OpenPrescribing: normalised data and software tool to research trends in English NHS primary care prescribing 1998-2016

Private prescribing of controlled opioids in England, 2014-2021: a retrospective observational study

BACKGROUND

Trends in NHS opioid prescribing have been well published, yet trends in private prescribing of opioids have not been widely established.

AIM

To assess trends and geographical variation in controlled opioids prescribed by private prescribers in England.

DESIGN AND SETTING

This was a retrospective observational study in English primary health care.

METHOD

Data on Schedule 2 and 3 controlled opioids ('controlled opioids') were obtained from the NHS Business Services Authority (BSA) using Freedom of Information (FOI) requests between 1 January 2014 and 30 November 2021. Absolute counts and rates of the number of items dispensed per cumulative number of registered private prescribers were calculated and stratified over time, by opioid type, and geographical region.

RESULTS

This study found that 128 341 items of controlled opioids were prescribed by private prescribers in England between January 2014 and November 2021, which decreased by 50% from 23 339 items (4.09 items/prescriber) in 2014 to 11 573 items (1.49 items/prescriber) in 2020. Methadone (36%, n = 46 660) was the most common controlled opioid prescribed privately, followed by morphine (18%, n = 22 543), buprenorphine (16%, n = 20 521), and oxycodone (12%, n = 15 319). Prescriptions were highest in London (74%, n = 94 438), followed by the South-East of England (7%, n = 9237). A proportion of items (n = 462; 0.36%) were prescribed by 'unidentified doctors' where the prescription is not readily attributable to an individual prescriber by the BSA.

CONCLUSION

Controlled opioids prescribed by private prescribers in England decreased and were primarily prescribed in London. To ensure patient safety, the monitoring and surveillance of controlled opioids dispensed privately should continue and items linked to 'unidentified doctors' should be addressed further.

[Efectividad de una intervención multimodal para la mejora de la atención al dolor crónico.]

OBJECTIVE

The prevalence of chronic pain in Spain is 17%, which causes suffering and significant loss of quality of life. Therapies should not focus only on pain reduction, to improve function and quality of life are necessary. Currently, it is committed to combining drugs and other therapies such as relaxation, meditation, cognitive behavioral therapy, targeted exercises, healthy lifestyles and techniques to increase self-esteem and motivation for change. These therapies can be used as part of a multimodal approach, forming part of multicomponent programs or workshops. In this paper we proposed to evaluate the effectiveness of a workshop developed from the Hospital San Juan de Dios del Ajarafe, that integrated different non-pharmacological therapies in the control of chronic non-oncologic pain and to analyze patients' perceptions of the techniques applied and how they affected pain and lifestyles.

METHODS

An intragroup before-after study (beginning-end of the workshop) was carried out, comparing pain, well-being, drug use, quality of life, and self-esteem. Surveys were conducted to deepen more qualitative aspects and identify improvements. The workshop consisted of psychoeducational action and training for the mental control of pain and emotions, based on the active participation of the patient in the management of his disease, promoting self-care and self-esteem, and aiming to improve well-being and quality of life. It consisted of 5 sessions of 3 hours (1 per week); of a group, interactive and practical nature. Statistical analysis was performed with SPSS vs.27.0. To compare related measures (before-after) we used Student's T tests for paired samples and Wilcoxon's test and to compare independent groups, Student's T and Mann Whitney's U; for the qualitative variables, we used Chi-Square and Fisher's test.

RESULTS

Four workshops were evaluated in which 63 patients participated, with a mean age of 57.6 (SD:11.37) years, 60 (95.2%) of them were women. At the end of the workshop pain decreased 1.5 median (-2.0-0) and well-being increased 2.0 (0-2.0); quality of life increased a median of 0.121 (SD: 0.209), health status 16.8 (23.78) and self-esteem 2.74 (4.73); [p<0.001]. The best valued techniques were meditations, mainly mental analgesia, affirmations in the mirror and self-esteem techniques.

CONCLUSIONS

Overall satisfaction with the workshop is 9.8 out of 10. There is a pain control and improvement in quality of life, self-perception of health status, well-being and self-esteem.

Estimating the fitness cost and benefit of antimicrobial resistance from pathogen genomic data

Increasing levels of antibiotic resistance in many bacterial pathogen populations are a major threat to public health. Resistance to an antibiotic provides a fitness benefit when the bacteria are exposed to this antibiotic, but resistance also often comes at a cost to the resistant pathogen relative to susceptible counterparts. We lack a good understanding of these benefits and costs of resistance for many bacterial pathogens and antibiotics, but estimating them could lead to better use of antibiotics in a way that reduces or prevents the spread of resistance. Here, we propose a new model for the joint epidemiology of susceptible and resistant variants, which includes explicit parameters for the cost and benefit of resistance. We show how Bayesian inference can be performed under this model using phylogenetic data from susceptible and resistant lineages and that by combining data from both we are able to disentangle and estimate the resistance cost and benefit parameters separately. We applied our inferential methodology to several simulated datasets to demonstrate good scalability and accuracy. We analysed a dataset of Neisseria gonorrhoeae genomes collected between 2000 and 2013 in the USA. We found that two unrelated lineages resistant to fluoroquinolones shared similar epidemic dynamics and resistance parameters. Fluoroquinolones were abandoned for the treatment of gonorrhoea due to increasing levels of resistance, but our results suggest that they could be used to treat a minority of around 10% of cases without causing resistance to grow again.

Experiences and behaviours of patients with asthma requesting prescriptions from primary care during medication shortages linked to the COVID-19 lockdown: insights from a qualitative analysis of a UK asthma online community

BACKGROUND

Inhaler shortages were reported in the UK following declaration of the COVID-19 pandemic, prompting advice against stockpiling.

