Using text and charts to provide social norm feedback to general practices with high overall and high broad-spectrum antibiotic prescribing: a series of national randomised controlled trials

Natalie Gold, Anna Sallis, Ayoub Saei, Rohan Arambepola, Robin Watson, Sarah Bowen, Matija Franklin, Tim Chadborn, Natalie Gold, Anna Sallis, Ayoub Saei, Rohan Arambepola, Robin Watson, Sarah Bowen, Matija Franklin, Tim Chadborn

Abstract

Background: Sending a social norms feedback letter to general practitioners who are high prescribers of antibiotics has been shown to reduce antibiotic prescribing. The 2017-9 Quality Premium for primary care in England sets a target for broad-spectrum prescribing, which should be at or below 10% of total antibiotic prescribing. We tested a social norm feedback letter that targeted broad-spectrum prescribing and the addition of a chart to a text-only letter that targeted overall prescribing.

Methods: We conducted three 2-armed randomised controlled trials, on different groups of practices: Trial A compared a broad-spectrum message and chart to the standard-practice overall prescribing letter (practices whose percentage of broad-spectrum prescribing was above 10% and who had relatively high overall prescribing). Trial C compared a broad-spectrum message and a chart to a no-letter control (practices whose percentage of broad-spectrum prescribing was above 10% and who had relatively moderate overall prescribing). Trial B compared an overall-prescribing message with a chart to the standard practice overall letter (practices whose percentage of broad-spectrum prescribing was below 10% but who had relatively high overall prescribing). Letters were posted to general practitioners, timed to be received on 1 November 2018. The primary outcomes were practices' percentage of broad-spectrum prescribing (trials A and C) and overall antibiotic prescribing (trial B) each month from November 2018 to April 2019 (all weighted by the number and characteristics of patients registered in the practice).

Results: We randomly assigned 1909 practices; 58 closed or merged during the trial, leaving 1851 practices: 385 in trial A, 674 in trial C, and 792 in trial B. AR(1) models showed that there were no statistically significant differences in our primary outcome measures: trial A β = - .199, p = .13; trial C β = .006, p = .95; trial B β = - .0021, p = .81. In all three trials, there were statistically significant time trends, showing that overall antibiotic prescribing and total broad-spectrum prescribing were decreasing.

Conclusion: Our broad-spectrum feedback letters had no effect on broad-spectrum prescribing; adding a bar chart to a text-only letter had no effect on overall antibiotic prescribing. Broad-spectrum and overall prescribing were both decreasing over time.

Trial registration: ClinicalTrials.gov NCT03862794. March 5, 2019.

Keywords: Antibiotics; Antimicrobial resistance; Behavioural intervention; Broad-spectrum prescribing; Data visualisation; Feedback; Messenger effect; Prescribing rates; Primary care; Social norms.

Conflict of interest statement

The authors declare that they have no competing interests.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Trial profile
Fig. 2
Fig. 2
Monthly trend of prescribing means over 6 months for broad-spectrum letter vs control letter trial
Fig. 3
Fig. 3
Monthly trend of prescribing mean over 6 months for broad-spectrum letter with chart vs no letter trial
Fig. 4
Fig. 4
Monthly trend of prescribing means over 6 months for overall letter with chart vs control letter trial

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Source: PubMed

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