Abstract
Objective
To determine differences in antibiotic prescription rates between conventional General Practice (GP) surgeries and GP surgeries employing general practitioners (GPs) additionally trained in integrative medicine (IM) or complementary and alternative medicine (CAM) (referred to as IM GPs) working within National Health Service (NHS) England.
Design
Retrospective study on antibiotic prescription rates per STAR-PU (Specific Therapeutic group Age–sex weighting Related Prescribing Unit) using NHS Digital data over 2016. Publicly available data were used on prevalence of relevant comorbidities, demographics of patient populations and deprivation scores.
Setting
Primary Care.
Participants
7283 NHS GP surgeries in England.
Primary outcome measure
The association between IM GPs and antibiotic prescribing rates per STAR-PU with the number of antibiotic prescriptions (total, and for respiratory tract infection (RTI) and urinary tract infection (UTI) separately) as outcome.
Results
IM GP surgeries (n=9) were comparable to conventional GP surgeries in terms of list sizes, demographics, deprivation scores and comorbidity prevalence. Negative binomial regression models showed that statistically significant fewer total antibiotics (relative risk (RR) 0.78, 95% CI 0.64 to 0.97) and RTI antibiotics (RR 0.74, 95% CI 0.59 to 0.94) were prescribed at NHS IM GP surgeries compared with conventional NHS GP surgeries. In contrast, the number of antibiotics prescribed for UTI were similar between both practices.
Conclusion
NHS England GP surgeries employing GPs additionally trained in IM/CAM have lower antibiotic prescribing rates. Accessibility of IM/CAM within NHS England primary care is limited. Main study limitation is the lack of consultation data. Future research should include the differences in consultation behaviour of patients self-selecting to consult an IM GP or conventional surgery, and its effect on antibiotic prescription. Additional treatment strategies for common primary care infections used by IM GPs should be explored to see if they could be used to assist in the fight against antimicrobial resistance.
Keywords: antimicrobial resistance, complementary medicine, integrative medicine, antibiotic prescription rate
Strengths and limitations of this study.
Use of National Health Service (NHS) Digital data on antibiotic prescription per Specific Therapeutic group Age–sex weighting Related Prescribing Unit (STAR-PU) provided a comprehensive insight into the prescribing practices of total antibiotics, and for respiratory tract infection and urinary tract infection separately in conventional General Practice (GP) surgeries and GP surgeries employing general practitioners (GPs) additionally trained in integrative medicine (IM GPs).
NHS England IM GP surgeries were comparable to conventional GP surgeries in terms of list sizes, demographics, deprivation scores and comorbidity prevalence.
Accessibility of IM/complementary and alternative medicine (CAM) within the NHS in General Practice in England is very limited. IM/CAM provision is currently almost exclusively private in the UK.
Results are limited by the lack of data on (1) number of consultations, (2) individual GP characteristics, (3) individual deprivation scores and (4) continuum of care.
Introduction
Antimicrobial resistance (AMR) and the inappropriate use of antibiotics represent a serious threat to public health internationally.1 Antibiotics are currently indispensable throughout the healthcare system, and the consequences of AMR, not only in primary care, but also in major surgery and cancer treatment for example, are dire. Fortunately, reductions in antibiotic use have been shown to be associated with a reduction in some resistance,2 and the reduction in the use of antibiotics, especially in primary care, to control the development of AMR is therefore a pressing national and international priority.1 3
In the UK, 74% of antibiotics are prescribed in primary care making this one of the most important contributors to the development of AMR.4 National Institute for Health and Care Excellence (NICE) guidelines on respiratory tract infection5 (RTI) management advise that a non-antibiotic prescribing strategy or a delayed antibiotic prescribing strategy should be considered for patients with the following conditions: acute otitis media, acute sore throat/acute pharyngitis/acute tonsillitis, common cold, acute rhinosinusitis and acute cough/acute bronchitis. Nevertheless, antibiotics are commonly prescribed for RTIs in adults and children in primary care, and are the reason for 60% of all antibiotic prescribing in general practice in the UK.6 Several studies have shown that there is substantial overprescribing of antibiotics for, often viral and self-limiting, RTIs in primary care.7–9 Consequently, there is a large potential to reduce antibiotic prescribing for RTIs, potentially by using other treatment strategies that do not increase the development or spread of AMR. Urinary tract infections (UTIs) are the most common confirmed bacterial infection, with about half of all women experiencing one of more UTIs in their lifetime.10 Most women with UTIs are currently treated with antibiotics, with longer duration and multiple courses associated with higher AMR rates.11 12 For example, NICE guideline on uncomplicated UTIs in women advise offering symptom relief and an antibiotic to all women with a suspected UTI. It states that for a woman with mild symptoms who has normal immunity, normal renal function and a normal renal tract, treatment can be delayed if the patient wishes to see if symptoms will resolve without treatment. For all other women treatment needs to start without delay.13 Therefore, overprescribing seems to be much less common for UTIs than for RTIs.14 Consequently, it may be easier to safely reduce antibiotic prescribing for RTIs than for UTIs in primary care.
