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Review 2: "Antibiotic Prescribing in Remote Versus Face-to-Face Consultations for Acute Respiratory Infections in English Primary Care: An Observational Study Using TMLE"

Overall, reviewers felt like this preprint was reliable with some reservations related to the appropriateness of the method or interpretation of the findings.

Published onJun 10, 2023
Review 2: "Antibiotic Prescribing in Remote Versus Face-to-Face Consultations for Acute Respiratory Infections in English Primary Care: An Observational Study Using TMLE"
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key-enterThis Pub is a Review of
Antibiotic prescribing in remote versus face-to-face consultations for acute respiratory infections in English primary care: An observational study using TMLE
Antibiotic prescribing in remote versus face-to-face consultations for acute respiratory infections in English primary care: An observational study using TMLE

Abstract Background The COVID-19 pandemic has led to an ongoing increase in the use of remote consultations in general practice in England. Though the evidence is limited, there are concerns that the increase in remote consultations could lead to more antibiotic prescribing.Methods We used patient-level primary care data from the Clinical Practice Research Datalink to estimate the association between consultation mode (remote vs face-to-face) and antibiotic prescribing in England for acute respiratory infections (ARI) between April 2021 – March 2022. We used targeted maximum likelihood estimation, a causal machine learning method with adjustment for patient-, clinician- and practice-level factors.Findings There were 45,997 ARI consultations (34,555 unique patients), of which 28,127 were remote and 17,870 face-to-face. For children, 48% of consultations were remote whereas for adults 66% were remote. For children, 42% of remote and 43% face-to-face consultations led to an antibiotic prescription; the equivalent in adults was 52% of remote and 42% face-to-face. Adults with a remote consultation had 23% (Odds Ratio (OR) 1.23 95% Confidence Interval (CI): 1.18-1.29) higher chance of being prescribed antibiotics compared to if they had been seen face-to-face. We found no significant association between consultation mode and antibiotic prescribing in children (OR 1·04 95% CI 0·98-1·11).Interpretation This study uses rich patient-level data and robust statistical methods and represents an important contribution to the evidence base on antibiotic prescribing in post-COVID primary care. The higher rates of antibiotic prescribing in remote consultations for adults are cause for concern. We see no significant difference in antibiotic prescribing between consultation mode for children. These findings should inform antimicrobial stewardship activities for health care professionals and policy makers. Future research should examine differences in guideline-compliance between remote and face-to-face consultations to understand the factors driving antibiotic prescribing in different consultation modes.Funding No external funding.Research in context Evidence before this study Use of remote consultations in general practice has increased rapidly since the onset of the COVID-19 pandemic. Concerns have been raised that antibiotic prescribing rates may be higher in remote compared with face-to-face consultations. Acute respiratory infection (ARI) is the most common reason for an antibiotic prescription in adults making it one of the most important areas of prescription practice for antibiotic use. Empirical studies investigating the differences in antibiotic prescribing rates between online and remote consultations have produced mixed findings, in general and for ARIs specifically. Recent review-type articles on the topic - including a 2020 qualitative systematic review and a 2021 meta-analytic systematic review – have reported mixed results when comparing online and face-to-face consultations with some showing higher and others lower antibiotic prescribing in remote consultations. Furthermore, many of the studies that were included in the reviews were at risk of bias due to a failure to control for demographic and clinical differences between patients in remote versus face-to-face consultations.Added value of this study This is the first England wide study estimating the difference in antibiotic prescribing between consultations modes in the post-covid setting where remote consultations are as common as face-to-face consultations. It is also the first study in this setting to apply TMLE – doubly robust causal machine learning method. We found that an adult was 23% more likely to be prescribed an antibiotic for an ARI in a remote compared with a face-to-face consultation with a general practitioner in England. There was no evidence for a difference in children. Our findings are based on an analysis of a representative sample of almost 46,000 GP consultations for ARIs in general practice in England and controls for patient-, clinician- and practice-level factors that are associated with both consultation mode and with antibiotic prescribing. As such, our findings are at a smaller risk of bias from unobserved confounding than the previous research examining this issue and therefore represent an important contribution to the evidence base.Implications of the available evidence Taken together with the existing body of evidence on this topic, our results showing higher prescribing in remote consultations are cause for concern. The factors affecting antibiotic prescribing and the interaction with consultation mode are complex and will require further research to unpick. The existing evidence including this study have largely focused on prescribing rates, and do not investigate the appropriateness of antibiotics prescribing in remote compared to face-to-face consultations. Further investigation is required to explain the discrepancy between consultation modes. The growing body of evidence in this area has relevance for future antimicrobial stewardship activities and should be used to inform the ongoing development of antibiotic prescribing guidelines for remote consultations.

RR:C19 Evidence Scale rating by reviewer:

  • Strong. The main study claims are very well-justified by the data and analytic methods used. There is little room for doubt that the study produced has very similar results and conclusions as compared with the hypothetical ideal study. The study’s main claims should be considered conclusive and actionable without reservation.



In this manuscript, the authors wish to examine the relationship between in-person (versus remote) consultations and the likelihood of antibiotic prescription in England. The authors adequately set up the problem by noting that remote consultations have increased since the COVID-19 pandemic, and evidence is limited/mixed about the impact of this shift on antibiotic prescribing, especially for those who have acute respiratory infections (ARIs). The authors found that, for adults, having an ARI remote visit was more likely to yield an antibiotic prescription compared to a face-to-face visit. The authors used robust and efficient statistical methods (e.g., targeted maximum likelihood estimation [TMLE] jointly with SuperLearner) to look at this relationship. While this methodology is appropriate to answer the primary question given the observational nature of the data, one major point the authors must address is the interpretation of their point estimates. Specifically, sometimes the authors used a causal odds ratio interpretation and other times the odds ratios were associational. Either could be appropriate, but the authors should think carefully through and be explicit about the assumptions needed for the one they choose. Additionally, the authors described TMLE as a causal machine learning method – however, TMLE is a statistical estimator that can incorporate machine learning in its estimation process and can yield causal effect estimates, but TMLE does not necessarily/always use machine learning or produce causal effects. That said, the authors used an adequate method for accounting for measured confounding in their estimation procedure, and they speak to the limitations of possible unmeasured confounding (a property of most observational data analyses) in the discussion. Finally, the conclusions were sound and, more importantly, signaled the need for closely monitoring antibiotic prescribing due to the potential implications of antibiotic resistance.

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