Dataset Information

Antibiotic prescribing for common infections in UK general practice: variability and drivers.

ABSTRACT:

Objectives

To examine variations across general practices and factors associated with antibiotic prescribing for common infections in UK primary care to identify potential targets for improvement and optimization of prescribing.

Methods

Oral antibiotic prescribing for common infections was analysed using anonymized UK primary care electronic health records between 2000 and 2015 using the Clinical Practice Research Datalink (CPRD). The rate of prescribing for each condition was observed over time and mean change points were compared with national guideline updates. Any correlation between the rate of prescribing for each infectious condition was estimated within a practice. Predictors of prescribing were estimated using logistic regression in a matched patient cohort (1:1 by age, sex and calendar time).

Results

Over 8 million patient records were examined in 587 UK general practices. Practices varied considerably in their propensity to prescribe antibiotics and this variance increased over time. Change points in prescribing did not reflect updates to national guidelines. Prescribing levels within practices were not consistent for different infectious conditions. A history of antibiotic use significantly increased the risk of receiving a subsequent antibiotic (by 22%-48% for patients with three or more antibiotic prescriptions in the past 12?months), as did higher BMI, history of smoking and flu vaccinations. Other drivers for receiving an antibiotic varied considerably for each condition.

Conclusions

Large variability in antibiotic prescribing between practices and within practices was observed. Prescribing guidelines alone do not positively influence a change in prescribing, suggesting more targeted interventions are required to optimize antibiotic prescribing in the UK.

SUBMITTER: Palin V

PROVIDER: S-EPMC6640319 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Antibiotic prescribing for common infections in UK general practice: variability and drivers.

Palin Victoria V Mölter Anna A Belmonte Miguel M Ashcroft Darren M DM White Andrew A Welfare William W van Staa Tjeerd T

The Journal of antimicrobial chemotherapy 20190801 8

<h4>Objectives</h4>To examine variations across general practices and factors associated with antibiotic prescribing for common infections in UK primary care to identify potential targets for improvement and optimization of prescribing.<h4>Methods</h4>Oral antibiotic prescribing for common infections was analysed using anonymized UK primary care electronic health records between 2000 and 2015 using the Clinical Practice Research Datalink (CPRD). The rate of prescribing for each condition was obs ...[more]

PMID: 31038162

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Project description:ObjectivesDespite widespread availability of evidence-based guidelines to inform rational use of medicines, considerable unwarranted variation exists in prescribing. A greater understanding of key determinants of contemporary prescribing in UK general practice could inform strategies to promote evidence-based prescribing. This study explored (1) current influences on prescribing in general practice and (2) the possibility that general practice-based pharmacists (PBPs) may contribute to greater engagement with evidence-based prescribing.DesignSemistructured, telephone interviews and a focus group were conducted, audio-recorded and transcribed verbatim. Thematic analysis was undertaken.ParticipantsGeneral practice prescribers: general practitioners (GPs), PBPs, nurses.Key informants: individuals within the National Health Service (NHS) with responsibility for influencing, monitoring and measuring general practice prescribing.SettingGeneral practices and NHS organisations in England.ResultsInterviews with 17 prescribers (GPs (n=6), PBPs (n=6), nurses (n=5)) and 6 key informants, and one focus group with five key informants were undertaken between November 2018 and April 2019. Determinants operating at individual, practice and societal levels impacted prescribing and guideline use. Prescribers' professional backgrounds, for example, nursing, pharmacy, patient populations and patient pressure were perceived as substantial influences, as well as media portrayal and public perceptions of medicines.Prescribers identified practice-level determinants of prescribing, including practice culture and shared beliefs. Key informants tended to emphasise higher-level influences, including NHS policies, availability of support and advice from secondary care and generic challenges associated with medicines use, for example, multimorbidity.Participants expressed mixed views about the potential of PBPs to promote evidence-based prescribing in general practice.ConclusionPrescribing in UK general practice is influenced by multiple intersecting factors. Strategies to promote evidence-based prescribing should target modifiable influences at practice and individual levels. Customising strategies for medical and non-medical prescribers may maximise their effectiveness.

