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We lead multidisciplinary applied research and training to rethink the way health care is delivered in general practice and across the community.
OpenSAFELY: Impact of national guidance on switching anticoagulant therapy during COVID-19 pandemic
Background Early in the COVID-19 pandemic, the National Health Service (NHS) recommended that appropriate patients anticoagulated with warfarin should be switched to direct-acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately coprescribed two anticoagulants following a medication change and associated monitoring. Objective To describe which people were switched from warfarin to DOACs; identify potentially unsafe coprescribing of anticoagulants; and assess whether abnormal clotting results have become more frequent during the pandemic. Methods With the approval of NHS England, we conducted a cohort study using routine clinical data from 24 million NHS patients in England. Results 20 000 of 164 000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in coprescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. International normalised ratio (INR) testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420). Conclusions Increased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people coprescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.
A comprehensive high cost drugs dataset from the NHS in England - An OpenSAFELY-TPP Short Data Report.
Background: At the outset of the COVID-19 pandemic, there was no routine comprehensive hospital medicines data from the UK available to researchers. These records can be important for many analyses including the effect of certain medicines on the risk of severe COVID-19 outcomes. With the approval of NHS England, we set out to obtain data on one specific group of medicines, "high-cost drugs" (HCD) which are typically specialist medicines for the management of long-term conditions, prescribed by hospitals to patients. Additionally, we aimed to make these data available to all approved researchers in OpenSAFELY-TPP. This report is intended to support all studies carried out in OpenSAFELY-TPP, and those elsewhere, working with this dataset or similar data. Methods: Working with the North East Commissioning Support Unit and NHS Digital, we arranged for collation of a single national HCD dataset to help inform responses to the COVID-19 pandemic. The dataset was developed from payment submissions from hospitals to commissioners. Results: In the financial year (FY) 2018/19 there were 2.8 million submissions for 1.1 million unique patient IDs recorded in the HCD. The average number of submissions per patient over the year was 2.6. In FY 2019/20 there were 4.0 million submissions for 1.3 million unique patient IDs. The average number of submissions per patient over the year was 3.1. Of the 21 variables in the dataset, three are now available for analysis in OpenSafely-TPP: Financial year and month of drug being dispensed; drug name; and a description of the drug dispensed. Conclusions: We have described the process for sourcing a national HCD dataset, making these data available for COVID-19-related analysis through OpenSAFELY-TPP and provided information on the variables included in the dataset, data coverage and an initial descriptive analysis.
Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY
Background Long COVID is a term to describe new or persistent symptoms at least four weeks after onset of acute COVID-19. Clinical codes to describe this phenomenon were released in November 2020 in the UK, but it is not known how these codes have been used in practice. Methods Working on behalf of NHS England, we used OpenSAFELY data encompassing 96% of the English population. We measured the proportion of people with a recorded code for long COVID, overall and by demographic factors, electronic health record software system, and week. We also measured variation in recording amongst practices. Results Long COVID was recorded for 23,273 people. Coding was unevenly distributed amongst practices, with 26.7% of practices having not used the codes at all. Regional variation was high, ranging between 20.3 per 100,000 people for East of England (95% confidence interval 19.3-21.4) and 55.6 in London (95% CI 54.1-57.1). The rate was higher amongst women (52.1, 95% CI 51.3-52.9) compared to men (28.1, 95% CI 27.5-28.7), and higher amongst practices using EMIS software (53.7, 95% CI 52.9-54.4) compared to TPP software (20.9, 95% CI 20.3-21.4). Conclusions Long COVID coding in primary care is low compared with early reports of long COVID prevalence. This may reflect under-coding, sub-optimal communication of clinical terms, under-diagnosis, a true low prevalence of long COVID diagnosed by clinicians, or a combination of factors. We recommend increased awareness of diagnostic codes, to facilitate research and planning of services; and surveys of clinicians’ experiences, to complement ongoing patient surveys.
