Forty two of the 48 peer review groups in the region of Utrecht were eligible and invited to participate. Twelve peer review groups (100 general practitioners) agreed to participate (figure). Insurance claims data showed no differences in volumes of antibiotics prescribed in participating compared with non-participating doctors. Out of 100 general practitioners who agreed to participate, 89 completed the study. Eleven were lost to follow up (intervention group 4/46; control group 7/54) because of retirement (one doctor), removal outside the region (three), illness (three), motivational problems (two) or technical problems (two). General practitioners in both arms did not differ at baseline with regard to sex, practice characteristics, and mean period since registration as general practitioner (table 1). They did not differ either regarding the extent to which the group was used to discuss indication and first choice medication in their meetings (table 1). Registered patients in both arms did not differ in 2000 and 2001 regarding age, sex, and type of diagnosis (table 2). Almost 80% (37) of the general practitioners (intervention group) attended all parts of the intervention.

    Flow of participants through the trial.

    Table 1 Baseline characteristics of general practitioners (n=89) participating in the study in 2000

    Table 2 Patients' characteristics in 2000 and 2001 in the intervention and control groups

    At baseline, mean antibiotic prescription rates for registered encounters for respiratory tract symptoms did not differ significantly between the two groups (27% v 29%, 95% confidence interval -9.1 to 5.0). In 2001, antibiotic prescription rates in the intervention group fell by 4% and those in the control group rose by 8% (mean difference in change -12%, -18.9% to -4.0%, table 3). Multilevel analysis confirmed the results of the unadjusted analysis (intervention effect -10.7%, -20.3% to -1.0%), while intra-class correlation coefficients showed that variation could be attributed to practice and group levels 0.17 and 0.09, respectively).

    Table 3 Registration of patients: changes in antibiotic prescription rates and patients' satisfaction in 2000 and 2001. Values are means with standard deviations unless otherwise indicated

    Patient satisfaction questionnaires were available from 83% (35) of general practitioners in the intervention group and from 91% (43) of doctors in the control group (table 2). We found no difference in patients' satisfaction in the two arms in 2000 and 2001 (table 3). The multiple intervention did not change patients' degree of satisfaction; they remained very satisfied with the consultation (mean satisfaction grade 4.2). These results were also confirmed by multilevel analysis (intervention effect on patients' satisfaction -0.03, -0.2 to 0.1).

    Claims data over 2000 and 2001 were in line with our results: no significant differences occurred in the number of antibiotic prescriptions between intervention and control group in 2000. In 2001, however, the mean number of antibiotic prescriptions had decreased by 9.7 prescriptions per 1000 patients (P = 0.05) in the intervention group, whereas in the control group it had increased (P = 0.60). This increase was also seen in the non-participating general practitioners in the same region (mean difference in change between intervention and control group -11.6 prescriptions/1000 patients, -23.2 to -0.03) and confirmed by multilevel analysis (table 4). After 15 months, the number of antibiotic prescriptions in the intervention group was still lower than in the pre-intervention period (data not shown). Referral rates (about 2%) remained stable over time and did not differ between intervention and control groups (mean difference in change -0.1, -2.0 to 1.8).

    Table 4 Insurance claims data: changes in mean number of antibiotic prescriptions per 1000 patients in March-April-May 2000 and March-April-May 2001 at practice level. Values are means with standard deviations

    Discussion

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