Project description:To assess the effects of a multifaceted educational intervention in Norwegian general practice aiming to reduce antibiotic prescription rates for acute respiratory tract infections and to reduce the use of broad spectrum antibiotics.Cluster randomised controlled study.Existing continuing medical education groups were recruited and randomised to intervention or control.79 groups, comprising 382 general practitioners, completed the interventions and data extractions.The intervention groups had two visits by peer academic detailers, the first presenting the national clinical guidelines for antibiotic use and recent research evidence on acute respiratory tract infections, the second based on feedback reports on each general practitioner's antibiotic prescribing profile from the preceding year. Regional one day seminars were arranged as a supplement. The control arm received a different intervention targeting prescribing practice for older patients.Prescription rates and proportion of non-penicillin V antibiotics prescribed at the group level before and after the intervention, compared with corresponding data from the controls.In an adjusted, multilevel model, the effect of the intervention on the 39 intervention groups (183 general practitioners) was a reduction (odds ratio 0.72, 95% confidence interval 0.61 to 0.84) in prescribing of antibiotics for acute respiratory tract infections compared with the controls (40 continuing medical education groups with 199 general practitioners). A corresponding reduction was seen in the odds (0.64, 0.49 to 0.82) for prescribing a non-penicillin V antibiotic when an antibiotic was issued. Prescriptions per 1000 listed patients increased from 80.3 to 84.6 in the intervention arm and from 80.9 to 89.0 in the control arm, but this reflects a greater incidence of infections (particularly pneumonia) that needed treating in the intervention arm.The intervention led to improved antibiotic prescribing for respiratory tract infections in a representative sample of Norwegian general practitioners, and the courses were feasible to the general practitioners.Clinical trials NCT00272155.

Project description:Study questionWhat is the prevalence of different types of potentially hazardous prescribing in general practice in the United Kingdom, and what is the variation between practices?MethodsA cross sectional study included all adult patients potentially at risk of a prescribing or monitoring error defined by a combination of diagnoses and prescriptions in 526 general practices contributing to the Clinical Practice Research Datalink (CPRD) up to 1 April 2013. Primary outcomes were the prevalence of potentially hazardous prescriptions of anticoagulants, anti-platelets, NSAIDs, β blockers, glitazones, metformin, digoxin, antipsychotics, combined hormonal contraceptives, and oestrogens and monitoring by blood test less frequently than recommended for patients with repeated prescriptions of angiotensin converting enzyme inhibitors and loop diuretics, amiodarone, methotrexate, lithium, or warfarin.Study answer and limitations49 927 of 949 552 patients at risk triggered at least one prescribing indicator (5.26%, 95% confidence interval 5.21% to 5.30%) and 21 501 of 182 721 (11.8%, 11.6% to 11.9%) triggered at least one monitoring indicator. The prevalence of different types of potentially hazardous prescribing ranged from almost zero to 10.2%, and for inadequate monitoring ranged from 10.4% to 41.9%. Older patients and those prescribed multiple repeat medications had significantly higher risks of triggering a prescribing indicator whereas younger patients with fewer repeat prescriptions had significantly higher risk of triggering a monitoring indicator. There was high variation between practices for some indicators. Though prescribing safety indicators describe prescribing patterns that can increase the risk of harm to the patient and should generally be avoided, there will always be exceptions where the indicator is clinically justified. Furthermore there is the possibility that some information is not captured by CPRD for some practices-for example, INR results in patients receiving warfarin.What this study addsThe high prevalence for certain indicators emphasises existing prescribing risks and the need for their appropriate consideration within primary care, particularly for older patients and those taking multiple medications. The high variation between practices indicates potential for improvement through targeted practice level intervention.Funding, competing interests, data sharingNational Institute for Health Research through the Greater Manchester Primary Care Patient Safety Translational Research Centre (grant No GMPSTRC-2012-1). Data from CPRD cannot be shared because of licensing restrictions.

Dataset Information

Antibiotic prescribing for common infections in UK general practice: variability and drivers.

Objectives

Methods

Results

Conclusions

Publications

Antibiotic prescribing for common infections in UK general practice: variability and drivers.

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