Dataset Information

The impact of COVID-19 on antibiotic prescribing in primary care in England: Evaluation and risk prediction of appropriateness of type and repeat prescribing.

ABSTRACT:

Background

This study aimed to predict risks of potentially inappropriate antibiotic type and repeat prescribing and assess changes during COVID-19.

Methods

With the approval of NHS England, we used OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system and selected patients prescribed antibiotics from 2019 to 2021. Multinomial logistic regression models predicted patient's probability of receiving inappropriate antibiotic type or repeat antibiotic course for each common infection.

Results

The population included 9.1 million patients with 29.2 million antibiotic prescriptions. 29.1% of prescriptions were identified as repeat prescribing. Those with same day incident infection coded in the EHR had considerably lower rates of repeat prescribing (18.0%) and 8.6% had potentially inappropriate type. No major changes in the rates of repeat antibiotic prescribing during COVID-19 were found. In the 10 risk prediction models, good levels of calibration and moderate levels of discrimination were found.

Conclusions

Our study found no evidence of changes in level of inappropriate or repeat antibiotic prescribing after the start of COVID-19. Repeat antibiotic prescribing was frequent and varied according to regional and patient characteristics. There is a need for treatment guidelines to be developed around antibiotic failure and clinicians provided with individualised patient information.

SUBMITTER: Zhong X

PROVIDER: S-EPMC10176893 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Publications

The impact of COVID-19 on antibiotic prescribing in primary care in England: Evaluation and risk prediction of appropriateness of type and repeat prescribing.

Zhong Xiaomin X Pate Alexander A Yang Ya-Ting YT Fahmi Ali A Ashcroft Darren M DM Goldacre Ben B MacKenna Brian B Mehrkar Amir A Bacon Sebastian C J SCJ Massey Jon J Fisher Louis L Inglesby Peter P Hand Kieran K van Staa Tjeerd T Palin Victoria V

The Journal of infection 20230512 1

<h4>Background</h4>This study aimed to predict risks of potentially inappropriate antibiotic type and repeat prescribing and assess changes during COVID-19.<h4>Methods</h4>With the approval of NHS England, we used OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system and selected patients prescribed antibiotics from 2019 to 2021. Multinomial logistic regression models predicted patient's probability of receiving inappropriate antibiotic type or repeat antibiotic co ...[more]

PMID: 37182748

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Project description:IntroductionThe persistent development and spread of resistance to antibiotics remain an important public health concern in the UK and globally. About 74% of antibiotics prescribed in England in 2016 was in primary care. The Quality Premium (QP) initiative that rewards Clinical Commissioning Groups (CCGs) financially based on the quality of specific health services commissioned is one of the National Health Service (NHS) England interventions to reduce antimicrobial resistance through reduced prescribing. Emerging evidence suggests a reduction in antibiotic prescribing in primary care practices in the UK following QP initiative. This study aims to investigate the mechanism of impact of this high-cost health-system level intervention on antibiotic prescribing in primary care practices in England.Methods and analysisThe study will constitute secondary analyses of antibiotic prescribing data for almost all primary care practices in England from the NHS England Antibiotic Quality Premium Monitoring Dashboard and OpenPrescribing covering the period 2013 to 2018. The primary outcome is the number of antibiotic items per Specific Therapeutic group Age-sex Related Prescribing Unit (STAR-PU) prescribed monthly in each practice or CCG. We will first conduct an interrupted time series using ordinary least square regression method to examine whether antibiotic prescribing rate in England has changed over time, and how such changes, if any, are associated with QP implementation. Single and sequential multiple-mediator models using a unified approach for the natural direct and indirect effects will be conducted to investigate the relationship between QP initiative, the potential mediators and antibiotic prescribing rate with adjustment for practice and CCG characteristics.Ethics and disseminationThis study will use secondary data that are anonymised and obtained from studies that have either undergone ethical review or generated data from routine collection systems. Multiple channels will be used in disseminating the findings from this study to academic and non-academic audiences.

