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Venn diagram of identifying top 20% of practices in terms of antibiotic prescribing rate per STAR-PU using three different methodologies, after removing outer 1% of practices based on antibiotic prescribing rate per STAR-PU. The full model considered all variables (blue ellipse, see Table 2), the comorbidity model considered only comorbidities (pink ellipse, see Table 2) and the current methodology is based on ranking practices based on their antibiotic prescribing rate per STAR-PU without taking into account any other variables (yellow ellipse). STAR-PU: Specific Therapeutic Group Age-sex weighting Related Prescribing Unit.
Source publication
Background
Seeing one's practice as a high antibiotic prescriber compared to general practices with similar patient populations can be one of the best motivators for change. Current comparisons are based on age-sex weighting of the practice population for expected prescribing rates (STAR-PU). Here, we investigate whether there is a need to addition...
Context in source publication
Context 1
... to the main analysis, there is substantial overlap between the different methodologies to identify the top 20% of antibiotic prescribers. In 1104 out of 1463 (75.5%) the STAR-PU based method and the model- based methods agree on which practices are among the top 20% highest antibiotic prescribers (Fig. 2). Table S2 shows the ranking of all practices based on the three different ...
Citations
... Monthly measures were estimated for antibiotic prescribing rate using the total number of antibiotic prescriptions divided by the population size multiplied by 1000 to get a prescribing rate per 1000 registered patients per month (crude) as well as practice-level agesex adjusted (STAR-PU) prescribing rates [18,19] Rates of consultations by common infection type were calculated at the practice level or for different age groups by dividing the number of infection-specific consultations by the population size multiplied by 1000. For infection-coded consultations, the rate of same day antibiotic prescribing was calculated by infection type, as well as prescribing within ± 7 days of the coded infection. ...
Background
There 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.
Methods
With 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.
Results
Records 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.
Conclusions
Changes 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.
... We adjusted for factors (or their proxies) known to be associated with antibiotic prescribing. These included comorbidities such as asthma or COPD, (17)(18)(19)(20) health need, rurality, ethnicity, deprivation, (21) region (22), CCG, (23) . CC-BY-NC 4.0 International license It is made available under a perpetuity. ...
Background
The COVID-19 pandemic has led to an ongoing increase in the use of remote consultations in general practice in England. Though the evidence is limited, there are concerns that the increase in remote consultations could lead to more antibiotic prescribing.
Methods
We used patient-level primary care data from the Clinical Practice Research Datalink to estimate the association between consultation mode (remote vs face-to-face) and antibiotic prescribing in England for acute respiratory infections (ARI) between April 2021 - March 2022. We used targeted maximum likelihood estimation, a causal machine learning method with adjustment for patient-, clinician- and practice-level factors.
Findings
There were 45,997 ARI consultations (34,555 unique patients), of which 28,127 were remote and 17,870 face-to-face. For children, 48% of consultations were remote whereas for adults 66% were remote. For children, 42% of remote and 43% face-to-face consultations led to an antibiotic prescription; the equivalent in adults was 52% of remote and 42% face-to-face. Adults with a remote consultation had 23% (Odds Ratio (OR) 1.23 95% Confidence Interval (CI): 1.18-1.29) higher chance of being prescribed antibiotics compared to if they had been seen face-to-face. We found no significant association between consultation mode and antibiotic prescribing in children (OR 1.04 95% CI 0.98-1.11).
Interpretation
This study uses rich patient-level data and robust statistical methods and represents an important contribution to the evidence base on antibiotic prescribing in post-COVID primary care. The higher rates of antibiotic prescribing in remote consultations for adults are cause for concern. We see no significant difference in antibiotic prescribing between consultation mode for children. These findings should inform antimicrobial stewardship activities for health care professionals and policy makers. Future research should examine differences in guideline-compliance between remote and face-to-face consultations to understand the factors driving antibiotic prescribing in different consultation modes.
Funding
No external funding.