There is great variability in the use of antimicrobial medications between countries, with the lowest prescription rates reported in northern European nations, and higher rates in southern Europe and the USA.15–17 Variations in the prescription of antibiotics both within and between countries may indicate poor practice18 with inappropriate use of antibiotics which increases the risk of adverse events for the patient,12 wastes healthcare resources19 and contributes to the rise in antibiotic resistance.16 Previous studies have shown that a complex array of factors influence antibiotic prescribing, which may explain the wide variety of antibiotic usage both at the clinician level and worldwide. The attitudes of both doctor20–22 and patient23–25 are shown to be of major significance in prescribing decisions.
General practitioners (GPs) as a professional group are expected, following the principles of evidence-based medicine, to apply best available evidence to patient’s individual situation, within the framework of national and local funding and administrative guidance. Prescription style (measured as the prevalence of prescriptions per GP) is found to be an important factor in the variation in antibiotic prescribing behaviour.18 Underlying factors for this finding might be differing views on medicalisation, differences in guidelines between countries and between specialists and knowledge and use of complementary and alternative medicine (CAM)/integrative medicine (IM).26–28 The association between the knowledge/use of IM/CAM by GPs and antibiotic prescribing has so far not been widely scrutinised.
The aim of this study is to determine the differences in antibiotic prescription rates between ‘conventional General Practice (GP) surgeries and GP surgeries employing GPs additionally trained in IM/CAM (hereafter referred to as integrative medicine (IM) GPs), and the association between having staff with an additional training in IM/CAM and antibiotic prescription (measured as total antibiotics, RTI-specific antibiotics and UTI-specific antibiotics) within the National Health Service (NHS) in England.
Methods
IM GP surgeries
To identify NHS General Practices employing an IM GP in 2016, two sequential tasks were required. First, IM GPs were identified and then a current working link was made to an NHS General Practice.
Identification of NHS GPs registered with an additional CAM qualification
We included the ‘Big 5’ CAM therapies as defined in a report by the House of Lords in 200029 (chiropractic, osteopathy, acupuncture, herbal medicine and homoeopathy); as well as Anthroposophic Medicine (AM). AM is an extension of conventional medicine and incorporates a holistic approach to people and nature and to illness and healing and is established in 80 countries, mostly in Central Europe.30 AM has been included so that future comparison with data in other European countries is possible.
In the UK each of these six therapies is either state regulated (osteopathy and chiropractic) or has voluntary regulation (including a voluntary regulatory body for mainstream healthcare practitioners in the case of acupuncture and homoeopathy). The regulatory bodies were therefore initially approached by email to check the best route of establishing which practitioners on their registers were trained as a conventional GP and trained in IM/CAM as well. Details of the organisations and methods by which IM GPs were identified are indicated in table 1. Where organisations were not able to provide this information, searches were made of the online registers (between May and June 2017) for the following:
Table 1.
IM/CAM specialism | Organisation | Website | Method for extracting General Practice (GP) information |
Osteopathy | General Osteopathic Council | www.osteopathy.org.uk | Search of online database |
Chiropractic | General Chiropractic Council (GCC) | www.gcc-uk.org | GCC staff identified GP registrants |
Acupuncture | British Medical Acupuncture Council | www.medical-acupuncture.co.uk | Search of online database |
Herbal medicine | College of Practitioners of Phytotherapy (CPP) | www.thecpp.uk | CPP staff identified GP registrants |
National Institute of Medical Herbalists (NIMH) | www.nimh.org.uk | NIMH staff identified GP registrants | |
The Register of Chinese Herbal Medicine in the UK | www.rchm.co.uk | Search of online database | |
The United Register of Herbal Practitioners | www.urhp.com | Search of online database | |
The Association of Traditional Chinese Medicine and Acupuncture UK | www.atcm.co.uk | Search of online database | |
Homeopathy | British Homeopathic Association | www.britishhomeopathic.org | Search of online database |
Faculty of Homeopathy | www.facultyofhomeopathy.org | Search of online database | |
Anthroposophic medicine | Anthroposophic Health, Education and Social Care Movement | www.ahasc.org.uk | Search of online database |
Location: the registers enabled us to search for practitioners either on a nationwide (England/UK) basis or by county (in the latter case, all English counties were checked, including recent boundary changes).
Qualification: in some databases, only healthcare professionals (eg, practitioners qualified in biomedicine) were included, and GP status was specified. Where this was not the case, titles were given and the absence of the title ‘Dr’ was used to exclude practitioners from our study. Where qualifications were also identified, practitioners with PhDs but not being a GP could be excluded. And if no additional information was given on the register, online searches were made of the practitioner to establish their professional qualifications. In all cases, putative IM GPs were checked against the General Medical Council (GMC) register, to confirm whether they were currently permitted to work in medical practice in the UK.
Identification of NHS General Practices employing IM GPs
Practice location(s) were indicated for each GP registrant identified in the CAM registers indicated in table 1. These workplaces were then checked against both the practice websites and the NHS website (www.nhs.uk), which lists all NHS practices and gives information such as staff lists. This acted to confirm the working location of the GP and whether this practice offered provision within NHS England.