AIM

To understand experiences and behaviours of patients with asthma requesting prescriptions from primary care during asthma medication shortages.

DESIGN & SETTING

UK asthma online community, between March and December 2020.

METHOD

Thematic analysis of posts identified using search terms 'shortage', 'out of stock', 'prescribe', and 'prescription'.

RESULTS

Sixty-seven participants were identified (48 adults, two children, 17 unstated age). Factors leading to increased requests included the following: stockpiling; early ordering; realising inhalers were out of date; and doctors prescribing multiple medication items. Patients' anxieties that could lead to stockpiling included the following: fear of asthma attacks leading to admission and acquiring COVID-19 in hospital; lack of dose counters on some inhalers; and believing a lower amount of drug is delivered in the last actuations. Strategies adopted in relation to shortages or changes in treatment owing to out-of-stock medications included the following: starting stockpiling; ordering prescriptions early; contacting medical professionals for advice or alternative prescriptions; getting 'emergency prescriptions'; ordering online or privately; seeking medications in different pharmacies; contacting drug manufacturers; and keeping track of number of doses left in canisters. No evidence was found of anxiety-triggered asthma symptoms that required medications due to fear of COVID-19. Participants seemed to disregard advice against stockpiling.

CONCLUSION

Better preparation is a key lesson from the COVID-19 pandemic. Clinicians, the pharmaceutical industry, and policymakers should use insights from this work to plan how to better manage medication shortages in future emergency situations.

Dilemmas Related to Direct-Acting Oral Anticoagulant Administration in Patients With Extreme Obesity

OBJECTIVE

The objective of the study was to discuss the controversies surrounding the use and dosing of direct-acting oral anticoagulants (DOACs) in obese patients recognizing the limitations of the existing evidence base that preclude strong recommendations.

DATA SOURCES

A literature search of MEDLINE was performed (2020 to end August 2022) subsequent to recent guidelines using the following search terms: direct acting anticoagulants, obesity, rivaroxaban, apixaban, edoxaban, dabigatran, dabigatran etexilate, and clinical practice guidelines.

STUDY SELECTION AND DATA ABSTRACTION

English-language studies and those conducted in adults were selected.

DATA SYNTHESIS

The available randomized studies evaluating DOACs had relatively small numbers of patients with more extreme forms of obesity (body mass index [BMI] > 40 kg/m²) and none of the larger studies had a specific focus on dosing DOACs in obese patients. Recent guidelines by the International Society on Thrombosis and Haemostasis (ISTH) have specific recommendations for dosing DOACs in obesity. There are pharmacokinetic/pharmacodynamic and observational studies published before and after the ISTH guidelines with a focus on DOAC dosing in obese patients that generally support the recommendations in the guidelines, but most involved small numbers of patients usually with BMIs <45 kg/m².

RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE

This review discusses DOAC dosing in obesity with important considerations for clinicians related to DOAC choice and dosing.

CONCLUSIONS

Dosing alterations of DOACs do not appear to be necessary when used for either prophylaxis or treatment in patients with BMIs up to approximately 45 to 50 kg/m², but research is needed for BMIs >50 kg/m².

An Explainable Transformer-Based Deep Learning Model for the Prediction of Incident Heart Failure

Predicting the incidence of complex chronic conditions such as heart failure is challenging. Deep learning models applied to rich electronic health records may improve prediction but remain unexplainable hampering their wider use in medical practice. We aimed to develop a deep-learning framework for accurate and yet explainable prediction of 6-month incident heart failure (HF). Using 100,071 patients from longitudinal linked electronic health records across the U.K., we applied a novel Transformer-based risk model using all community and hospital diagnoses and medications contextualized within the age and calendar year for each patient's clinical encounter. Feature importance was investigated with an ablation analysis to compare model performance when alternatively removing features and by comparing the variability of temporal representations. A post-hoc perturbation technique was conducted to propagate the changes in the input to the outcome for feature contribution analyses. Our model achieved 0.93 area under the receiver operator curve and 0.69 area under the precision-recall curve on internal 5-fold cross validation and outperformed existing deep learning models. Ablation analysis indicated medication is important for predicting HF risk, calendar year is more important than chronological age, which was further reinforced by temporal variability analysis. Contribution analyses identified risk factors that are closely related to HF. Many of them were consistent with existing knowledge from clinical and epidemiological research but several new associations were revealed which had not been considered in expert-driven risk prediction models. In conclusion, the results highlight that our deep learning model, in addition high predictive performance, can inform data-driven risk factor identification.

PrAna: an R package to calculate and visualize England NHS primary care prescribing data

Background

The objective of this work to calculate prescribed quantity of an active pharmaceutical ingredient (API) in prescription medications for human use, to facilitate research on the prediction of amount of API released to the environment and create an open-data tool to facilitate spatiotemporal and long-term prescription trends for wider usage.

Design

We have developed an R package, PrAna to calculate the prescribed quantity (in kg) of an APIs by postcode using England’s national level prescription data provided by National Health Service, for the years 2015–2018. Datasets generated using PrAna can be visualized in a real-time interactive web-based tool, PrAnaViz to explore spatiotemporal and long-term trends. The visualisations can be customised by selecting month, year, API, and region.

Results

PrAnaViz’s targeted API approach is demonstrated with the visualisation of prescribed quantities of 14 APIs in the Bath and North East Somerset (BANES) region during 2018. Once the APIs list is loaded, the back end retrieves relevant data and populates the graphs based on user-defined data features in real-time. These plots include the prescribed quantity of APIs over a year, by month, and individual API by month, general practice, postcode, and medicinal form. The non-targeted API approach is demonstrated with the visualisation of clarithromycin prescribed quantities at different postcodes in the BANES region.