The impact of lidocaine plaster prescribing reduction strategies: A comparison of two national health services in Europe
Aims: In 2017, two distinct interventions were implemented in Ireland and England to reduce prescribing of lidocaine medicated plasters. In Ireland, restrictions on reimbursement were introduced through implementation of an application system for reimbursement. In England, updated guidance on items which should not be routinely prescribed in primary care, including lidocaine plasters, was published. This study aims to compare how the interventions impacted prescribing of lidocaine plasters in these countries. Methods: We conducted an interrupted time-series study using general practice data. For Ireland, monthly dispensing data (2015–2019) from the means-tested General Medical Services (GMS) scheme was used. For England, data covered all patients. Outcomes were the rate of dispensings, quantity and costs of lidocaine plasters, and we modelled level and trend changes from the first full month of the policy/guidance change. Results: Ireland had higher rates of lidocaine dispensings compared to England throughout the study period; this was 15.22/1000 population immediately pre-intervention, and there was equivalent to a 97.2% immediate reduction following the intervention. In England, the immediate pre-intervention dispensing rate was 0.36/1000, with an immediate reduction of 0.0251/1000 (a 5.8% decrease), followed by a small but significant decrease in the monthly trend relative to the pre-intervention trend of 0.0057 per month. Conclusions: Among two different interventions aiming to decrease low-value lidocaine plaster prescribing, there was a substantially larger impact in Ireland of reimbursement restriction compared to issuing guidance in England. However, this is in the context of much higher baseline rates of use in Ireland compared to England.
The impact of COVID-19 on antibiotic prescribing in primary care in England: Evaluation and risk prediction of appropriateness of type and repeat prescribing
Background: This study aimed to predict risks of potentially inappropriate antibiotic type and repeat prescribing and assess changes during COVID-19. Methods: With the approval of NHS England, we used OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system and selected patients prescribed antibiotics from 2019 to 2021. Multinomial logistic regression models predicted patient's probability of receiving inappropriate antibiotic type or repeat antibiotic course for each common infection. Results: The population included 9.1 million patients with 29.2 million antibiotic prescriptions. 29.1% of prescriptions were identified as repeat prescribing. Those with same day incident infection coded in the EHR had considerably lower rates of repeat prescribing (18.0%) and 8.6% had potentially inappropriate type. No major changes in the rates of repeat antibiotic prescribing during COVID-19 were found. In the 10 risk prediction models, good levels of calibration and moderate levels of discrimination were found. Conclusions: Our study found no evidence of changes in level of inappropriate or repeat antibiotic prescribing after the start of COVID-19. Repeat antibiotic prescribing was frequent and varied according to regional and patient characteristics. There is a need for treatment guidelines to be developed around antibiotic failure and clinicians provided with individualised patient information.
Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report
Background: Care home residents have been severely affected by the COVID-19 pandemic. Electronic Health Records (EHR) hold significant potential for studying the healthcare needs of this vulnerable population; however, identifying care home residents in EHR is not straightforward. We describe and compare three different methods for identifying care home residents in the newly created OpenSAFELY-TPP data analytics platform. Methods: Working on behalf of NHS England, we identified individuals aged 65 years or older potentially living in a care home on the 1st of February 2020 using (1) a complex address linkage, in which cleaned GP registered addresses were matched to old age care home addresses using data from the Care and Quality Commission (CQC); (2) coded events in the EHR; (3) household identifiers, age and household size to identify households with more than 3 individuals aged 65 years or older as potential care home residents. Raw addresses were not available to the investigators. Results: Of 4,437,286 individuals aged 65 years or older, 2.27% were identified as potential care home residents using the complex address linkage, 1.96% using coded events, 3.13% using household size and age and 3.74% using either of these methods. 53,210 individuals (32.0% of all potential care home residents) were classified as care home residents using all three methods. Address linkage had the largest overlap with the other methods; 93.3% of individuals identified as care home residents using the address linkage were also identified as such using either coded events or household age and size. Conclusion: We have described the partial overlap between three methods for identifying care home residents in EHR, and provide detailed instructions for how to implement these in OpenSAFELY-TPP to support research into the impact of the COVID-19 pandemic on care home residents.
