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Analysis of antibiotic prescribing through multi-level modelling: variability and drivers

Safe People

Organisation name

Ulster University

Organisation sector

Academic Institute

Applicant name(s)

Magda Bucholc

Funders/ Sponsors

Economic and Social Research Council

DEA accredited researcher?

Yes

Safe Projects

Project ID

E093

Lay summary

Antimicrobial resistance (AMR) has become one of the most serious global public health threats. In 2019, AMR contributed to an estimated 1.27 million deaths worldwide. This number is predicted to rise to 10 million people per year by 2050, with a corresponding loss of $60-100 trillion in economic output. Increased AMR not only endangers the efficacy of antibiotics but also leads to infection-related complications, prolonged illness, higher hospitalisation rates, and increased mortality. Concerns about AMR resulted in increased monitoring and evaluation of antibiotic prescribing, with primary care responsible for over 80% of these prescriptions. Demographic, geographic, and socio-economic factors have been shown to have a significant effect on prescribing rates. Furthermore, higher antibiotic prescribing has been reported among patients who have high rates of comorbidity, suggesting the need for stewardship interventions that focus on comorbid patients with high-frequency antibiotic use. Although reducing antibiotic use is central to antimicrobial stewardship, it may have unintended consequences. In particular, there is currently uncertainty with regards to the relationship between antibiotic prescribing levels and complications that can arise after various common infections. Through this study, we aim to i) analyse temporal trends and variations in antibiotic prescribing at GP practice level; ii) investigate the association between antibiotic prescribing and demographic, clinical, geographic, and socio-economic characteristics, and iii) evaluate the association between antibiotic prescribing and infection-related hospitalisations. Investigating antibiotic prescribing can help public health authorities identify trends, outbreaks, and determinants of high antibiotic use, enabling them to take preventive measures.

Public benefit statement

The public will benefit as the knowledge generated by this investigation will contribute to the debate on determinants of antibiotic prescribing in primary care and provide actionable insights to policy makers responsible for antimicrobial stewardship and public health campaigns.

Other approval committees

Latest approval date

04/03/2024

Safe Data

Dataset(s) name

National Health Application and Infrastructure Services (NHAIS)

Enhanced Prescribing Data (EPD)

Hospital Inpatient Data (PAS)

Safe Setting

Access type

TRE

Safe Outputs

Link to research outputs