Keywords
general practice; England; antibiotics; remote consultations; telehealth; telemedicine; TMLE; causal inference; machine learning; acute respiratory infections; antimicrobial resistance; covid; ARTI; ARI; antibiotic prescribing; primary care
... 8,9 Despite these initiatives, antibiotic prescribing patterns still vary considerably across areas and practices, and some remain high prescribers. 5,[10][11][12] In the authors' previous research, clinical commissioning group and general practice professionals perceived a high turnover of locum GPs as contributing to higher antibiotic prescribing, and locums as more likely than other GPs to be higher prescribers; this was because practices with transient staff were perceived as having less ownership of prescribing and locum GPs were perceived as less accountable for prescribing, less engaged in AMS, less aware of local guidelines, and lacking continuity of care. 13,14 Locum or sessional GPs are registered, licensed GPs who work in temporary positions -often for multiple organisations -covering short-term absences and vacancies. ...
Background:
Most antibiotics are prescribed in primary care. Locum or sessional general practitioners (locums) are perceived as contributing to higher prescribing and may face barriers to engaging with antimicrobial stewardship (AMS).
Aim:
To identify how locums' antibiotic prescribing compares to other general practice prescribers, and how they perceive their role in antibiotic prescribing and AMS.
Design and setting:
A mixed-methods study in primary care.
Methods:
Data on antibiotic prescribing, diagnoses, and patient and prescriber characteristics were extracted from The Health Improvement Network database. A mixed-effects logistic model was used to compare locums' and other prescribers' antibiotic prescribing for conditions which do not usually benefit from antibiotics. Nineteen semi-structured telephone interviews were conducted with locums in England and analysed thematically.
Results:
Locums accounted for 11% of consultations analysed. They prescribed antibiotics more often than other GPs and nurse prescribers for cough, sore throat, asthma exacerbations and acute bronchitis. The percentage of patients receiving antibiotics for these conditions was 4% higher (on absolute scale) when consulting with locums compared to other GPs. Four themes capture the perceived influences on prescribing antibiotics and AMS: (1) Antibiotic prescribing as a complex but individual issue; (2) Nature and patterns of locum work; (3) Relationships between practices and locums; (4) Professional isolation.
Conclusions:
Locums contribute to higher antibiotic prescribing compared to their peers. They experience challenges but also opportunities for contributing to AMS, which should be better addressed. With an increasing proportion of locums, they have an important role in antibiotic optimisation and AMS.
... Target users: Although antibiotic prescribing in general practices has reduced in recent years, studies show that a proportion of general practices remain highprescribing [36][37][38]. Therefore, we identified the 'users' or 'population' to target by our intervention as healthcare professionals in high antibiotic prescribing practices (i.e. in the top quarter of antibiotic prescribing in England). ...
Background
Trials show that antimicrobial stewardship (AMS) strategies, including communication skills training, point-of-care C-reactive protein testing (POC-CRPT) and delayed prescriptions, help optimise antibiotic prescribing and use in primary care. However, the use of these strategies in general practice is limited and inconsistent. We aimed to develop an intervention to enhance uptake and implementation of these strategies in primary care.
Methods
We drew on the Person-Based Approach to develop an implementation intervention in two stages. (1) Planning and design: We defined the problem in behavioural terms drawing on existing literature and conducting primary qualitative research (nine focus groups) in high-prescribing general practices. We identified ‘guiding principles’ with intervention objectives and key features and developed logic models representing intended mechanisms of action. (2) Developing the intervention: We created prototype intervention materials and discussed and refined these with input from 13 health professionals and 14 citizens in two sets of design workshops. We further refined the intervention materials following think-aloud interviews with 22 health professionals.
Results
Focus groups highlighted uncertainties about how strategies could be used. Health professionals in the workshops suggested having practice champions, brief summaries of each AMS strategy and evidence supporting the AMS strategies, and they and citizens gave examples of helpful communication strategies/phrases. Think-aloud interviews helped clarify and shorten the text and user journey of the intervention materials. The intervention comprised components to support practice-level implementation: antibiotic champions, practice meetings with slides provided, and an ‘implementation support’ website section, and components to support individual-level uptake: website sections on each AMS strategy (with evidence, instructions, links to electronic resources) and material resources (patient leaflets, POC-CRPT equipment, clinician handouts).
