Antibiotics and return visits for respiratory illness: a comparison of pooled versus hierarchical statistical methods

Antibiotic prescribing for respiratory illness has been associated with small reductions in return visits in an analysis of a large practice-based network. In this study, we apply hierarchical analytical methods that account for the clustering of patients by practices to identify whether antibiotic prescribing by primary care physicians reduces subsequent visits for 6 acute respiratory illnesses-upper respiratory infection, pharyngitis, bronchitis, otitis media, sinusitis, and cough.

The study data came from 318 family physicians and internists in 45 practices in the Practice Partner Research Network from January 1995 through December 1996, with 255,564 active patients. Patients treated with antibiotics were compared with those who were not on the frequency of revisit within the next 14 days. A simple pooling model and 3 hierarchical statistical models (fixed-effects, random-effects, and Bayesian) were used to compare the odds-ratios for return visits.

Statistically significant results were found only for bronchitis and sinusitis by the hierarchical models, but the simple pooling model produced statistically significant results for all study conditions.

We conclude that antibiotics may reduce return visits for patients with bronchitis and sinusitis, but not for patients with other respiratory illness (upper respiratory infection, pharyngitis, otitis media, or cough). Studies of large clinical databases should use methods of analysis that account for the grouping of patients by practice to avoid false positive associations (type I errors.)