Describing the population experiencing COVID-19 vaccine breakthrough following second vaccination in England: a cohort study from OpenSAFELY
Background: While the vaccines against COVID-19 are highly effective, COVID-19 vaccine breakthrough is possible despite being fully vaccinated. With SARS-CoV-2 variants still circulating, describing the characteristics of individuals who have experienced COVID-19 vaccine breakthroughs could be hugely important in helping to determine who may be at greatest risk. Methods: With the approval of NHS England, we conducted a retrospective cohort study using routine clinical data from the OpenSAFELY-TPP database of fully vaccinated individuals, linked to secondary care and death registry data and described the characteristics of those experiencing COVID-19 vaccine breakthroughs. Results: As of 1st November 2021, a total of 15,501,550 individuals were identified as being fully vaccinated against COVID-19, with a median follow-up time of 149 days (IQR: 107–179). From within this population, a total of 579,780 (<4%) individuals reported a positive SARS-CoV-2 test. For every 1000 years of patient follow-up time, the corresponding incidence rate (IR) was 98.06 (95% CI 97.93–98.19). There were 28,580 COVID-19-related hospital admissions, 1980 COVID-19-related critical care admissions and 6435 COVID-19-related deaths; corresponding IRs 4.77 (95% CI 4.74–4.80), 0.33 (95% CI 0.32–0.34) and 1.07 (95% CI 1.06–1.09), respectively. The highest rates of breakthrough COVID-19 were seen in those in care homes and in patients with chronic kidney disease, dialysis, transplant, haematological malignancy or who were immunocompromised. Conclusions: While the majority of COVID-19 vaccine breakthrough cases in England were mild, some differences in rates of breakthrough cases have been identified in several clinical groups. While it is important to note that these findings are simply descriptive and cannot be used to answer why certain groups have higher rates of COVID-19 breakthrough than others, the emergence of the Omicron variant of COVID-19 coupled with the number of positive SARS-CoV-2 tests still occurring is concerning and as numbers of fully vaccinated (and boosted) individuals increases and as follow-up time lengthens, so too will the number of COVID-19 breakthrough cases. Additional analyses, to assess vaccine waning and rates of breakthrough COVID-19 between different variants, aimed at identifying individuals at higher risk, are needed.
Safety of COVID-19 vaccination and acute neurological events: A self-controlled case series in England using the OpenSAFELY platform
Introduction: We investigated the potential association of COVID-19 vaccination with three acute neurological events: Guillain-Barré syndrome (GBS), transverse myelitis and Bell's palsy. Methods: With the approval of NHS England we analysed primary care data from >17 million patients in England linked to emergency care, hospital admission and mortality records in the OpenSAFELY platform. Separately for each vaccine brand, we used a self-controlled case series design to estimate the incidence rate ratio for each outcome in the period following vaccination (4–42 days for GBS, 4–28 days for transverse myelitis and Bell's palsy) compared to a within-person baseline, using conditional Poisson regression. Results: Among 7,783,441 ChAdOx1 vaccinees, there was an increased rate of GBS (N = 517; incidence rate ratio 2·85; 95% CI2·33–3·47) and Bell's palsy (N = 5,350; 1·39; 1·27–1·53) following a first dose of ChAdOx1 vaccine, corresponding to 11.0 additional cases of GBS and 17.9 cases of Bell's palsy per 1 million vaccinees if causal. For GBS this applied to the first, but not the second, dose. There was no clear evidence of an association of ChAdOx1 vaccination with transverse myelitis (N = 199; 1·51; 0·96–2·37). Among 5,729,152 BNT162b2 vaccinees, there was no evidence of any association with GBS (N = 283; 1·09; 0·75–1·57), transverse myelitis (N = 109; 1·62; 0·86–3·03) or Bell's palsy (N = 3,609; 0·89; 0·76–1·03). Among 255,446 mRNA-1273 vaccine recipients there was no evidence of an association with Bell's palsy (N = 78; 0·88, 0·32–2·42). Conclusions: COVID-19 vaccines save lives, but it is important to understand rare adverse events. We observed a short-term increased rate of Guillain-Barré syndrome and Bell's palsy after first dose of ChAdOx1 vaccine. The absolute risk, assuming a causal effect attributable to vaccination, was low.
Association between warfarin and COVID-19-related outcomes compared with direct oral anticoagulants: population-based cohort study
Background: Thromboembolism has been reported as a consequence of severe COVID-19. Although warfarin is a commonly used anticoagulant, it acts by antagonising vitamin K, which is low in patients with severe COVID-19. To date, the clinical evidence on the impact of regular use of warfarin on COVID-19-related thromboembolism is lacking. Methods: On behalf of NHS England, we conducted a population-based cohort study investigating the association between warfarin and COVID-19 outcomes compared with direct oral anticoagulants (DOACs). We used the OpenSAFELY platform to analyse primary care data and pseudonymously linked SARS-CoV-2 antigen testing data, hospital admissions and death records from England. We used Cox regression to estimate hazard ratios (HRs) for COVID-19-related outcomes comparing warfarin with DOACs in people with non-valvular atrial fibrillation. We also conducted negative control outcome analyses (being tested for SARS-CoV-2 and non-COVID-19 death) to assess the potential impact of confounding. Results: A total of 92,339 warfarin users and 280,407 DOAC users were included. We observed a lower risk of all outcomes associated with warfarin versus DOACs [testing positive for SARS-CoV-2, HR 0.73 (95% CI 0.68–0.79); COVID-19-related hospital admission, HR 0.75 (95% CI 0.68–0.83); COVID-19-related deaths, HR 0.74 (95% CI 0.66–0.83)]. A lower risk of negative control outcomes associated with warfarin versus DOACs was also observed [being tested for SARS-CoV-2, HR 0.80 (95% CI 0.79–0.81); non-COVID-19 deaths, HR 0.79 (95% CI 0.76–0.83)]. Conclusions: Overall, this study shows no evidence of harmful effects of warfarin on severe COVID-19 disease.