Conclusion

PrAna and PrAnaViz enables the analysis of spatio-temporal and long-term trends with prescribed quantities of different APIs by postcode. This can be used as a support tool for policymakers, academics and researchers in public healthcare, and environmental scientist to monitor different group of pharmaceuticals emitted to the environment and for prospective risk assessment of pharmaceuticals in the environment.

Exploring temporal trends and risk factors for resistance in Escherichia coli-causing bacteraemia in England between 2013 and 2018: an ecological study

BACKGROUND

Escherichia coli are Gram-negative bacteria associated with an increasing burden of antimicrobial resistance (AMR) in England.

OBJECTIVES

To create a comprehensive epidemiological picture of E. coli bacteraemia resistance trends and risk factors in England by linking national microbiology data sources and performing a longitudinal analysis of rates.

METHODS

A retrospective observational study was conducted on all national records for antimicrobial susceptibility testing on E. coli bacteraemia in England from 1 January 2013 to 31 December 2018 from the UK Health Security Agency (UKHSA) and the BSAC Resistance Surveillance Programme (BSAC-RSP). Trends in AMR and MDR were estimated using iterative sequential regression. Logistic regression analyses were performed on UKHSA data to estimate the relationship between risk factors and AMR or MDR in E. coli bacteraemia isolates.

RESULTS

An increase in resistance rates was observed in community- and hospital-onset bacteraemia for third-generation cephalosporins, co-amoxiclav, gentamicin and ciprofloxacin. Among community-acquired cases, and after adjustment for other factors, patients aged >65 years were more likely to be infected by E. coli isolates resistant to at least one of 11 antibiotics than those aged 18-64 years (OR: 1.21, 95% CI: 1.18-1.25; P < 0.05). In hospital-onset cases, E. coli isolates from those aged 1-17 years were more likely to be resistant than those aged 18-64 years (OR: 1.33, 95% CI: 1.02-1.73; P < 0.05).

CONCLUSIONS

Antibiotic resistance rates in E. coli-causing bacteraemia increased between 2013 and 2018 in England for key antimicrobial agents. Findings of this study have implications for guiding future policies on a prescribing of antimicrobial agents, for specific patient populations in particular.

The effects of an evidence- and theory-informed feedback intervention on opioid prescribing for non-cancer pain in primary care: A controlled interrupted time series analysis

BACKGROUND

The rise in opioid prescribing in primary care represents a significant international public health challenge, associated with increased psychosocial problems, hospitalisations, and mortality. We evaluated the effects of a comparative feedback intervention with persuasive messaging and action planning on opioid prescribing in primary care.

METHODS AND FINDINGS

A quasi-experimental controlled interrupted time series analysis used anonymised, aggregated practice data from electronic health records and prescribing data from publicly available sources. The study included 316 intervention and 130 control primary care practices in the Yorkshire and Humber region, UK, serving 2.2 million and 1 million residents, respectively. We observed the number of adult patients prescribed opioid medication by practice between July 2013 and December 2017. We excluded adults with coded cancer or drug dependency. The intervention, the Campaign to Reduce Opioid Prescribing (CROP), entailed bimonthly, comparative, and practice-individualised feedback reports to practices, with persuasive messaging and suggested actions over 1 year. Outcomes comprised the number of adults per 1,000 adults per month prescribed any opioid (main outcome), prescribed strong opioids, prescribed opioids in high-risk groups, prescribed other analgesics, and referred to musculoskeletal services. The number of adults prescribed any opioid rose pre-intervention in both intervention and control practices, by 0.18 (95% CI 0.11, 0.25) and 0.36 (95% CI 0.27, 0.46) per 1,000 adults per month, respectively. During the intervention period, prescribing per 1,000 adults fell in intervention practices (change -0.11; 95% CI -0.30, -0.08) and continued rising in control practices (change 0.54; 95% CI 0.29, 0.78), with a difference of -0.65 per 1,000 patients (95% CI -0.96, -0.34), corresponding to 15,000 fewer patients prescribed opioids. These trends continued post-intervention, although at slower rates. Prescribing of strong opioids, total opioid prescriptions, and prescribing in high-risk patient groups also generally fell. Prescribing of other analgesics fell whilst musculoskeletal referrals did not rise. Effects were attenuated after feedback ceased. Study limitations include being limited to 1 region in the UK, possible coding errors in routine data, being unable to fully account for concurrent interventions, and uncertainties over how general practices actually used the feedback reports and whether reductions in prescribing were always clinically appropriate.

CONCLUSIONS

Repeated comparative feedback offers a promising and relatively efficient population-level approach to reduce opioid prescribing in primary care, including prescribing of strong opioids and prescribing in high-risk patient groups. Such feedback may also prompt clinicians to reconsider prescribing other medicines associated with chronic pain, without causing a rise in referrals to musculoskeletal clinics. Feedback may need to be sustained for maximum effect.

Trends and variation in antidepressant prescribing in English primary care: a retrospective longitudinal study

Background

Antidepressants are commonly prescribed. There are clear national guidelines in relation to treatment sequencing. This study examines trends and variation in antidepressant prescribing across English primary care.

Aim

To examine trends and variation in antidepressant prescribing in England, with a focus on: monoamine oxidase inhibitors (MAOIs); paroxetine; and dosulepin and trimipramine.

Design & setting

Retrospective longitudinal study using national and practice-level data on antidepressant items prescribed per year (1998–2018) and per month (2010–2019).