Conclusions
We used a systematic, user-focussed process of developing a behavioural intervention, illustrating how it can be used in an implementation context. This resulted in a multicomponent intervention to facilitate practice-wide implementation of evidence-based strategies which now requires implementing and evaluating. Focusing on supporting the uptake and implementation of evidence-based strategies to optimise antibiotic use in general practice is critical to further support appropriate antibiotic use and mitigate antimicrobial resistance.
... Most antibiotics are prescribed in general practice (72% in 2018) [1], largely for respiratory tract infections (RTIs) which are often self-limiting [2,3]. England has seen a gradual reduction in antibiotic prescribing but with significant variation in prescribing rates within and between practices, even after accounting for factors such as comorbidities and deprivation [2][3][4][5]. Moreover, there is wide variation in prescribing to less unwell patients [6]. ...
... We used the antibiotic items per STAR-PU as a measure to identify high prescribing practices that may particularly benefit from strategies to support optimising their antibiotic prescribing. High antibiotics/STAR-PU may suggest some suboptimal prescribing but it does not take into consideration potential valid reasons for high prescribing rates such as those practices with high numbers of patients with co-morbidities [5]. In our study, we did not explore in more detail the (in)appropriateness of antibiotic prescribing and only used the antibiotics/ STAR-PU as a proxy to identify practices that may have more scope for and benefit from implementing additional strategies to optimise antibiotics. ...
Background
Trials have shown that delayed antibiotic prescriptions (DPs) and point-of-care C-Reactive Protein testing (POC-CRPT) are effective in reducing antibiotic use in general practice, but these were not typically implemented in high-prescribing practices. We aimed to explore views of professionals from high-prescribing practices about uptake and implementation of DPs and POC-CRPT to reduce antibiotic use.
Methods
This was a qualitative focus group study in English general practices. The highest antibiotic prescribing practices in the West Midlands were invited to participate. Clinical and non-clinical professionals attended focus groups co-facilitated by two researchers. Focus groups were audio-recorded, transcribed verbatim and analysed thematically.
Results
Nine practices (50 professionals) participated. Four main themes were identified. Compatibility of strategies with clinical roles and experience – participants viewed the strategies as having limited value as ‘clinical tools’, perceiving them as useful only in ‘rare’ instances of clinical uncertainty and/or for those less experienced. Strategies as ‘social tools’ – participants perceived the strategies as helpful for negotiating treatment decisions and educating patients, particularly those expecting antibiotics. Ambiguities – participants perceived ambiguities around when they should be used, and about their impact on antibiotic use. Influence of context – various other situational and practical issues were raised with implementing the strategies.
Conclusions
High-prescribing practices do not view DPs and POC-CRPT as sufficiently useful ‘clinical tools’ in a way which corresponds to the current policy approach advocating their use to reduce clinical uncertainty and improve antimicrobial stewardship. Instead, policy attention should focus on how these strategies may instead be used as ‘social tools’ to reduce unnecessary antibiotic use. Attention should also focus on the many ambiguities (concerns and questions) about, and contextual barriers to, using these strategies that need addressing to support wider and more consistent implementation.
... Some potential confounding at practice level may occur due to variation in patient population frailty even when characteristics have been accounted for at practice level. 20 In addition, although this analysis attempted to adjust for several available factors that might influence the association investigated, missing data were present in some of the covariates. The analyses accounted for this by using a missing indicator and the presence of missing data in the covariates could have influenced the estimates, although the large sample size and replication of the analysis in a second database (SAIL) gives weight to the interpretation of the results. ...
Objective:
Determine the association of incident antibiotic prescribing levels for common infections with infection-related complications and hospitalisations by comparing high with low prescribing general practitioner practices.
