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Antibiotics for Common Infections in Primary Care Before, During and after the COVID-19 Pandemic and Extent of Risk-Based Prescribing: Need for Personalised Guidelines

19 Pages Posted: 10 Nov 2023

See all articles by Ali Fahmi

Ali Fahmi

The University of Manchester

Ya-Ting Yang

The University of Manchester

Xiaomin Zhong

The University of Manchester

Alexander Pate

The University of Manchester

Anita Sharma

Chadderton South Health Centre

Simon Watts

The University of Manchester - Manchester University NHS Foundation Trust

Darren Ashcroft

The University of Manchester - Manchester Academic Health Science Centre (MAHSC)

Ben Goldacre

University of Oxford - Bennett Institute of Applied Data Science

Brian Mackenna

University of Oxford

Jon Massey

University of Oxford - Bennett Institute of Applied Data Science

Amir Mehrkar

University of Oxford - Bennett Institute of Applied Data Science

Sebastian Bacon

University of Oxford - Bennett Institute of Applied Data Science

Paul Dark

North Manchester General Hospital - Regional Infectious Diseases Unit

Kieran Hand

Government of the United Kingdom - National Health Service (NHS)

Victoria Palin

The University of Manchester

Tjeerd P. Van Staa

The University of Manchester - Centre for Health Informatics; Utrecht University - Utrecht Institute of Pharmaceutical Science

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Abstract

Background: To assess whether antibiotics for common infections are prescribed in a risk-based manner and how this changed during the COVID-19 pandemic.

Methods: 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. 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). Patients with a record of COVID-19 were excluded. Patient-specific risks of infection-related hospital admission were estimated for each infection cohort (not prescribed an antibiotic) using predictors. These predicted non-antibiotic risks were then applied to the antibiotic users and cohorts split into risk deciles.

Findings: We found 15,719,750 diagnoses of common infections from January 2019 to March 2023. 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. The probability of prescribed antibiotic was unrelated for LRTI and UTI’s admission risks and weakly for URTI. During the COVID-19 pandemic, the level of risk-based antibiotic prescribing reduced. Predictors were not or only weakly associated with the probability of antibiotic prescribing.

Interpretation: There is a need to better target antibiotics in primary care to patients with worse prognosis and strengthen treatment guidelines in personalisation of prescribing.

Funding: Health Data Research UK, National Institute for Health and Care Research.

Declaration of Interest: 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.

Ethical Approval: This study was approved by the Health Research Authority and NHS Research Ethics Committee [REC reference 21/SC/0287]. NHS England is the data controller of the NHS England OpenSAFELY COVID-19 Service; TPP is the data processor; all study authors using OpenSAFELY have the approval of NHS England.

Keywords: Antibiotics, infections, hospital admissions, antimicrobial resistance, COVID-19 pandemic

Suggested Citation

Fahmi, Ali and Yang, Ya-Ting and Zhong, Xiaomin and Pate, Alexander and Sharma, Anita and Watts, Simon and Ashcroft, Darren and Goldacre, Ben and Mackenna, Brian and Massey, Jon and Mehrkar, Amir and Bacon, Sebastian and Dark, Paul and Hand, Kieran and Palin, Victoria and Van Staa, Tjeerd P., Antibiotics for Common Infections in Primary Care Before, During and after the COVID-19 Pandemic and Extent of Risk-Based Prescribing: Need for Personalised Guidelines. Available at SSRN: https://ssrn.com/abstract=4626877 or http://dx.doi.org/10.2139/ssrn.4626877

Ali Fahmi (Contact Author)

The University of Manchester ( email )

Oxford Road
Manchester, M13 9PL
United Kingdom

Ya-Ting Yang

The University of Manchester ( email )

Oxford Road
Manchester, M13 9PL
United Kingdom

Xiaomin Zhong

The University of Manchester ( email )

Oxford Road
Manchester, M13 9PL
United Kingdom

Alexander Pate

The University of Manchester ( email )

Oxford Road
Manchester, M13 9PL
United Kingdom

Anita Sharma

Chadderton South Health Centre ( email )

Simon Watts

The University of Manchester - Manchester University NHS Foundation Trust ( email )

Oxford Road
Manchester, M13 9PL
United Kingdom

Darren Ashcroft

The University of Manchester - Manchester Academic Health Science Centre (MAHSC) ( email )

46 Grafton Street
Manchester, M13 9NT
United Kingdom

Ben Goldacre

University of Oxford - Bennett Institute of Applied Data Science ( email )

Brian Mackenna

University of Oxford ( email )

Mansfield Road
Oxford, OX1 4AU
United Kingdom

Jon Massey

University of Oxford - Bennett Institute of Applied Data Science ( email )

Amir Mehrkar

University of Oxford - Bennett Institute of Applied Data Science ( email )

Sebastian Bacon

University of Oxford - Bennett Institute of Applied Data Science ( email )

Paul Dark

North Manchester General Hospital - Regional Infectious Diseases Unit ( email )

Kieran Hand

Government of the United Kingdom - National Health Service (NHS) ( email )

Victoria Palin

The University of Manchester ( email )

United Kingdom

Tjeerd P. Van Staa

The University of Manchester - Centre for Health Informatics ( email )

United Kingdom

Utrecht University - Utrecht Institute of Pharmaceutical Science ( email )

Padualaan 8
Utrecht, 3584 CH
Netherlands

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