Method

Class- and drug-specific proportions were calculated at national and practice levels. Descriptive statistics were generated, percentile charts and maps were plotted, and logistic regression analysis was conducted.

Results

Antidepressant prescriptions more than tripled between 1998 and 2018, from 377 items per 1000 population to 1266 per 1000. MAOI prescribing fell substantially, from 0.7% of all antidepressant items in 1998 to 0.1% in 2018. There was marked variation between practices in past year prescribing of paroxetine (median practice proportion [MPP] = 1.7%, interdecile range [IDR] = 2.6%) and dosulepin (MPP = 0.7%, IDR = 1.8%), but less for trimipramine (MPP = 0%, IDR = 0.2%).

Conclusion

Rapid growth and substantial variation in antidepressant prescribing behaviour was found between practices. The causes could be explored using mixed-methods research. Interventions to reduce prescribing of specific antidepressants, such as dosulepin, could include review prompts, alerts at the time of prescribing, and clinician feedback through tools like OpenPrescribing.net.

Effect of antibiotic stewardship interventions in primary care on antimicrobial resistance of Escherichia coli bacteraemia in England (2013-18): a quasi-experimental, ecological, data linkage study

Background

Antimicrobial resistance is a major global health concern, driven by overuse of antibiotics. We aimed to assess the effectiveness of a national antimicrobial stewardship intervention, the National Health Service (NHS) England Quality Premium implemented in 2015–16, on broad-spectrum antibiotic prescribing and Escherichia coli bacteraemia resistance to broad-spectrum antibiotics in England.

Methods

In this quasi-experimental, ecological, data linkage study, we used longitudinal data on bacteraemia for patients registered with a general practitioner in the English National Health Service and patients with E coli bacteraemia notified to the national mandatory surveillance programme between Jan 1, 2013, and Dec 31, 2018. We linked these data to data on antimicrobial susceptibility testing of E coli from Public Health England's Second-Generation Surveillance System. We did an ecological analysis using interrupted time-series analyses and generalised estimating equations to estimate the change in broad-spectrum antibiotics prescribing over time and the change in the proportion of E coli bacteraemia cases for which the causative bacteria were resistant to each antibiotic individually or to at least one of five broad-spectrum antibiotics (co-amoxiclav, ciprofloxacin, levofloxacin, moxifloxacin, ofloxacin), after implementation of the NHS England Quality Premium intervention in April, 2015.

Findings

Before implementation of the Quality Premium, the rate of antibiotic prescribing for all five broad-spectrum antibiotics was increasing at rate of 0·2% per month (incidence rate ratio [IRR] 1·002 [95% CI 1·000–1·004], p=0·046). After implementation of the Quality Premium, an immediate reduction in total broad-spectrum antibiotic prescribing rate was observed (IRR 0·867 [95% CI 0·837–0·898], p<0·0001). This effect was sustained until the end of the study period; a 57% reduction in rate of antibiotic prescribing was observed compared with the counterfactual situation (ie, had the Quality Premium not been implemented). In the same period, the rate of resistance to at least one broad-spectrum antibiotic increased at rate of 0·1% per month (IRR 1·001 [95% CI 0·999–1·003], p=0·346). On implementation of the Quality Premium, an immediate reduction in resistance rate to at least one broad-spectrum antibiotic was observed (IRR 0·947 [95% CI 0·918–0·977], p=0·0007). Although this effect was also sustained until the end of the study period, with a 12·03% reduction in resistance rate compared with the counterfactual situation, the overall trend remained on an upward trajectory. On examination of the long-term effect following implementation of the Quality Premium, there was an increase in the number of isolates resistant to at least one of the five broad-spectrum antibiotics tested (IRR 1·002 [1·000–1·003]; p=0·047).

Interpretation

Although interventions targeting antibiotic use can result in changes in resistance over a short period, they might be insufficient alone to curtail antimicrobial resistance.

Funding

National Institute for Health Research, Economic and Social Research Council, Rosetrees Trust, and The Stoneygate Trust.

PRINCIPLE trial demonstrates scope for in-pandemic improvement in primary care antibiotic stewardship: a retrospective sentinel network cohort study

BACKGROUND

The Platform Randomised trial of INterventions against COVID-19 In older peoPLE (PRINCIPLE) has provided in-pandemic evidence that azithromycin and doxycycline were not beneficial in the early primary care management of COVID-19.

AIM

To explore the extent of azithromycin and doxycycline in-pandemic use, and the scope for trial findings impacting on practice.

DESIGN & SETTING

Crude rates of prescribing and respiratory tract infections (RTI) in 2020 were compared with 2019, using the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC).

METHOD

A negative binomial model was used to compare azithromycin and doxycycline lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), and influenza-like-illness (ILI) in 2020 with 2019; reporting incident rate ratios (IRR) between years, and 95% confidence intervals (95% CI).

RESULTS

Azithromycin prescriptions increased 7% in 2020 compared with 2019, whereas doxycycline decreased by 7%. Concurrently, LRTI and URTI incidence fell by over half (58.3% and 54.4%, respectively) while ILI rose slightly (6.4%). The overall percentage of RTI prescribed azithromycin rose from 0.51% in 2019 to 0.72% in 2020 (risk difference of 0.214% [95% CI = 0.211 to 0.217]); doxycycline rose from 11.86% in 2019 to 15.79% in 2020 (risk difference: 3.93% [95% CI = 3.73 to 4.14]). The adjusted IRR showed azithromycin prescribing was 22% higher in 2020 (IRR = 1.22, 95% CI = 1.19 to 1.26, P<0.0001), for every unit rise in confirmed COVID-19 there was an associated 3% rise in prescription (IRR = 1.03, 95% CI = 1.02 to 1.03, P<0.0001); whereas these measures were static for doxycycline.

