Do Fair Comparisons or Harms Data Increase Responsiveness to Feedback About Antibiotic Prescribing: 2x2 Factorial Trial

Overview

Antibiotic overuse is common and antibiotic prescribing contributes to rising rates of antimicrobial resistance. Primary care physicians prescribe the majority of all antibiotics and there is large inter-physician variability in prescribing that cannot be explained by differences in patient populations. Peer comparison audit and feedback (A\&F) can act as an effective behavioural intervention to reduce unnecessary antibiotic use. The range of effects seen in prior A\&F trials could be attributed, at least in part, to differences in the way the feedback interventions were designed. In fall 2018, the investigators conducted an audit and feedback trial of mailed letters to 3500 family physicians in Ontario who prescribe the highest volume of antibiotics \[NCT03776383\]. While effective, family physicians questioned the credibility of the report in terms of its ability to fairly account for their practice size and population. In Ontario, A\&F is routinely offered to primary care providers from a variety of sources. Ontario Health - an agency created by the Government of Ontario - provides A\&F via email to physicians who voluntarily sign up for their "MyPractice" reports. These are multi-topic reports with aggregated (physician-level) data. As of November 2021, the MyPractice reports for family physicians will include data on antibiotic prescribing. To date, less than half of Ontario family physicians have signed up for the MyPractice reports from Ontario Health. For this study, the investigators will conduct a trial to investigate the effect of A\&F in family physicians not already receiving A\&F through a MyPractice: Primary Care report. Physicians who do not already receive antibiotic prescribing feedback through a MyPractice report will receive personalized antibiotic prescribing feedback through a letter mailed out from PHO. This large-scale evaluation provides an opportunity to evaluate not only whether A\&F using such data is helpful in the post-covid context, but how best to design the A\&F intervention and to explore why we observed (or not) changes in antibiotic prescribing.

This study will examine ways to optimize the effects of A\&F for antibiotic prescribing in primary care. This study will aim to answer the following questions: 1. Do patients of family physicians receiving A\&F about antibiotic prescribing receive fewer antibiotics compared to patients of family physicians that do not receive A\&F? 2. Does the effects of A\&F vary with the following design features? i) case-mix adjusted (or simple) peer comparators to represent a target for the prescribing quality indicators ii) emphasis (or not) on antibiotic-associated harms in addition to messages that focus on lack of benefit This trial will include family physicians who did not opt-in to receive MyPractice: Primary Care report from Ontario Health. Physicians will be randomized to the control group or intervention group. Physicians in the intervention group will receive a personalized antibiotic prescribing feedback letter that will include personalized data regarding total antibiotic prescribing per 1000 patient visits and proportion of antibiotic prescriptions provided for a duration of \>7 days. The letter will also contain two experimental factors: 1: Simple vs complex peer comparators; and 2) Emphasis or not on antibiotic harms. For the complex (adjusted) comparator, recipients will be compared only to top-performing 'like-peers' - the group of physicians with similar complexity and numbers of patients. For the harms vs no harms factor, physicians will be either provided with information that focuses on lack of benefit for certain conditions (no harms), or with information that emphasizes the potential harms caused by unnecessary use of antibiotics. The feedback letters will be mailed to each physicians' primary practice address, along with a viral prescription pad developed by Choosing Wisely Canada. One month after the initial intervention, intervention participants will be invited to complete a process evaluation survey to determine why or why not the intervention worked and how individual factors can affect physician motivation, willingness, and ability to engage in new practices. Intervention participants will also be invited to take part in a process evaluation interview.