Design retrospective cohort study:
Retrospective cohort study.
Data source:
UK primary care records from the Clinical Practice Research Datalink (CPRD GOLD) and SAIL Databank (SAIL) linked with Hospital Episode Statistics (HES) data, including 546 CPRD, 346 CPRD-HES and 338 SAIL-HES practices.
Exposures:
Initial general practice visit for one of six common infections and the proportion of antibiotic prescribing in each practice.
Main outcome measures:
Incidence of infection-related complications (as recorded in general practice) or infection-related hospital admission within 30 days after consultation for a common infection.
Results:
A practice with 10.4% higher antibiotic prescribing (the IQR) was associated with a 5.7% lower rate of infection-related hospital admissions (adjusted analysis, 95% CI 3.3% to 8.0%). The association varied by infection with larger associations in hospital admissions with lower respiratory tract infection (16.1%; 95% CI 12.4% to 19.7%) and urinary tract infection (14.7%; 95% CI 7.6% to 21.1%) and smaller association in hospital admissions for upper respiratory tract infection (6.5%; 95% CI 3.5% to 9.5%) The association of antibiotic prescribing levels and hospital admission was largest in patients aged 18-39 years (8.6%; 95% CI 4.0% to 13.0%) and smallest in the elderly aged 75+ years (0.3%; 95% CI -3.4% to 3.9%).
Conclusions:
There is an association between lower levels of practice level antibiotic prescribing and higher infection-related hospital admissions. Indiscriminately reducing antibiotic prescribing may lead to harm. Greater focus is needed to optimise antibiotic use by reducing inappropriate antibiotic prescribing and better targeting antibiotics to patients at high risk of infection-related complications.
... However, not all CCGs and general practices reduced antibiotic prescribing at the same rate or met the QP targets. There was also considerable overall variation in the volume of antibiotic prescribing [7][8][9][10][11][12], i.e., two-fold differences between the lowest-and highest-prescribing CCGs (2010-2017) [7] and general practices (2004)(2005) [12]. ...
... Some variation in antibiotic prescribing can be explained by patient-related factors, such as comorbidities, smoking, age, weight, ethnicity, or socioeconomic status [7,8,10,12]. However, substantial variation between practices remains even after accounting for comorbidities, smoking, and deprivation [9,10]. ...
... Some variation in antibiotic prescribing can be explained by patient-related factors, such as comorbidities, smoking, age, weight, ethnicity, or socioeconomic status [7,8,10,12]. However, substantial variation between practices remains even after accounting for comorbidities, smoking, and deprivation [9,10]. Higher antibiotic prescribing has been associated with practice characteristics, such as location (north of England, rural), deprivation, larger practice size, or high consultation rates for respiratory infections [7][8][9][11][12][13]. ...
Antibiotic prescribing in England varies considerably between Clinical Commissioning Groups (CCGs) and general practices. We aimed to assess social and contextual factors affecting antibiotic prescribing and engagement with antimicrobial stewardship (AMS) initiatives. Semi-structured telephone interviews were conducted with 22 CCG professionals and 19 general practice professionals. Interviews were audio-recorded, transcribed, and analyzed thematically. Social/contextual influences were grouped into the following four categories: (1) Immediate context, i.e., patients’ social characteristics (e.g., deprivation and culture), clinical factors, and practice and clinician characteristics (e.g., “struggling” with staff shortage/turnover) were linked to higher prescribing. (2) Wider context, i.e., pressures on the healthcare system, limited resources, and competing priorities were seen to reduce engagement with AMS. (3) Collaborative and whole system approaches, i.e., communication, multidisciplinary networks, leadership, and teamwork facilitated prioritizing AMS, learning, and consistency. (4) Relativity of appropriate prescribing, i.e., “high” or “appropriate” prescribing was perceived as relative, depending on comparators, and disregarding different contexts, but social norms around antibiotic use among professionals and patients seemed to be changing. Further optimization of antibiotic prescribing would benefit from addressing social/contextual factors and addressing wider health inequalities, not only targeting individual clinicians. Tailoring and adapting to local contexts and constraints, ensuring adequate time and resources for AMS, and collaborative, whole system approaches to promote consistency may help promote AMS.