CONCLUSION

PRINCIPLE demonstrates scope for improved antimicrobial stewardship during a pandemic.

Deep learning in systems medicine

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape. It discusses how DL can be applied to SM with an emphasis on the applications to predictive, preventive and precision medicine. Several key challenges have been highlighted including delivering clinical impact and improving interpretability. We used some prototypical examples to highlight the relevance and significance of the adoption of DL in SM, one of them is involving the creation of a model for personalized Parkinson's disease. The review offers valuable insights and informs the research in DL and SM.

Surging trends in prescriptions and costs of antidepressants in England amid COVID-19

The social restrictions amid coronavirus disease 2019 (COVID-19) pandemic have posed a serious threat to mental health and have implications in the use of medications for mental health including antidepressants (ADs). This study investigated the trends in prescriptions and costs of various ADs in England during COVID-19 pandemic. National prescribing rates and net ingredient costs (NIC) of all ADs prescriptions during 2016 to 2020 were analyed. The total number of ADs prescriptions dispensed during COVID-19 pandemic (January to December 2020) were 78 million, 4 million more than in 2019 that costed NHS England £ 139 million more than in 2019. Sertraline, an SSRI antidepressant drug, alone accounted for an extra £113 million during 2020 than in 2019. The peak dispensing for ADs was observed in March 2020 while the total costs for AD drugs peaked in April 2020. The rising prescription costs for ADs during COVID-19 pandemic is a potential cause of concern, in particular the increasing use in adolescents and younger adults needs attention, who are at a higher risk of life-threatening adverse drug reactions.

Establishing a primary care audit and feedback implementation laboratory: a consensus study

BACKGROUND

There is a significant variation among individual primary care providers in prescribing of potentially problematic, low-value medicines which cause avoidable patient harm. Audit and feedback is generally effective at improving prescribing. However, progress has been hindered by research waste, leading to unanswered questions about how to include audit and feedback for specific problems and circumstances. Trials of different ways of providing audit and feedback in implementation laboratories have been proposed as a way of improving population healthcare while generating robust evidence on feedback effects. However, there is limited experience in their design and delivery.

AIM

To explore priorities, feasibility, and ethical challenges of establishing a primary care prescribing audit and feedback implementation laboratory.

DESIGN AND SETTING

Two-stage Delphi consensus process involving primary care pharmacy leads, audit and feedback researchers, and patient and public.

METHOD

Participants initially scored statements relating to priorities, feasibility, and ethical considerations for an implementation laboratory. These covered current feedback practice, priority topics for feedback, usefulness of feedback in improving prescribing and different types of prescribing data, acceptability and desirability of different organization levels of randomization, options for trial consent, different methods of delivering feedback, and interest in finding out how effective different ways of presenting feedback would be. After receiving collated results, participants then scored the items again. The consensus was defined using the GRADE criteria. The results were analyzed by group and overall score.

RESULTS

Fourteen participants reached consensus for 38 out of 55 statements. Addressing antibiotic and opioid prescribing emerged as the highest priorities for action. The panel supported statements around addressing high-priority prescribing issues, taking an "opt-out" approach to practice consent if waiving consent was not permitted, and randomizing at lower rather than higher organizational levels. Participants supported patient-level prescribing data and further research evaluating most of the different feedback methods we presented them with.

CONCLUSIONS

There is a good level of support for evaluating a wide range of potential enhancements to improve the effects of feedback on prescribing. The successful design and delivery of a primary care audit and feedback implementation laboratory depend on identifying shared priorities and addressing practical and ethical considerations.

Projected spending for brand-name drugs in English primary care given US prices: a cross-sectional study

Objectives

To estimate additional spending if NHS England paid the same prices as US Medicare Part D for the 50 single-source brand-name drugs with the highest expenditure in English primary care in 2018.

Design

Retrospective analysis of 2018 drug prescribing and spending in the NHS England prescribing data and the Medicare Part D Drug Spending Dashboard and Data. We examined the 50 costliest drugs in English primary care available as brand-name-only in the US and England. We performed cost projections of NHS England spending with US Medicare Part D prices. We estimated average 2018 US rebates as 1 minus the quotient of net divided by gross Medicare Part D spending.

Setting

England and US

Participants

NHS England and US Medicare systems

Main outcome measures

Total spending, prescriptions and claims in NHS England and Medicare Part D. All spending and cost measures were reported in 2018 British pounds.

Results

NHS England spent £1.39 billion on drugs in the cohort. All drugs were more expensive under US Medicare Part D than NHS England. The US–England price ratios ranged from 1.3 to 9.9 (mean ratio 4.8). Accounting for prescribing volume, if NHS England had paid US Medicare Part D prices after adjusting for estimated US rebates, it would have spent 4.6 times as much in 2018 on drugs in the cohort (£6.42 billion).

Conclusions

Spending by NHS England would be substantially higher if it paid US Medicare Part D prices. This could result in decreased access to medicines and other health services.