Data-Driven Identification of Unusual Prescribing Behavior: Analysis and Use of an Interactive Data Tool Using 6 Months of Primary Care Data From 6500 Practices in England
Background: Approaches to addressing unwarranted variation in health care service delivery have traditionally relied on the prospective identification of activities and outcomes, based on a hypothesis, with subsequent reporting against defined measures. Practice-level prescribing data in England are made publicly available by the National Health Service (NHS) Business Services Authority for all general practices. There is an opportunity to adopt a more data-driven approach to capture variability and identify outliers by applying hypothesis-free, data-driven algorithms to national data sets. Objective: This study aimed to develop and apply a hypothesis-free algorithm to identify unusual prescribing behavior in primary care data at multiple administrative levels in the NHS in England and to visualize these results using organization-specific interactive dashboards, thereby demonstrating proof of concept for prioritization approaches. Methods: Here we report a new data-driven approach to quantify how "unusual"the prescribing rates of a particular chemical within an organization are as compared to peer organizations, over a period of 6 months (June-December 2021). This is followed by a ranking to identify which chemicals are the most notable outliers in each organization. These outlying chemicals are calculated for all practices, primary care networks, clinical commissioning groups, and sustainability and transformation partnerships in England. Our results are presented via organization-specific interactive dashboards, the iterative development of which has been informed by user feedback. Results: We developed interactive dashboards for every practice (n=6476) in England, highlighting the unusual prescribing of 2369 chemicals (dashboards are also provided for 42 sustainability and transformation partnerships, 106 clinical commissioning groups, and 1257 primary care networks). User feedback and internal review of case studies demonstrate that our methodology identifies prescribing behavior that sometimes warrants further investigation or is a known issue. Conclusions: Data-driven approaches have the potential to overcome existing biases with regard to the planning and execution of audits, interventions, and policy making within NHS organizations, potentially revealing new targets for improved health care service delivery. We present our dashboards as a proof of concept for generating candidate lists to aid expert users in their interpretation of prescribing data and prioritize further investigations and qualitative research in terms of potential targets for improved performance.
Incidence and management of inflammatory arthritis in England before and during the COVID-19 pandemic: a population-level cohort study using OpenSAFELY
Background: The impact of the COVID-19 pandemic on the incidence and management of inflammatory arthritis is not understood. Routinely captured data in secure platforms, such as OpenSAFELY, offer unique opportunities to understand how care for patients with inflammatory arthritis was impacted upon by the pandemic. Our objective was to use OpenSAFELY to assess the effects of the pandemic on diagnostic incidence and care delivery for inflammatory arthritis in England and to replicate key metrics from the National Early Inflammatory Arthritis Audit. Methods: In this population-level cohort study, we used primary care and hospital data for 17·7 million adults registered with general practices using TPP health record software, to explore the following outcomes between April 1, 2019, and March 31, 2022: (1) incidence of inflammatory arthritis diagnoses (rheumatoid arthritis, psoriatic arthritis, axial spondyloarthritis, and undifferentiated inflammatory arthritis) recorded in primary care; (2) time to first rheumatology assessment; (3) time to first prescription of a disease-modifying antirheumatic drug (DMARD) in primary care; and (4) choice of first DMARD. Findings: Among 17 683 500 adults, there were 31 280 incident inflammatory arthritis diagnoses recorded between April 1, 2019, and March 31, 2022. The mean age of diagnosed patients was 55·4 years (SD 16·6), 18 615 (59·5%) were female, 12 665 (40·5%) were male, and 22 925 (88·3%) of 25 960 with available ethnicity data were White. New inflammatory arthritis diagnoses decreased by 20·3% in the year commencing April, 2020, relative to the preceding year (5·1 vs 6·4 diagnoses per 10 000 adults). The median time to first rheumatology assessment was shorter during the pandemic (18 days; IQR 8–35) than before (21 days; 9–41). The proportion of patients prescribed DMARDs in primary care was similar before and during the pandemic; however, during the pandemic, fewer people were prescribed methotrexate or leflunomide, and more were prescribed sulfasalazine or hydroxychloroquine. Interpretation: Inflammatory arthritis diagnoses decreased markedly during the early phase of the pandemic. The impact on rheumatology assessment times and DMARD prescribing in primary care was less marked than might have been anticipated. This study demonstrates the feasibility of using routinely captured, near real-time data in the secure OpenSAFELY platform to benchmark care quality on a national scale, without the need for manual data collection. Funding: Versus Arthritis and Pfizer Grant for Quality Improvement in Rheumatology.