... For most conditions, only a minority of antibiotic prescriptions given are necessary [4]. Moreover, a large part of the variation in prescribing rates between general practices cannot be explained by differences in patient comorbidities or other factors such as smoking [5][6][7]. Almost half of all antibiotics prescribed in primary care are for respiratory tract infections (RTIs) such as influenza-like illnesses (ILI), which do not generally require antibiotics [8]. General practitioners (GPs) are more likely to prescribe antibiotics when patients request them or are perceived to want them [9,10]. ...
... Just as diseases often cluster within certain populations according to sociodemographic factors [22], so too does antibiotic use. There is evidence in England and Wales of significant variation in antibiotic prescribing levels by area-level deprivation, with higher prescribing levels in more deprived areas [7,23,24]. Moreover, this association is not fully explained by differences in the prevalence of common chronic conditions or smoking status [7,24]. ...
... There is evidence in England and Wales of significant variation in antibiotic prescribing levels by area-level deprivation, with higher prescribing levels in more deprived areas [7,23,24]. Moreover, this association is not fully explained by differences in the prevalence of common chronic conditions or smoking status [7,24]. In previous work using the present dataset, several of the indicators used in this study have been shown to be associated with a number of sociodemographic characteristics [13]. ...
Influenza-like illnesses (ILI) account for a significant portion of inappropriate antibiotic use. Patient expectations for antibiotics for ILI are likely to play a substantial role in 'unnecessary' antibiotic consumption. This study aimed to investigate trends in awareness of appropriate antibiotic use and antimicrobial resistance (AMR). Three sequential online surveys of independent representative samples of adults in the United Kingdom investigated expectations for, and consumption of, antibiotics for ILI (May/June 2015 (n = 2064); Oct/Nov 2016 (n = 4000); Mar 2017 (n = 4000)). Respondents were asked whether they thought antibiotics were effective for ILI and about their antibiotic use. Proportions and 95% confidence intervals (CI) were calculated for each question and interactions with respondent characteristics were tested using logistic regression. Over the three surveys, the proportion of respondents who believed antibiotics would "definitely/probably" help an ILI fell from 37% (95% CI 35-39%) to 28% (95% CI 26-29%). Those who would "definitely/probably" visit a doctor in this situation fell from 48% (95% CI 46-50%) to 36% (95% CI 34-37%), while those who would request antibiotics during a consultation fell from 39% (95% CI 37-41%) to 30% (95% CI 29-32%). The percentage of respondents who found the information we provided about AMR "new/surprising" fell from 34% (95% CI 32-36%) to 28% (95% CI 26-31%). Awareness improved more among black, Asian and minority ethnic (BAME) than white people, with little other evidence of differences in Antibiotics 2020, 9, 690 2 of 16 improvements between subgroups. Whilst a degree of selection bias is unavoidable in online survey samples, the results suggest that awareness of AMR and appropriate antibiotic use has recently significantly improved in the United Kingdom, according to a wide range of indicators.
... Most studies assessing antibiotic prescribing do not take into account these patient characteristics which may justify prescription of antibiotics for certain indications [4,5]. An exception is a study by Hope et al. who found that almost 20% of practices among a group of high antibiotic prescribers would not have been classified as high prescribers when taking comorbidity into account [6]. Another exception is the study of Dekker et al. who took into account age, gender, general health state and comorbidity [7]. ...
... In the current study we assessed for each studied episode of RTIs whether, according to the guidelines, antibiotics could be considered or not. A previous study by Hope et al. showed the importance of taking into account factors such as comorbidity, like we did in the current study, to determine guideline adherence [6]. The high percentage of antibiotic prescribing in episodes for which we could not find an indication for antibiotics suggests that guideline adherence can be improved. ...
