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Abstract
Objectives – Antibiotics are effective in treating bacterial infections, but they carry the risks of antimicrobial resistance and effectiveness loss. This study aimed to assess whether antibiotics for common infections are prescribed in a risk-based manner and how this changed during the COVID-19 pandemic.
Design – Cohort study of common infections and antibiotic prescribing.
Setting – With the approval of NHS England, we accessed pseudonymised patient-level electronic health records of primary care data from The Phoenix Partnership (TPP) through OpenSAFELY.
Participants – We included adults registered at general practices in England with a record of common infection, including lower respiratory tract infection (LRTI), upper respiratory tract infections (URTI), and lower urinary tract infection (UTI), from January 2019 to March 2023. Patients with a record of COVID-19 were excluded.
Main outcome measures – Patient-specific risks of infection-related hospital admission were estimated for each infection using risk prediction scores for ;patients who were not prescribed an antibiotic. The infection cohorts were then grouped into risk deciles and probabilities of being prescribed an antibiotic were assessed.
Results – We found 15,719,750 diagnoses of common infections. Of them, 450,215 (2.86%) were hospitalised in the 30 days after the diagnosis and 10,429,060 (66.34%) prescribed an antibiotic. There were substantial differences in observed rates of hospital admissions between the lowest and highest risk deciles (25-fold difference in URTI). The probability of being prescribed an antibiotic for LRTI or UTI was unrelated to hospital admission risk, and that for URTI was weakly related to hospital admission risk. During the COVID-19 pandemic, the level of risk-based antibiotic prescribing reduced.
Conclusions – There is a need to better target antibiotics in primary care to patients with worse prognosis and strengthen treatment guidelines in personalisation of prescribing.
Design – Cohort study of common infections and antibiotic prescribing.
Setting – With the approval of NHS England, we accessed pseudonymised patient-level electronic health records of primary care data from The Phoenix Partnership (TPP) through OpenSAFELY.
Participants – We included adults registered at general practices in England with a record of common infection, including lower respiratory tract infection (LRTI), upper respiratory tract infections (URTI), and lower urinary tract infection (UTI), from January 2019 to March 2023. Patients with a record of COVID-19 were excluded.
Main outcome measures – Patient-specific risks of infection-related hospital admission were estimated for each infection using risk prediction scores for ;patients who were not prescribed an antibiotic. The infection cohorts were then grouped into risk deciles and probabilities of being prescribed an antibiotic were assessed.
Results – We found 15,719,750 diagnoses of common infections. Of them, 450,215 (2.86%) were hospitalised in the 30 days after the diagnosis and 10,429,060 (66.34%) prescribed an antibiotic. There were substantial differences in observed rates of hospital admissions between the lowest and highest risk deciles (25-fold difference in URTI). The probability of being prescribed an antibiotic for LRTI or UTI was unrelated to hospital admission risk, and that for URTI was weakly related to hospital admission risk. During the COVID-19 pandemic, the level of risk-based antibiotic prescribing reduced.
Conclusions – There is a need to better target antibiotics in primary care to patients with worse prognosis and strengthen treatment guidelines in personalisation of prescribing.
| Original language | English |
|---|---|
| Journal | Journal of the Royal Society of Medicine |
| Early online date | 3 Apr 2025 |
| DOIs | |
| Publication status | E-pub ahead of print - 3 Apr 2025 |
Keywords
- Antibiotics
- infections
- hospital admissions
- antimicrobial resistance
- COVID-19 pandemic
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NIHR Manchester Biomedical Research Centre
Bruce, I. (PI), Lord, G. (CoI), Lennon, R. (CoI), Black, G. (CoI), Wedge, D. (CoI), Morris, A. (CoI), Hussell, T. (CoI), Sharrocks, A. (CoI), Stivaros, S. (CoI), Buch, M. (CoI), Gough, J. (CoI), Kostarelos, K. (CoI), Thistlethwaite, F. (CoI), Kadler, K. (CoI), Barton, A. (CoI), Hyrich, K. (CoI), Mcbeth, J. (CoI), O'Neill, T. (CoI), Vestbo, J. (CoI), Simpson, A. (CoI), Singh, S. (CoI), Smith, J. (CoI), Felton, T. (CoI), Murray, C. (CoI), Griffiths, C. (CoI), Cullum, N. (CoI), Rhodes, L. (CoI), Warren, R. (CoI), Paus, R. (CoI), Dumville, J. (CoI), Viros Usandizaga, A. (CoI), Keavney, B. (CoI), Tomaszewski, M. (CoI), Allan, S. (CoI), Body, R. (CoI), Cartwright, E. (CoI), Heagerty, A. (CoI), Kalra, P. (CoI), Miller, C. (CoI), Rutter, M. (CoI), Smith, C. (CoI), Trafford, A. (CoI), Evans, D. (CoI), Crosbie, E. (CoI), Crosbie, P. (CoI), Harvie, M. (CoI), Howell, S. (CoI), Renehan, A. (CoI), Dive, C. (CoI), Blackhall, F. (CoI), Landers, D. (CoI), Krebs, M. (CoI), Cook, N. (CoI), Clarke, R. (CoI), Taylor, S. (CoI), Jorgensen, C. (CoI), Lorigan, P. (CoI), Jayson, G. (CoI), Valle, J. (CoI), Mccabe, M. (CoI), Armstrong, A. (CoI), Freitas, A. (CoI), Illidge, T. (CoI), Choudhury, A. (CoI), Hoskin, P. (CoI), West, C. (CoI), Van Herk, M. (CoI), Faivre-Finn, C. (CoI), Bristow, R. (CoI), Kirkby, K. (CoI), Birtle, A. (CoI), Mackay, R. (CoI), Radford, J. (CoI), Linton, K. (CoI), Higham, C. (CoI), Munro, K. (CoI), Plack, C. (CoI), Arden Armitage, C. (CoI), Bruce, I. (CoI), Moore, D. (CoI), Saunders, G. (CoI), Stone, M. (CoI), Haddock, G. (CoI), Lewis, S. (CoI), Elliott, R. (CoI), Green, J. (CoI), Lovell, K. (CoI), Morrison, A. (CoI), Shaw, J. (CoI), Bucci, S. (CoI), Ainsworth, J. (CoI), Webb, R. (CoI), Newman, W. (CoI), Banka, S. (CoI), Clayton-Smith, J. (CoI), Payne, K. (CoI), Moldovan, R. (CoI), Wynn, R. (CoI) & Jones, S. (CoI)
1/12/22 → 30/11/27
Project: Research