Data
Monthly prescribing data were obtained from NHS Digital. NHS Digital collect data and information about a wide range of General Practice (GP) services, for many different organisations and purposes. It also collates all primary care prescribing data. These data are released for monthly download via the NHS Digital website (http://digital.nhs.uk/searchcatalogue). Data are released at the specific healthcare provider level and volumes are provided by full British National Formulation code (BNF code). To determine mean antibiotic prescription rates, we used the total number of oral antibiotic prescriptions per general practice for the most recent calendar year for which antibiotic prescribing was publicly available via the NHS Digital website (January 2016 to December 2016).
Specific Therapeutic group Age–sex weighting Related Prescribing Units
Specific Therapeutic group Age–sex weighting Related Prescribing Units (STAR-PUs) have been used as the denominator instead of the number of registered patients as STAR-PUs allow more accurate and meaningful comparisons within a specific therapeutic group by considering the types of people who will be receiving that treatment. The amount of STAR-PU per practice was estimated by multiplying the number of patients in each age–gender category.31
Comorbidities
The prevalence of various comorbidities that may adversely influence the outcome of infections, based on the conditions that indicate high-risk patients who qualify for the free seasonal influenza vaccination programme,32 was also measured to identify potential case-mix differences that may explain different antibiotic prescribing rates. General practice-specific prevalence is available for the following high-risk comorbidities via the Quality Outcomes Framework indicators at the NHS Digital website: asthma, cancer, chronic kidney disease, chronic obstructive pulmonary disease, heart failure and diabetes. We extracted comorbidity prevalence for the financial year 2015–2016.
Indices of multiple deprivation
Previously it has been shown that indices of multiple deprivation are indicators of poor health in a population. Tosas Auguet et al33 for example, found that more deprived areas are at higher risk of methicillin-resistant Staphylococcus aureus infection. The most recent index of multiple deprivation was calculated in 2015 and is available from the Department for Communities and Local Government.34 Deprivation scores are available at a lower-layer super output area (LSOA), which consists of approximately 1500 residents each. Linkage of the data from NHS Digital was performed using a lookup table from NHS Digital. Where a practice served multiple LSOAs, the average deprivation score for that practice was calculated, weighted by the number of patients in each LSOA.
The final dataset included only practices that were present in both the comorbidity and deprivation, and antibiotic prescribing files. We removed outliers based on practice size, since there were some doubts about the validity of these data (eg, a practice with 157 patients registered). We removed the outer 2% of data based on practice size.
Statistical analysis
All analyses are performed on GP surgery level (hereafter referred to as GPs). Potential differences in antibiotic prescribing rates per STAR-PU between the IM and conventional GPs were evaluated. NHS Digital defines a prescription item as: ‘a prescription item is a single supply of a medicine, dressing or appliance written on a prescription form’. If a prescription form includes three medicines, it is counted as three prescription items. We tested for between group differences using a random effects meta-analysis model for proportions (R package ‘meta’). For continuous variables like the number of STAR-PU per practices Mann-Whitney U tests were used to test for statistically significant differences.
The association between the IM GPs and antibiotic prescribing rates per STAR-PU was assessed using negative binomial regression models with the number of antibiotic prescriptions as the outcome and the natural logarithm of the number of STAR-PU per practice as an offset. A negative binomial regression model was used as this type of regression model can handle count data (number of antibiotic prescriptions), accounts for differences in the number of antibiotics purely caused by practice size (by including the offset) and can still provide valid results when the variance in antibiotic use does not equal the mean antibiotic use.35 Both crude results and results adjusted for additional variables to correct for potential confounding are presented.
We additionally evaluated associations between IM GPs and antibiotics commonly used for RTI (amoxicillin, amoxicillin and enzyme inhibitor, ampicillin, clarithromycin, doxycycline, erythromycin and phenoxymethylpenicillin) and for UTI (cephalexin, cefixime, ciprofloxacin, nitrofurantoin, pivmecillinam and trimethoprim).36
Results
Identification of NHS IM GPs in England
Eight hundred and fifty CAM practitioner records were checked against the various CAM registers (table 1) to identify 21 GPs who are conventionally trained as a GP and also trained in CAM at 19 NHS GP surgeries in England (table 2). It should be noted that the 850 registrants were not the total numbers of CAM practitioners on the registers, as (as previously described) some registers permitted limiting searches to medical practitioners, or more specifically to medically qualified doctors.
Table 2.
Apparent level of IM/complementary and alternative medicine (CAM) practice | IM/CAM registration (n) | |
Subset 1 (n=9) |
General Practices where an IM approach is taken with IM/CAM-trained GP (n=4) | Homeopathy (1) Anthroposophic medicine (4) Acupuncture (1) |
General practices listing IM/CAM therapy provision with CAM-trained GP (n=5) | Homeopathy (1) Acupuncture (4) |
|
Subset 2 (n=10) |
General practices mention a IM/CAM therapy in the listing of the special interests of the GP, but no other information is given and it is unclear whether the GP practises this IM/CAM therapy at that site |
While some practices were publicly working in an IM structure, in others it was unknown whether the identified GP was using IM/CAM or indeed whether or the practice permitted this, as no mention was made of it on the websites (including no reference to privately available CAM clinics). General Practices were therefore classified into two subsets as indicated in table 2. There were further IM GPs on the register who were either not practising (or at least not in England), or working in private practice. As any level of IM/CAM activity in subset 2 practices could not be determined, it was decided to exclude these GP surgeries from further analysis. Nine NHS IM GP surgeries (urban (n=6), semiurban (n=2) and semirural (n=1)) were included in the analysis. table 2 also shows the CAM therapies for which each IM GP in our subsequent analysis was registered. Each practice included has at least one IM GP, as GP partner or salaried. The number of IM GPs per practice varies from a minimum of 1 IM GP in a practice with 12 GPs of whom 6 part time, to a maximum of 3 IM GPs (all GP practice partners) in a practice with 7 GPs (two full-time GPs and five part time GPs).