Evaluating the efficacy and mechanisms of a ketogenic diet as adjunctive treatment for people with treatment-resistant depression: A protocol for a randomised controlled trial.
BACKGROUND: One-third of people with depression do not respond to antidepressants, and, after two adequate courses of antidepressants, are classified as having treatment-resistant depression (TRD). Some case reports suggest that ketogenic diets (KDs) may improve some mental illnesses, and preclinical data indicate that KDs can influence brain reward signalling, anhedonia, cortisol, and gut microbiome which are associated with depression. To date, no trials have examined the clinical effect of a KD on TRD. METHODS: This is a proof-of-concept randomised controlled trial to investigate the efficacy of a six-week programme of weekly dietitian counselling plus provision of KD meals, compared with an intervention involving similar dietetic contact time and promoting a healthy diet with increased vegetable consumption and reduction in saturated fat, plus food vouchers to purchase healthier items. At 12 weeks we will assess whether participants have continued to follow the assigned diet. The primary outcome is the difference between groups in the change in Patient Health Questionnaire-9 (PHQ-9) score from baseline to 6 weeks. PHQ-9 will be measured at weeks 2, 4, 6 and 12. The secondary outcomes are the differences between groups in the change in remission of depression, change in anxiety score, functioning ability, quality of life, cognitive performance, reward sensitivity, and anhedonia from baseline to 6 and 12 weeks. We will also assess whether changes in reward sensitivity, anhedonia, cortisol awakening response and gut microbiome may explain any changes in depression severity. DISCUSSION: This study will test whether a ketogenic diet is an effective intervention to reduce the severity of depression, anxiety and improve quality of life and functioning ability for people with treatment-resistant depression.
How 'blended' is blended learning?: students' perceptions of issues around the integration of online and face-to-face learning in a Continuing Professional Development (CPD) health care context.
PurposeThis paper explores students' perceptions of blended learning modules delivered in a Continuing Professional Development (CPD) health care context in the UK. 'Blended learning' is the term used to describe a hybrid model of learning where traditional face-to-face teaching approaches and newer electronic learning activities and resources are utilised together.MethodA new model of CPD for health care practitioners based on a blended learning approach was developed at a university in the south west of England. As part of the evaluation of the new modules, a qualitative study was conducted, in which 17 students who had experienced the modules were interviewed by telephone.ResultsThree main themes emerged from the interviews relating to the 'blended' nature of the blended learning modules. These were i) issues around the opportunities for discussion of online materials face-to-face; ii) issues of what material should be online versus face-to-face and iii) balancing online and face-to-face components.ConclusionTeaching staff engaged in the development of blended learning courses need to pay particular attention to the ways in which they develop and integrate online and face-to-face materials. More attention needs to be paid to allowing opportunity for students to come together to create a 'community of inquiry'.
A multimethod approach to the evaluation of community preschool speech and language therapy provision.
ObjectivesThe paper presents a research study investigating the effectiveness and acceptability of community speech and language therapy provision for preschool children with early speech/language delays. As a 'worked example', it demonstrates the value of a multimethod approach to evaluation.MethodsThe paper examines how the research findings of a pragmatic randomized controlled trial (RCT), a survey questionnaire and qualitative in-depth interviews, which were the methods used in the evaluation, overlap and complement each other.ResultsThere was little evidence to establish the effectiveness of the speech and language therapy provided in the trial. This lack of difference was reflected in responses of parents to items on the questionnaire. The findings of the RCT, questionnaire and interviews all cast considerable doubt on the prospect of spontaneous resolution of the children's difficulties. Although the RCT showed few differences between the children allocated to immediate therapy or 'watchful waiting', the questionnaire and interviews revealed the circumstances in which the parents felt that these intervention strategies had been acceptable and unacceptable.ConclusionsAlthough the trial provided information about the progress of the children, the questionnaire and interview components highlighted the advantages and limitations of the intervention from the viewpoint of parents, thereby helping to explain the RCT findings. Thus, the study demonstrates how a multimethod approach to evaluation can yield useful information to explain the findings of RCTs.