Predicting the future distribution of antibiotic resistance using time series forecasting and geospatial modelling

Background: Increasing antibiotic resistance in a location may be mitigated by changes in treatment policy, or interventions to limit transmission of resistant bacteria. Therefore, accurate forecasting of the distribution of antibiotic resistance could be advantageous. Two previously published studies addressed this, but neither study compared alternative forecasting algorithms or considered spatial patterns of resistance spread. Methods: We analysed data describing the annual prevalence of antibiotic resistance per country in Europe from 2012 – 2016, and the quarterly prevalence of antibiotic resistance per clinical commissioning group in England from 2015 – 2018. We combined these with data on rates of possible covariates of resistance. These data were used to compare the previously published forecasting models, with other commonly used forecasting models, including one geospatial model. Covariates were incorporated into the geospatial model to assess their relationship with antibiotic resistance. Results: For the European data, which was recorded on a coarse spatiotemporal scale, a naïve forecasting model was consistently the most accurate of any of the forecasting models tested. The geospatial model did not improve on this accuracy. However, it did provide some evidence that antibiotic consumption can partially explain the distribution of resistance. The English data were aggregated at a finer scale, and expected-trend-seasonal (ETS) forecasts were the most accurate. The geospatial model did not significantly improve upon the median accuracy of the ETS model, but it appeared to be less sensitive to noise in the data, and provided evidence that rates of antibiotic prescription and bacteraemia are correlated with resistance. Conclusion: Annual, national-level surveillance data appears to be insufficient for fitting accurate antibiotic resistance forecasting models, but there is evidence that data collected at a finer spatiotemporal scale could be used to improve forecast accuracy. Additionally, incorporating antibiotic prescription or consumption data into the model could improve the predictive accuracy.

Prescription of suboptimal statin treatment regimens: a retrospective cohort study of trends and variation in English primary care

BACKGROUND

Since 2014 English national guidance recommends 'high-intensity' statins, reducing low-density lipoprotein (LDL) cholesterol by ≥40%.

AIM

To describe trends and variation in low-/medium-intensity statin prescribing and assess the feasibility of rapid prescribing behaviour change.

DESIGN AND SETTING

A retrospective cohort study using OpenPrescribing data from all 8142 standard NHS general practices in England from August 2010 to March 2019.

METHOD

Statins were categorised as high- or low-/medium-intensity using two different thresholds, and the proportion prescribed below these thresholds was calculated. The authors plotted trends and geographical variation, carried out mixed-effects logistic regression to identify practice characteristics associated with breaching of guidance, and used indicator saturation to identify sudden prescribing changes.

RESULTS

The proportion of statins prescribed below the recommended 40% LDL-lowering threshold has decreased gradually from 80% in 2011/2012 to 45% in 2019; the proportion below a pragmatic 37% threshold decreased from 30% to 18% in 2019. Guidance from 2014 had minimal impact on trends. Wide variation was found between practices (interdecile ranges 20% to 85% and 10% to 30% respectively in 2018). Regression identified no strong associations with breaching of guidance. Indicator saturation identified several practices exhibiting sudden changes towards greater guideline compliance.

CONCLUSION

Breaches of guidance on choice of statin remain common, with substantial variation between practices. Some have implemented rapid change, indicating the feasibility of rapid prescribing behaviour change. This article discusses the potential for a national strategic approach, using data and evidence to optimise care, including targeted education alongside audit and feedback to outliers through services such as OpenPrescribing.

No benefit from flexible titration above minimum licensed dose in prescribing antidepressants for major depression: systematic review

BACKGROUND

In fixed-dose antidepressant trials, the lower range of the licensed dose achieves the optimal balance between efficacy and tolerability. Whether flexible upward titration while side-effects permit provides additional benefits is unknown.

METHODS

We did a systematic review of placebo-controlled randomized trials that examined selective serotonin reuptake inhibitors (SSRIs), venlafaxine or mirtazapine in the acute treatment of major depression. Our primary outcome was response, defined as 50% or greater reduction in depression severity. Secondary outcomes included drop-outs due to adverse effects and drop-outs for any reason. We conducted random-effects meta-analyses to calculate the ratios of odds ratios (RORs) between trials comparing the flexible dose titrating above the minimum licensed dose against placebo and those comparing the fixed minimum licensed dose against placebo.

RESULTS

We included 123 published and unpublished randomized controlled trials (29 420 participants). There was no evidence supporting efficacy of the flexible dosing over the fixed low dose of SSRIs (ROR 0.96, 95% CI: 0.73 to 1.25), venlafaxine (1.24, 0.96 to 1.60) or mirtazapine (0.77, 0.33 to 1.78). No important differences were noted for tolerability or for any subgroup analyses except the superior efficacy of venlafaxine flexible dosing between 75 and 150 mg over the fixed 75 mg (1.30, 1.02 to 1.65).

CONCLUSION

There was no evidence to support added value in terms of efficacy, tolerability or acceptability of flexibly titrating up the dosage over the minimum licensed dose of SSRIs or mirtazapine. For venlafaxine, increased efficacy can be expected by flexibly titrating up to 150 mg.

Optimal Dose of Selective Serotonin Reuptake Inhibitors, Venlafaxine, and Mirtazapine in Major Depression: A Systematic Review and Dose-Response Meta-Analysis

(Reprinted with permission from Lancet Psychiatry. 2019 Jul;6(7):601-609).

Tesco Grocery 1.0, a large-scale dataset of grocery purchases in London

We present the Tesco Grocery 1.0 dataset: a record of 420 M food items purchased by 1.6 M fidelity card owners who shopped at the 411 Tesco stores in Greater London over the course of the entire year of 2015, aggregated at the level of census areas to preserve anonymity. For each area, we report the number of transactions and nutritional properties of the typical food item bought including the average caloric intake and the composition of nutrients. The set of global trade international numbers (barcodes) for each food type is also included. To establish data validity we: i) compare food purchase volumes to population from census to assess representativeness, and ii) match nutrient and energy intake to official statistics of food-related illnesses to appraise the extent to which the dataset is ecologically valid. Given its unprecedented scale and geographic granularity, the data can be used to link food purchases to a number of geographically-salient indicators, which enables studies on health outcomes, cultural aspects, and economic factors.