Antibiotic prescription rates
In total 7283 NHS England General Practices (N_conventional=7274/N_IMGPs=9) were included in the analyses. Table 3 presents the baseline characteristic of the NHS IM GP surgeries compared with those characteristic of NHS conventional GPs in England. It also shows the prevalence of various comorbidities that may adversely influence the outcome of infections and may consequently influence antibiotic prescribing. The patient populations of both kinds of practices were comparable for most of the listed comorbidities. Statistically significant differences (P<0.05) between the IM GP- and conventional GP surgery patient population were found in the percentage of patients with coronary heart disease, cancer and diabetes, although absolute differences were relatively small. No statistical differences (P<0.05) were found in deprivation score between IM GP surgeries and conventional GP surgeries.
Table 3.
Conventional GP surgery, median (25th–75th percentile), n=7274 | IM/CAM GP surgery (subset 1),† median (25th–75th percentile), n=9 | |
Number of registered patients | 6698 (4162–9942) | 7088 (4037–9534) |
Male (%) | 49.7 (48.8–50.9) | 49.3 (46.9–49.4) |
Aged 0–17 years (%) | 20.5 (18.5–23.0) | 21.2 (18.7–22.0) |
Aged 18–64 years (%) | 61.2 (58.7–64.2) | 61.9 (60.3–62.4) |
Aged 65+ years (%) | 17.2 (12.3–21.4) | 18.2 (14.0–18.4) |
STAR-PU‡ | 3705 (2276–5599) | 3716 (2315–5382) |
Coronary heart disease (%) | 3.3 (2.5–4.0) | 2.8 (2.1–3.1)* |
Heart failure (%) | 0.7 (0.5–0.9) | 0.5 (0.4–0.8) |
Asthma (%) | 6.0 (4.9–6.7) | 5.1 (4.8–6.2) |
COPD (%) | 1.8 (1.3–2.4) | 1.0 (0.8–2.0) |
Cancer (%) | 2.4 (1.7–3.0) | 2.5 (2.2–2.9)* |
Chronic kidney disease (%) | 3.0 (2.0–4.1) | 1.9 (1.2–2.9) |
Diabetes (%) | 5.4 (4.5–6.2) | 3.9 (2.9–4.6)* |
Deprivation score | 0.27 (0.11–0.63) | 0.36 (0.15–0.48) |
*P<0.05.
†Subset 1: General Practices where an integrative medicine approach is taken with IM/CAM-trained General practitioners (GPs) (n=4) and General Practices listing IM/CAM therapy provision with IM/CAM-trained GP (n=5).
‡Oral antibacterial item-based STAR-PUs. The amount of STAR-PU per practice was estimated by multiplying the number of patients in each age–gender category by the relevant STAR-PU weights (see the Methods section for detailed explanation on STAR-PUs).
COPD, chronic obstructive pulmonary disease; NHS, National Health Service; STAR-PU, Specific Therapeutic Group Age–sex weightings Related Prescribing Unit.
IM GP surgeries and antibiotic prescription rates
Overall within the NHS in England, the median prescription rates of IM GP surgeries were lower for ‘any antibiotic’ and for ‘RTI-specific antibiotic’ compared with the rates of the conventional GP surgeries over 2016, while the median prescription rates of ‘UTI-specific antibiotic’ per STAR-PU were comparable for the two groups (table 4).
Table 4.
Any antibiotic/STAR-PU,† median (25th–75th percentile) | RTI antibiotic/STAR-PU,† median (25th –75th percentile) | UTI antibiotic/STAR-PU,† median (25th–75th percentile) | |
Conventional General Practice (GP) surgeries (n=7274) | 1.01 (0.86–1.17) | 0.56 (0.46–0.67) | 0.22 (0.17–0.26) |
IM GP surgeries with IM/CAM-trained GP (n=9) | 0.79 (0.73–0.91)* | 0.44 (0.37–0.48)* | 0.21 (0.19–0.23) |
RR,† (95% CI) | RR,† (95% CI) | RR,† (95% CI) | |
Conventional GP surgeries (n=7274) | Ref. | Ref. | Ref. |
IM GP surgeries with IM/CAM-trained GP (n=9) | 0.78 (0.64 to 0.97)* | 0.74 (0.59 to 0.94)* | 0.91 (0.72 to 1.17) |
*P<0.05.
†This rate is obtained by dividing the total number of antibiotics prescribed by the number of STAR-PU registered.
RR, relative risk; RTI, respiratory tract infection; STAR-PU, Specific Therapeutic Group Age–sex weightings Related Prescribing Unit; UTI, urinary tract infection.