Project description:BackgroundThere has been growing international interest in performing remote consultations in primary care, particularly amidst the current COVID-19 pandemic. Despite this, the evidence surrounding the safety of remote consultations is inconclusive. The appropriateness of antibiotic prescribing in remote consultations is an important aspect of patient safety that needs to be addressed.ObjectiveThis study aimed to summarize evidence on the impact of remote consultation in primary care with regard to antibiotic prescribing.MethodsSearches were conducted in MEDLINE, Embase, HMIC, PsycINFO, and CINAHL for literature published since the databases' inception to February 2020. Peer-reviewed studies conducted in primary health care settings were included. All remote consultation types were considered, and studies were required to report any quantitative measure of antibiotic prescribing to be included in this systematic review. Studies were excluded if there were no comparison groups (face-to-face consultations).ResultsIn total, 12 studies were identified. Of these, 4 studies reported higher antibiotic-prescribing rates, 5 studies reported lower antibiotic-prescribing rates, and 3 studies reported similar antibiotic-prescribing rates in remote consultations compared with face-to-face consultations. Guideline-concordant prescribing was not significantly different between remote and face-to-face consultations for patients with sinusitis, but conflicting results were found for patients with acute respiratory infections. Mixed evidence was found for follow-up visit rates after remote and face-to-face consultations.ConclusionsThere is insufficient evidence to confidently conclude that remote consulting has a significant impact on antibiotic prescribing in primary care. However, studies indicating higher prescribing rates in remote consultations than in face-to-face consultations are a concern. Further, well-conducted studies are needed to inform safe and appropriate implementation of remote consulting to ensure that there is no unintended impact on antimicrobial resistance.

Project description:BackgroundThere 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.MethodsWith 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.ResultsRecords 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.ConclusionsChanges 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.

Project description:BackgroundInternationally, there are growing concerns about antimicrobial resistance. This has resulted in increased scrutiny of antibiotic prescribing trends - particularly in primary care where the majority of prescribing occurs. In England, antibiotic prescribing targets are set nationally but little is known about the local context of antibiotic prescribing. This study aimed to examine trends in antibiotic prescribing (including broad-spectrum), and the association with area-level deprivation and region in England.MethodsAntibiotic prescribing data by GP surgery in England were obtained from NHS Business Service Authority for the years 2014-2018. These data were matched with the Index of Multiple Deprivation (IMD) 2015 at the Lower Layer Super Output Area level Lower Layer Super Output Area (LSOA) level. Linear regression methods were employed to explore the relationship between antibiotic use and area-level deprivation as well as region, after controlling for a range of other confounding variables, including health need, rurality, and ethnicity.ResultsOver time, the amount of antibiotic prescribing significantly reduced from 1.11 items per STAR-PU to 0.96 items per STAR-PU - a reduction of 13.6%. The adjusted models found that, at LSOA level, the most deprived areas of England had the highest levels of antibiotic prescribing (0.03 items per STAR-PU higher). However, broad spectrum antibiotic prescribing exceeding 10% of all antibiotic prescribing within a GP practice was higher in more affluent areas. There were also significant regional differences - with the North East and the East of England having the highest levels of antibiotic prescribing (by 0.16 items per STAR-PU).ConclusionAlthough antibiotic prescribing has reduced over time, there remains significant variation in by area-level deprivation and region in England - with higher antibiotic prescribing in more deprived areas. Future prescribing targets should account for local factors to ensure the most deprived communities are not inappropriately penalised.

Dataset Information

The impact of COVID-19 on antibiotic prescribing in primary care in England: Evaluation and risk prediction of appropriateness of type and repeat prescribing.

Background

Methods

Results

Conclusions

Publications

The impact of COVID-19 on antibiotic prescribing in primary care in England: Evaluation and risk prediction of appropriateness of type and repeat prescribing.

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