Respiratory tract infections (RTIs) account for a large part of antibiotic prescriptions in primary care. However, guidelines advise restrictive antibiotic prescribing for RTIs. Only in certain circumstances, depending on, e.g., comorbidity, are antibiotics indicated. Most studies on guideline adherence do not account for this. We aimed to assess guideline adherence for antibiotic prescribing for RTIs as well as its variation between general practices (GPs), accounting for patient characteristics. We used data from electronic health records of GPs in the Netherlands. We selected patients who consulted their GP for acute cough, rhinitis, rhinosinusitis or sore throat in 2014. For each disease episode we assessed whether, according to the GP guideline, there was an indication for antibiotics, using the patient's sociodemographic characteristics, comorbidity and co-medication. We assessed antibiotic prescribing for episodes with no or an unsure indication according to the guidelines. We analysed 248,896 episodes. Diagnoses with high rates of antibiotic prescribing when there was no indication include acute tonsillitis (57%), strep throat (56%), acute bronchitis (51%) and acute sinusitis (48%). Prescribing rates vary greatly between diagnoses and practices. Reduction of inappropriate antibiotic prescribing remains a key target to tackle antimicrobial resistance. Insight into reasons for guideline non-adherence may guide successful implementation of the variety of interventions already available for GPs and patients.
... 6 The prevalence of comorbidities such as diabetes varies over time and geographical area, contributing to the disparities in the antibiotic prescribing pattern within and between primary care practices. 7,8 Several approaches have been adopted to reduce primary care antibiotic prescribing in England including: increased surveillance and prescribing feedback; the provision of C-reactive protein pointof-care testing; education and training interventions targeted at prescribers and patients; public antimicrobial stewardship (AMS) campaigns; and financial incentives. 9,10 The QP is an NHS England performance-related incentive scheme established in 2013 to reward CCGs financially, based on the quality of specific health services considered to be national or local priorities and commissioned over a specific period. ...
Background:
In 2017, approximately 73% of antibiotics in England were prescribed from primary care practices. It has been estimated that 9%-23% of antibiotic prescriptions between 2013 and 2015 were inappropriate. Reducing antibiotic prescribing in primary care was included as one of the national priorities in a financial incentive scheme in 2015-2016.
Aim:
To investigate whether the effects of the Quality Premium (QP), which provided performance-related financial incentives to clinical commissioning groups (CCGs), could be explained by practice characteristics that contribute to variations in antibiotic prescribing.
Design & setting:
Longitudinal monthly prescribing data were analysed for 6251 primary care practices in England from April 2014 to March 2016.
Method:
Linear generalised estimating equations models were fitted, examining the effect of the 2015-2016 QP on the number of antibiotic items per specific therapeutic group age-sex related prescribing unit (STAR-PU) prescribed, adjusting for seasonality and months since implementation. Consistency of effects after further adjustment for variations in practice characteristics were also examined, including practice workforce, comorbidities prevalence, prescribing rates of non-antibiotic drugs, and deprivation.
Results:
Antibiotics prescribed in primary care practices in England reduced by -0.172 items per STAR-PU (95% confidence interval [CI] = -0.180 to -0.171) after 2015-2016 QP implementation, with slight increases in the months following April 2015 (+0.014 items per STAR-PU; 95% CI = +0.013 to +0.014). Adjusting the model for practice characteristics, the immediate and month-on-month effects following implementation remained consistent, with slight attenuation in immediate reduction from -0.172 to -0.166 items per STAR-PU. In subgroup analysis, the QP effect was significantly greater among the top 20% prescribing practices (interaction p<0.001). Practices with low workforce and those with higher diabetes prevalence had greater reductions in prescribing following 2015-2016 QP compared with other practices (interaction p<0.001).
Conclusion:
In high-prescribing practices, those with low workforce and high diabetes prevalence had more reduction following the QP compared with other practices, highlighting the need for targeted support of these practices and appropriate resourcing of primary care.