The relative risks (RRs) in table 4 were obtained using negative binomial regression models with the number of antibiotic prescriptions as the outcome and taking into account differences in practice sizes. Our analysis shows that IM GP surgeries were associated with lower prescriptions of ‘any antibiotic’ (RR 0.78, 95% CI 0.64 to 0.97) and with lower prescriptions of ‘RTI-specific antibiotic’ (RR 0.74, 95% CI 0.59 to 0.94*). Patients consulting an IM GP surgery were 22% less likely to get ‘any antibiotic’ prescription compared with those who consulted a conventional GP surgery. Receiving a RTI-specific antibiotic prescription was 26% less likely among those who consulted an IM GP surgery compared with those who consulted a conventional GP surgery. No statistically significant difference (P<0.05) was found in the number of prescriptions of UTI-specific antibiotic prescriptions per STAR-PU between IM GP surgeries and conventional GP surgeries within the NHS in England.
Adjustment for deprivation score or diabetes resulted in virtually identical results. For ‘any antibiotic’ if adjusted for deprivation score the RR for IM GP surgeries remains virtually identical (RR 0.78, 95% CI 0.64 to 0.97), and for diabetes (RR 0.80, 95% CI 0.65 to 0.99). This was the case regardless of which confounder was added to the model, however adjusting for multiple potential confounders was not possible due to the small number of cases.
Discussion
There were 7283 NHS England General Practices included in our analyses. Despite the very small proportion of IM GP surgeries, our data show that significantly fewer ‘total antibiotics’ and ‘RTI-specific antibiotics’ per STAR-PU were prescribed at IM GP surgeries compared with conventional GP surgeries within NHS England over 2016. No statistically significant differences were found in median prescription rates of ‘UTI-specific antibiotics’ per STAR-PU in the two kinds of NHS GP surgeries.
This is the first (retrospective) study comparing antibiotic prescribing rates between IM GP surgeries and conventional GP surgeries in England. However, the small proportion of NHS IM GPs in England asks for careful interpretation of the results. Accounting for one other variable (eg, deprivation or diabetes) did not change our results, but, due to the low number of cases it was not possible to similarly account for more variables.
Lack of information on the number of consultations is the main limitation of this study. Consultation rates may explain most of the variation in antibiotic prescribing, and with the data used in this study, it is not clear whether patients consulting at IM GP surgeries consulted less in general. If this were the case, they may be equally likely to receive antibiotics when they do consult their GP. Besides, previous studies show that the consultation rate is also dependent on the previous likelihood to receive antibiotics for a RTI.37–39 Future studies should therefore include consultation behaviour/number of consultations as a confounding factor.
Other study limitations that need to be taken into account when interpreting the results are the lack of information on (1) individual deprivation scores, (2) individual GP characteristics and (3) continuum of care. First, no statistically significant differences were found in deprivation score on practice level. However, this may be partly because deprivation scores are area based and not based on the individuals registered at the different practices. Second, our analyses are at GP practice level and include information on GP practice characteristics, such as list size and population. Data on GP characteristics on individual level are not part of NHS Digital data and are therefore not included in our analysis. However, these GP characteristics may partly explain the variation in antibiotic prescribing.40–42 Finally, the data used for our analysis are based on the number of antibiotic ‘prescriptions’, which may differ from the numbers of antibiotics ‘consumed’, and do not include information on the continuum of care of patients (eg, hospital admissions/reconsultation). Future studies using clinical practice data taking continuum of care into account are warranted.
The lower antibiotic prescription rates of IM GPs are in line with the current national guidance aimed at reducing antibiotic usage and AMR.1 IM GPs might possible comply more closely with this guidance. However, the difference found could also be partly explained by the fact that patients who consult IM GPs might demand less for antibiotics, and that GPs in IM surgeries have other avenues to offer to patients than antibiotics or that they are more confident to delay prescriptions and to assert themselves against the wishes of those patients who appear to want antibiotics. Our results are in line with a yet unpublished pilot study in The Netherlands in which the prescription of antimicrobials for systemic use in 23 unselected anthroposophic GP surgeries was compared with the national mean GP figures for the years 2012–2014. On average AM GPs in the Netherlands prescribed less antimicrobials: −13% (2012), –10% (2013) and −7% (2014) (unpublished data).
Despite the differences we found in RTI antibiotics, no statistically significant differences were found in UTI antibiotics prescription rates between the two kinds of NHS GP surgeries. Although it should be borne in mind that the use of prescribing data to infer the type of infection may be prone to errors, our finding reflects current UK GP clinical guidance.