Open source automated insulin delivery: addressing the challenge

Do-it-yourself automated insulin delivery systems for people living with type 1 diabetes use commercially available continuous glucose sensors and insulin pumps linked by unregulated open source software. Uptake of these systems is increasing, with growing evidence suggesting that positive glucose outcomes may be feasible. Increasing interest from people living with, or affected by, type 1 diabetes presents challenges to healthcare professionals, device manufacturers and regulators as the legal, governance and risk frameworks for such devices are not defined. We discuss the data, education, policy, technology and medicolegal obstacles to wider implementation of DIY systems and outline the next steps required for a co-ordinated approach to reducing variation in access to a technology that has potential to enable glucose self-management closer to target.

Variation in responsiveness to warranted behaviour change among NHS clinicians: novel implementation of change detection methods in longitudinal prescribing data

OBJECTIVES

To determine how clinicians vary in their response to new guidance on existing or new interventions, by measuring the timing and magnitude of change at healthcare institutions.

DESIGN

Automated change detection in longitudinal prescribing data.

SETTING

Prescribing data in English primary care.

PARTICIPANTS

English general practices.

MAIN OUTCOME MEASURES

In each practice the following were measured: the timing of the largest changes, steepness of the change slope (change in proportion per month), and magnitude of the change for two example time series (expiry of the Cerazette patent in 2012, leading to cheaper generic desogestrel alternatives becoming available; and a change in antibiotic prescribing guidelines after 2014, favouring nitrofurantoin over trimethoprim for uncomplicated urinary tract infection (UTI)).

RESULTS

Substantial heterogeneity was found between institutions in both timing and steepness of change. The range of time delay before a change was implemented was large (interquartile range 2-14 months (median 8) for Cerazette, and 5-29 months (18) for UTI). Substantial heterogeneity was also seen in slope following a detected change (interquartile range 2-28% absolute reduction per month (median 9%) for Cerazette, and 1-8% (2%) for UTI). When changes were implemented, the magnitude of change showed substantially less heterogeneity (interquartile range 44-85% (median 66%) for Cerazette and 28-47% (38%) for UTI).

CONCLUSIONS

Substantial variation was observed in the speed with which individual NHS general practices responded to warranted changes in clinical practice. Changes in prescribing behaviour were detected automatically and robustly. Detection of structural breaks using indicator saturation methods opens up new opportunities to improve patient care through audit and feedback by moving away from cross sectional analyses, and automatically identifying institutions that respond rapidly, or slowly, to warranted changes in clinical practice.

Optimal dose of selective serotonin reuptake inhibitors, venlafaxine, and mirtazapine in major depression: a systematic review and dose-response meta-analysis

BACKGROUND

Depression is the single largest contributor to non-fatal health loss worldwide. Second-generation antidepressants are the first-line option for pharmacological management of depression. Optimising their use is crucial in reducing the burden of depression; however, debate about their dose dependency and their optimal target dose is ongoing. We have aimed to summarise the currently available best evidence to inform this clinical question.

METHODS

We did a systematic review and dose-response meta-analysis of double-blind, randomised controlled trials that examined fixed doses of five selective serotonin reuptake inhibitors (SSRIs; citalopram, escitalopram, fluoxetine, paroxetine, and sertraline), venlafaxine, or mirtazapine in the acute treatment of adults (aged 18 years or older) with major depression, identified from the Cochrane Central Register of Controlled Trials, CINAHL, Embase, LILACS, MEDLINE, PsycINFO, AMED, PSYNDEX, websites of drug licensing agencies and pharmaceutical companies, and trial registries. We imposed no language restrictions, and the search was updated until Jan 8, 2016. Doses of SSRIs were converted to fluoxetine equivalents. Trials of antidepressants for patients with depression and a serious concomitant physical illness were excluded. The main outcomes were efficacy (treatment response defined as 50% or greater reduction in depression severity), tolerability (dropouts due to adverse effects), and acceptability (dropouts for any reasons), all after a median of 8 weeks of treatment (range 4-12 weeks). We used a random-effects, dose-response meta-analysis model with flexible splines for SSRIs, venlafaxine, and mirtazapine.

FINDINGS

28 554 records were identified through our search (24 524 published and 4030 unpublished records). 561 published and 121 unpublished full-text records were assessed for eligibility, and 77 studies were included (19 364 participants; mean age 42·5 years, SD 11·0; 7156 [60·9%] of 11 749 reported were women). For SSRIs (99 treatment groups), the dose-efficacy curve showed a gradual increase up to doses between 20 mg and 40 mg fluoxetine equivalents, and a flat to decreasing trend through the higher licensed doses up to 80 mg fluoxetine equivalents. Dropouts due to adverse effects increased steeply through the examined range. The relationship between the dose and dropouts for any reason indicated optimal acceptability for the SSRIs in the lower licensed range between 20 mg and 40 mg fluoxetine equivalents. Venlafaxine (16 treatment groups) had an initially increasing dose-efficacy relationship up to around 75-150 mg, followed by a more modest increase, whereas for mirtazapine (11 treatment groups) efficacy increased up to a dose of about 30 mg and then decreased. Both venlafaxine and mirtazapine showed optimal acceptability in the lower range of their licensed dose. These results were robust to several sensitivity analyses.

INTERPRETATION

For the most commonly used second-generation antidepressants, the lower range of the licensed dose achieves the optimal balance between efficacy, tolerability, and acceptability in the acute treatment of major depression.

FUNDING

Japan Society for the Promotion of Science, Swiss National Science Foundation, and National Institute for Health Research.

