Effect on Antibiotic Prescribing of Repeated Clinical Prompts to Use a Sore Throat Score

Patients assessed included 692 children and adults. Of these, 71 (10.3%) were excluded because of a diagnosis of bronchitis (35), sinusitis (16), otitis media (11), or pneumonia (4) or because the patient was less than 3 years old (5). The score approach did not apply to the 4 conditions of exclusion because they involve organisms other than GAS. The remaining 621 patients in the control and intervention groups were similar in demographic and clinical characteristics as well as regarding the prevalence of GAS as documented by throat culture (Table 1). However, a diagnosis of tonsillitis, strep throat, or pharyngitis was more likely to occur in the intervention group (38.6%) than in the control group (28.9%, P = .01). These diagnoses were associated with a higher rate of antibiotic prescribing (54.8%) than were situations in which physicians recorded a URTI or other diagnosis (14.2%, P < .001).

Differences were noted in the characteristics of the treating physicians in each group when considered by patient encounter. Although there were no differences in the age or sex of individual physicians in each group, the participating physicians did not contribute equal numbers of patient encounters. The average number of patients assessed per physician was 3, ranging from a low of 1 patient contributed by some physicians to a high of 8 for others. More patient encounters in the intervention group were contributed by male physicians who had been in practice longer, who worked in smaller communities, and who reported larger practice volumes (Table 1). Physicians from small communities were more likely to diagnose strep throat, tonsillitis, or pharyngitis than were those in larger communities (45.1% vs 28.1%, respectively, P < .001), as were those with higher patient volumes (46.5% vs 30.2%, P = .003).

Certain physician practice characteristics were associated with a patient’s being more likely to receive a prescription for an unnecessary antibiotic (Table 2). For example, physicians were more likely to prescribe unnecessary antibiotics if they saw more than 150 patients per week than if they saw fewer and if they had been in practice for 20 or more years than if they had practiced for a shorter time. In addition, higher overall antibiotic use was associated with higher patient volume and with practicing in a smaller community.

There were no differences between the intervention and control groups in either unnecessary antibiotic prescriptions (20.4% vs 16.1%, respectively, P = .17) or overall antibiotic use (28.1% vs 27.9%, P = .96) (Table 1). However, while the culture reports that were needed to classify prescriptions as unnecessary were available for most (600) patients (96.6%), significantly more culture reports were missing in the control group (5.4%) than in the intervention group (1.2%, P = .007). Antibiotics were prescribed in 59% of the 17 cases with missing culture reports in the control group but for none of the 4 cases with missing culture reports in the intervention group.

Because intervention patients were more likely than controls to have been treated by physicians with higher prescribing characteristics, adjustments were made for the differing physician characteristics and diagnostic practices and for the clustering of patients by physician, using multiple logistic regression (Table 3). After adjustment, the intervention was associated with a nonsignificant reduction in unnecessary antibiotic prescriptions (odds ratio [OR] = 0.76, 95% confidence interval [CI] = 0.42, 1.40) and in overall antibiotic use (OR = 0.57, 95% CI = 0.27, 1.17).

TABLE 1
COMPARISON OF PATIENTS IN CONTROL AND INTERVENTION GROUPS

TABLE 2
ASSOCIATION BETWEEN INDIVIDUAL PHYSICIAN FACTORS* AND ANTIBIOTIC PRESCRIBING, ADJUSTING FOR THE CLUSTERING OF PATIENTS BY PHYSICIAN