For the majority of RTIs it is recommended that antibiotics should be avoided or delayed, so that this is an area where the desired reduction in prescribing could take place. In the case of UTIs, antibiotics are advised more readily.36 For several RTIs, including common colds, sore throat, sinusitis and acute bronchitis, randomised controlled trials (RCTs) have shown that antibiotics provide no, or negligible benefit compared with placebo.43–46 As such, symptom management with paracetamol, ibuprofen or the use of CAM therapies proven to be effective and safe for RTIs may safely reduce antibiotic prescribing among patients with a low risk for pneumonia. A recent RCT comparing ibuprofen with fosfomycin treatment for UTIs indicates that it may be more difficult to safely reduce antibiotic prescribing for UTIs using a similar approach.47
Our study shows that accessibility of IM/CAM within the NHS in General Practice is very limited, and this limited the number of IM GPs included in our analysis. IM/CAM provision is currently almost exclusively privately provided in the UK, which could be at least partly linked to the austerity measures currently imposed in the UK possibly resulting in NHS IM/CAM provision being withdrawn at a local level in recent years (and imminently nationally). It was seen on practice websites that there was a noticeable amount of ‘private’ CAM provision available at several NHS surgeries by non-GP CAM practitioners—in weekly clinics for example. However, these surgeries have not been included in our analysis as this study specifically aimed to determine the differences in antibiotic prescribing between conventional GP surgeries and GP surgeries staffing GPs who were additionally trained in IM/CAM.
Attitudes of GPs to IM/CAM are extremely important for it to remain available within the NHS. A 2015 study of these attitudes in England, showed that, despite demand for CAM among the general public, GPs remain concerned about its limited evidence base as well as the lack of regulation of CAM practitioners. Nevertheless, those questioned continue to see a role for CAM in clinical practice.48
In our study each of the NHS IM GP practices included at least 1 IM GP. However, as the number of (IM) GP partners and salaried (IM) GPs (full time and part time) in these practices varies, proportions of the number of IM GPs per included NHS IM GP surgery are difficult to determine and in addition, will not provide meaningful information as they do not take into account the power balance of the different GPs within these practices.
The impact which any one IM GP could have in terms of antibiotic prescribing may vary hugely between practices partly depending on their status at the practice—as a partner or a salaried employee for example, or as a full-time or part time worker. In the presented analysis we did not include NHS GP practices that are offering NHS IM/CAM provision by a ‘non-GP NHS CAM practitioner’ or private IM/CAM practitioner. However, having even one CAM contact within a surgery might give the possibility for others to experience CAM perspectives either formally or informally from them, and for long-held attitudes to be perhaps modified. Additionally, it would be of interest to explore if patients may be independently accessing IM GPs in the private sector and then seeking antibiotics from non-IM GPs in the NHS.
In line with Hawker et al49 our results suggest that a further decrease in prescribing in conventional surgeries might be possible. It may be that advice should be sought from this small number of surgeries to establish whether their daily clinical practice may differ from other surgeries and whether this could be used to assist others in the fight against AMR.
Although this study found only a small number of CAM practitioners working at NHS General Practices in England, the difference seen in antibiotic prescribing rates at IM GP surgeries warrants further study. It is very likely that, due to similarity in healthcare system (NHS) and the number of NHS IM GPs and—surgeries, our findings are generalisable to Scotland, Wales and Northern Ireland. However, differences in healthcare systems and the general level of IM practice may lead to other results in other (European) countries. Therefore, analysis in comparison with other (European) countries are indicated to prove whether in general IM GP (surgeries) tend to prescribe less antibiotics or whether other (socioeconomic) factors dominate the prescription rate for specific infections.
As the clear majority of CAM practitioners (mainly non-GPs) work privately in England, there is also potential for research into non-antibiotic strategies in private practice, and to analysis of how these practitioners work with their patients’ NHS GPs in this regard. However, as patients who self-select to consult IM GPs might be less likely to demand antibiotics, differences in lifestyle and the ‘transferability of lifestyle skills’ need to be taken into account as well in future study design.
Supplementary Material
Acknowledgments
The authors gratefully acknowledge the statistical support of Dr Koen Pouwels (Senior Mathematical/Economic Modeller).
Footnotes
Contributors: Substantial contributions to the conception and design of the work: ETvdW/LJD/PvF/EWB. Acquisition, analysis or interpretation of data for the work: ETvdW/LJD. Drafting the work and revising it critically for important intellectual content: ETvdW/LJD/PvF/EWB. Final approval of the version to be published: ETvdW/LJD/PvF/EWB. Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved: ETvdW/LJD/PvF/EWB.
Funding: This research was supported in part by an unrestricted grant of WALA Heilmittel GmbH, Germany.
Competing interests: None declared.
Patient consent: Not required.
Provenance and peer review: Not commissioned; externally peer reviewed.
Data sharing statement: Data are available through NHS digital.