Pan-Canadian Pharmaceutical Alliance (pCPA): Timelines Analysis and Policy Implications

This analysis follows our recent study showing that Canadian public reimbursement delays have lengthened from regulatory approval to listing decisions by public drug plans and delayed public access to innovative medicines, mainly due to processes following the Common Drug Review (CDR) and the pan-Canadian Oncology Drug Review (pCODR). Public drug plans participate in a pan-Canadian Pharmaceutical Alliance (pCPA) joint negotiation process before making decisions about whether or not to reimburse a product reviewed through CDR and pCODR. This research aims to report the findings from a comprehensive analysis of pCPA process times, times to reimbursement by public payers in Canada, and to explore the opportunities to reduce total delays in public reimbursement with a specific focus on the pCPA process. An analysis was conducted of pCPA timelines with respect to making decisions about products and indications reviewed through CDR/pCODR, and focusses on three separate time components: time to begin negotiating, time spent negotiating, and time to implement the negotiation (i.e., time to list) in each of nine jurisdictions (i.e., 10 provinces of Canada, excluding Quebec). This study demonstrates the role of post-CDR/pCODR processes in large and lengthening delays to listing new medicines. Notably, oncology products have experienced the longest increases in time to begin negotiating and to complete negotiations. Trends in listing times post-pCPA across provinces are less clear, however, it appears that consistency in terms of timelines across provinces is not happening quite so smoothly for oncology products compared to non-oncology products. Listing rates also appear to be declining for non-oncology products, although this trend is less conclusive for oncology products. Challenges need to be addressed to improve efficiency, transparency, and ultimately reduce pCPA timelines and total timelines to public reimbursement. Suggested ways to improve and streamline the listing process are: (1) transparent target timelines and associated performance incentives for the pCPA and public plan decisions, (2) parallel HTA-pCPA processes to enable pCPA negotiations to start part-way through the HTA review and allow pCPA negotiation information to be fed back into the HTA review, and (3) innovative agreements that consider patient input and earlier coverage with real-world evidence development.

Opioid prescribing trends and geographical variation in England, 1998-2018: a retrospective database study

BACKGROUND

There is a call for greater monitoring of opioid prescribing in the UK, particularly of strong opioids in chronic pain, for which there is little evidence of clinical benefit. We aimed to comprehensively assess trends and variation in opioid prescribing in primary care in England, from 1998 to 2018, and to assess factors associated with high-dose opioid prescribing behaviour in general practices.

METHODS

We did a retrospective database study using open data sources on prescribing for all general practices in England. For all standard opioids we calculated the number of items prescribed, costs, and oral morphine equivalency to account for variation in strength. We assessed long-term prescribing trends from 1998 to 2017, patterns of geographical variation for 2018, and investigated practice factors associated with higher opioid prescribing. We also analysed prescriptions for long-acting opioids at high doses.

FINDINGS

Between 1998 and 2016, opioid prescriptions increased by 34% in England (from 568 per 1000 patients to 761 per 1000). After correcting for total oral morphine equivalency, the increase was 127% (from 190 000 mg to 431 000 mg per 1000 population). There was a decline in prescriptions from 2016 to 2017. If every practice prescribed high-dose opioids at the lowest decile rate, 543 000 fewer high-dose prescriptions could have been issued over a period of 6 months. Larger practice list size, ruralness, and deprivation were associated with greater high-dose prescribing rates. The clinical commissioning group to which a practice belongs accounted for 11·7% of the variation in high-dose prescribing. We have developed a publicly available interactive online tool, OpenPrescribing.net, which displays all primary care opioid prescribing data in England down to the individual practice level.

INTERPRETATION

Failing to account for opioid strength would substantially underestimate the true increase in opioid prescribing in the National Health Service (NHS) in England. Our findings support calls for greater action to promote best practice in chronic pain prescribing and to reduce geographical variation. This study provides a model for routine monitoring of opioid prescribing to aid targeting of interventions to reduce high-dose prescribing.

FUNDING

National Institute for Health Research (NIHR) School of Primary Care Research, NIHR Biomedical Research Centre Oxford, NHS England.

Time trends and geographical variation in prescribing of drugs for diabetes in England from 1998 to 2017

AIMS

To measure the variation in prescribing of second-line non-insulin diabetes drugs.

MATERIALS AND METHODS

We evaluated time trends for the period 1998 to 2016, using England's publicly available prescribing datasets, and stratified these by the order in which they were prescribed to patients using the Clinical Practice Research Datalink. We calculated the proportion of each class of diabetes drug as a percentage of the total per year. We evaluated geographical variation in prescribing using general practice-level data for the latest 12 months (to August 2017), with aggregation to Clinical Commissioning Groups. We calculated percentiles and ranges, and plotted maps.

RESULTS

Prescribing of therapy after metformin is changing rapidly. Dipeptidyl peptidase-4 (DPP-4) inhibitor use has increased markedly, with DPP-4 inhibitors now the most common second-line drug (43% prescriptions in 2016). The use of sodium-glucose co-transporter-2 (SGLT-2) inhibitors also increased rapidly (14% new second-line, 27% new third-line prescriptions in 2016). There was wide geographical variation in choice of therapies and average spend per patient. In contrast, metformin was consistently used as a first-line treatment in accordance with guidelines.

CONCLUSIONS

In England there is extensive geographical variation in the prescribing of diabetes drugs after metformin, and increasing use of higher-cost DPP-4 inhibitors and SGLT-2 inhibitors compared with low-cost sulphonylureas. Our findings strongly support the case for comparative effectiveness trials of current diabetes drugs.