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. 2023 Sep 16;12(1):102.
doi: 10.1186/s13756-023-01280-6.

The impact of the COVID-19 pandemic on the treatment of common infections in primary care and the change to antibiotic prescribing in England

Affiliations

The impact of the COVID-19 pandemic on the treatment of common infections in primary care and the change to antibiotic prescribing in England

Ya-Ting Yang et al. Antimicrob Resist Infect Control. .

Abstract

Background: There is concern that the COVID-19 pandemic altered the management of common infections in primary care. This study aimed to evaluate infection-coded consultation rates and antibiotic use during the pandemic and how any change may have affected clinical outcomes.

Methods: With the approval of NHS England, a retrospective cohort study using the OpenSAFELY platform analysed routinely collected electronic health data from GP practices in England between January 2019 and December 2021. Infection coded consultations and antibiotic prescriptions were used estimate multiple measures over calendar months, including age-sex adjusted prescribing rates, prescribing by infection and antibiotic type, infection consultation rates, coding quality and rate of same-day antibiotic prescribing for COVID-19 infections. Interrupted time series (ITS) estimated the effect of COVID-19 pandemic on infection-coded consultation rates. The impact of the pandemic on non- COVID-19 infection-related hospitalisations was also estimated.

Results: Records from 24 million patients were included. The rate of infection-related consultations fell for all infections (mean reduction of 39% in 2020 compared to 2019 mean rate), except for UTI which remained stable. Modelling infection-related consultation rates highlighted this with an incidence rate ratio of 0.44 (95% CI 0.36-0.53) for incident consultations and 0.43 (95% CI 0.33-0.54) for prevalent consultations. Lower respiratory tract infections (LRTI) saw the largest reduction of 0.11 (95% CI 0.07-0.17). Antibiotic prescribing rates fell with a mean reduction of 118.4 items per 1000 patients in 2020, returning to pre-pandemic rates by summer 2021. Prescribing for LRTI decreased 20% and URTI increased 15.9%. Over 60% of antibiotics were issued without an associated same-day infection code, which increased during the pandemic. Infection-related hospitalisations reduced (by 62%), with the largest reduction observed for pneumonia infections (72.9%). Same-day antibiotic prescribing for COVID-19 infection increased from 1 to 10.5% between the second and third national lockdowns and rose again during 2022.

Conclusions: Changes to consultations and hospital admissions may be driven by reduced transmission of non-COVID-19 infections due to reduced social mixing and lockdowns. Inconsistencies in coding practice emphasises the need for improvement to inform new antibiotic stewardship policies and prevent resistance to novel infections.

Keywords: Antibiotic stewardship; Antibiotics; COVID-19 pandemic; Infection; Primary care.

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Conflict of interest statement

BG and OpenSAFELY has received research funding from the Laura and John Arnold Foundation, the NHS National Institute for Health Research (NIHR), the NIHR School of Primary Care Research, NHS England, the NIHR Oxford Biomedical Research Centre, the Mohn-Westlake Foundation, NIHR Applied Research Collaboration Oxford and Thames Valley, the Wellcome Trust, the Good Thinking Foundation, Health Data Research UK, the Health Foundation, the World Health Organisation, UKRI MRC, Asthma UK, the British Lung Foundation, and the Longitudinal Health and Wellbeing strand of the National Core Studies programme; he is a Non-Executive Director at NHS Digital; he also receives personal income from speaking and writing for lay audiences on the misuse of science. AM has received consultancy fees (from https:// inductionhealthcare.com) and is member of RCGP health informatics group and the NHS Digital GP data Professional Advisory Group that advises on access to GP Data for Pandemic Planning and Research (GDPPR). For the latter, he received payment for the GDPPR role.

Figures

Fig. 1
Fig. 1
A Monthly antibiotic prescribing rates per 1000 registered patients; B Specific Therapeutic group Age-sex Related Prescribing Unit (STAR-PU) adjusted monthly antibiotic prescribing rates per 1000 registered patients. Data from approximately 2544 TTP practices − 50th percentile; − 25th and 75th percentile, − 5th and 95th percentile
Fig. 2
Fig. 2
Monthly incident consultation rates per 1000 registered patients, stratified by common infections. Grey shading represents England national lockdown periods. Data from approximately 2544 TTP practices. Dotted lines indicate observation counts < 5. For monthly prevalent consultation rates, see SAdditional file 1: Fig. S2
Fig. 3
Fig. 3
Interrupted time series analysis of incident consultation rates pre and during COVID-19 periods, overall and stratified by consultation recorded infection type A Modelled consultation rate change before and during pandemic (blue), modelled counterfactual rate if COVID-19 did not occur (red) and actual rate (black cross), b Incidence rate ratio (IRR) of consultation rates
Fig. 4
Fig. 4
The proportion of infection coded consultations that resulted in an antibiotic prescription on the A same day, or B within ± 7 days. Figure represents all incident consultations. For prevalent consultations see Additional file 1: Fig. S3. Grey shading represents England national lockdown periods
Fig. 5
Fig. 5
the top five antibiotics prescribed, by type, for six common infections for incident consultations over time. Data represents consultations that resulted in an antibiotic prescription only. Grey shading represents England national lockdown periods. For the top five antibiotics prescribed for prevalent infection coded consultation, see Additional file 1: Fig. S4
Fig. 6
Fig. 6
Percentage of episode of the same day COVID-19 diagnosis with an antibiotic prescription (± 2 days) as recorded in primary care (GP) records or the Second Generation Surveillance System (SGSS). Grey shading represents England national lockdown periods
Fig. 7
Fig. 7
The rate of infection-related hospital admissions over calendar time
Fig. 8
Fig. 8
A proxy for infection coding quality. The percentage of incident (A) and repeated (B) antibiotic prescriptions with and without same-day infection codes recorded. Analysis included multiple common infections, displaying the percentage for the top six common infections and all other infections grouped. Grey shading represents the national lockdown periods in England over time. Data are from approximately 2544 TTP practices

References

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