References
- 1.Public Health England. English surveillance programme for antimicrobial utilisation and resistance (ESPAUR). 2016. https://phe-newsroom.prgloo.com/resources/espaur-report-2016
- 2.Butler CC, Dunstan F, Heginbothom M, et al. Containing antibiotic resistance: decreased antibiotic-resistant coliform urinary tract infections with reduction in antibiotic prescribing by general practices. Br J Gen Pract 2007;57:785–92. [PMC free article] [PubMed] [Google Scholar]
- 3.Laxminarayan R, Duse A, Wattal C, et al. Antibiotic resistance-the need for global solutions. Lancet Infect Dis 2013;13:1057–98. 10.1016/S1473-3099(13)70318-9 [DOI] [PubMed] [Google Scholar]
- 4.Public Health England. English surveillance programme for antimicrobial utilisation and resistance (ESPAUR. London: Public Health England, 2016. [Google Scholar]
- 5.NICE. Respiratory tract infections: prescribing of antibiotics for self-limiting respiratory tract infections in adults and children in primary care, 2008. [PubMed] [Google Scholar]
- 6.Lindbaek M. Prescribing antibiotics to patients with acute cough and otitis media. Br J Gen Pract 2006;56:164-6. [PMC free article] [PubMed] [Google Scholar]
- 7.Dekker AR, Verheij TJ, van der Velden AW. Inappropriate antibiotic prescription for respiratory tract indications: most prominent in adult patients. Fam Pract 2015;32:401–7. 10.1093/fampra/cmv019 [DOI] [PubMed] [Google Scholar]
- 8.Fleming-Dutra KE, Hersh AL, Shapiro DJ, et al. Prevalence of inappropriate antibiotic prescriptions among us ambulatory care visits, 2010-2011. JAMA 2016;315:1864–73. 10.1001/jama.2016.4151 [DOI] [PubMed] [Google Scholar]
- 9.Flöistrup H, SWARTZ J, BERGSTROM A, et al. Allergic disease and sensitization in Steiner school children. J Allergy Clin Immunol 2006;117:59–66. 10.1016/j.jaci.2005.09.039 [DOI] [PubMed] [Google Scholar]
- 10.Foxman B. Epidemiology of urinary tract infections: incidence, morbidity, and economic costs. Dis Mon 2003;49:53–70. 10.1067/mda.2003.7 [DOI] [PubMed] [Google Scholar]
- 11.Bryce A, Hay AD, Lane IF, et al. Global prevalence of antibiotic resistance in paediatric urinary tract infections caused by Escherichia coli and association with routine use of antibiotics in primary care: systematic review and meta-analysis. BMJ 2016;352:i939. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Costelloe C, Metcalfe C, Lovering A, et al. Effect of antibiotic prescribing in primary care on antimicrobial resistance in individual patients: systematic review and meta-analysis. BMJ 2010;340:c2096 10.1136/bmj.c2096 [DOI] [PubMed] [Google Scholar]
- 13.NICE. Urinary tract infection (lower) - women - summary. Clinical knowledge summaries, 2015. [Google Scholar]
- 14.Public health England. Management and treatment of common infections. Antibiotic guidance for primary care: for consultation and local adaptation, 2017. [Google Scholar]
- 15.Goossens H, Ferech M, Vander Stichele R, et al. Outpatient antibiotic use in Europe and association with resistance: a cross-national database study. Lancet 2005;365:9–587. 10.1016/S0140-6736(05)70799-6 [DOI] [PubMed] [Google Scholar]
- 16.Goossens H. Antibiotic consumption and link to resistance. Clin Microbiol Infect 2009;15(Suppl 3):12–15. 10.1111/j.1469-0691.2009.02725.x [DOI] [PubMed] [Google Scholar]
- 17.Goossens H, Ferech M, Coenen S, et al. Comparison of outpatient systemic antibacterial use in 2004 in the United States and 27 European countries. Clin Infect Dis 2007;44:1091–5. 10.1086/512810 [DOI] [PubMed] [Google Scholar]
- 18.Cordoba G, Siersma V, Lopez-Valcarcel B, et al. Prescribing style and variation in antibiotic prescriptions for sore throat: cross-sectional study across six countries. BMC Fam Pract 2015;16:7 10.1186/s12875-015-0224-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Sirovich B, Gallagher PM, Wennberg DE, et al. Discretionary decision making by primary care physicians and the cost of U.S. Health care. Health Aff 2008;27:11 10.1377/hlthaff.27.3.813 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Carthy P, Harvey I, Brawn R, et al. A study of factors associated with cost and variation in prescribing among GPs. Fam Pract 2000;17:36–41. 10.1093/fampra/17.1.36 [DOI] [PubMed] [Google Scholar]
- 21.Teixeira Rodrigues A, Ferreira M, Roque F, et al. Physicians' attitudes and knowledge concerning antibiotic prescription and resistance: questionnaire development and reliability. BMC Infect Dis 2016;16:7 10.1186/s12879-015-1332-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Teixeira Rodrigues A, Roque F, Falcão A, et al. Understanding physician antibiotic prescribing behaviour: a systematic review of qualitative studies. Int J Antimicrob Agents 2013;41:203–12. 10.1016/j.ijantimicag.2012.09.003 [DOI] [PubMed] [Google Scholar]
- 23.Gualano MR, Gili R, Scaioli G, et al. General population’s knowledge and attitudes about antibiotics: a systematic review and meta-analysis. Pharmacoepidemiol Drug Saf 2015;24:2–10. 10.1002/pds.3716 [DOI] [PubMed] [Google Scholar]
- 24.Linder JA, Singer DE. Desire for antibiotics and antibiotic prescribing for adults with upper respiratory tract infections. J Gen Intern Med 2003;18:795–801. 10.1046/j.1525-1497.2003.21101.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Moro ML, Marchi M, Gagliotti C, et al. Why do paediatricians prescribe antibiotics? Results of an Italian regional project. BMC Pediatr 2009;9:69 10.1186/1471-2431-9-69 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Grimaldi-Bensouda L, Bégaud B, Rossignol M, et al. Management of upper respiratory tract infections by different medical practices, including homeopathy, and consumption of antibiotics in primary care: the EPI3 cohort study in France 2007-2008. PLoS One 2014;9:e89990 10.1371/journal.pone.0089990 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Hamre HJ, Glockmann A, Schwarz R, et al. Antibiotic use in children with acute respiratory or ear infections: prospective observational comparison of anthroposophic and conventional treatment under routine primary care conditions. Evid Based Complement Alternat Med 2014;2014:1–17. 10.1155/2014/243801 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Taylor JA, Jacobs J. Homeopathic ear drops as an adjunct in reducing antibiotic usage in children with acute otitis media. Glob Pediatr Health 2014;1:2333794X1455939 10.1177/2333794X14559395 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.House of Lords. In: Ho L, ed Science and technology - sixth report, 2000. [Google Scholar]
- 30.Kienle GS, Albonico HU, Baars E, et al. Anthroposophic medicine: an integrative medical system originating in europe. Glob Adv Health Med 2013;2:20–31. 10.7453/gahmj.2012.087 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.NHS Digital. Practice level prescribing in England: a summary. http://content.digital.nhs.uk/gpprescribingdata
- 32.Public Health England. Chapter 19 Influenza: the Green Book, 2015. [Google Scholar]
- 33.Tosas Auguet O, Betley JR, Stabler RA, et al. Evidence for community transmission of community-associated but not health-care-associated methicillin-resistant Staphylococcus aureus strains linked to social and material deprivation: spatial analysis of cross-sectional data. PLoS Med 2016;13:e1001944 10.1371/journal.pmed.1001944 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Department for Communities and Local Government. The english indices of deprivation 2015, 2015. [Google Scholar]
- 35.Hilbe JM. Negative binomial regression. Cambridge, UK: Cambridge University Press, 2012. [Google Scholar]
- 36.McNulty CA. Management of infection guidance for primary care for consultation and local adaptation. London, UK: Public Health England, 2017. [Google Scholar]
- 37.Ashworth M, Charlton J, Ballard K, et al. Variations in antibiotic prescribing and consultation rates for acute respiratory infection in UK general practices 1995-2000. Br J Gen Pract 2005;55:603–8. [PMC free article] [PubMed] [Google Scholar]
- 38.Little P, Gould C, Williamson I, et al. Reattendance and complications in a randomised trial of prescribing strategies for sore throat: the medicalising effect of prescribing antibiotics. BMJ 1997;315:350–2. 10.1136/bmj.315.7104.350 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Moore M, Little P, Rumsby K, et al. Effect of antibiotic prescribing strategies and an information leaflet on longer-term reconsultation for acute lower respiratory tract infection. Br J Gen Pract 2009;59:728–34. 10.3399/bjgp09X472601 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Brookes-Howell L, Hood K, Cooper L, et al. Understanding variation in primary medical care: a nine-country qualitative study of clinicians’ accounts of the non-clinical factors that shape antibiotic prescribing decisions for lower respiratory tract infection. BMJ Open 2012;2:e000796 10.1136/bmjopen-2011-000796 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Butler CC, Hood K, Verheij T, et al. Variation in antibiotic prescribing and its impact on recovery in patients with acute cough in primary care: prospective study in 13 countries. BMJ 2009;338:b2242 10.1136/bmj.b2242 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Silverman M, Povitz M, Sontrop JM, et al. Antibiotic prescribing for nonbacterial acute upper respiratory infections in elderly persons. Ann Intern Med 2017;166:765–74. 10.7326/M16-1131 [DOI] [PubMed] [Google Scholar]
- 43.Kenealy T, Arroll B. Antibiotics for the common cold and acute purulent rhinitis. Cochrane Database Syst Rev 2013;6:CD000247 10.1002/14651858.CD000247.pub3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Little P, Stuart B, Moore M, et al. Amoxicillin for acute lower-respiratory-tract infection in primary care when pneumonia is not suspected: a 12-country, randomised, placebo-controlled trial. Lancet Infect Dis 2013;13:123–9. 10.1016/S1473-3099(12)70300-6 [DOI] [PubMed] [Google Scholar]
- 45.Smith SM, Fahey T, Smucny J, et al. Antibiotics for acute bronchitis. Cochrane Database Syst Rev 2017;6:CD000245 10.1002/14651858.CD000245.pub4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Spinks A, Glasziou PP, Del Mar CB. Antibiotics for sore throat. Cochrane Database Syst Rev 2013;5:CD000023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Gágyor I, Bleidorn J, Kochen MM, et al. Ibuprofen versus fosfomycin for uncomplicated urinary tract infection in women: randomised controlled trial. BMJ 2015;351:h6544 10.1136/bmj.h6544 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Jarvis A, Perry R, Smith D, et al. General practitioners’ beliefs about the clinical utility of complementary and alternative medicine. Prim Health Care Res Dev 2015;16:246–53. 10.1017/S146342361400022X [DOI] [PubMed] [Google Scholar]
- 49.Hawker JI, Smith S, Smith GE, et al. Trends in antibiotic prescribing in primary care for clinical syndromes subject to national recommendations to reduce antibiotic resistance, UK 1995-2011: analysis of a large database of primary care consultations. J Antimicrob Chemother 2014;69:3423–30. 10.1093/jac/dku291 [DOI] [PubMed] [Google Scholar]
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