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The Centre for Evidence-Based Medicine (CEBM) at Oxford University develops, promotes and disseminates better evidence for health care.
How can NHS trusts in England optimise strategies to improve the mental health and well-being of hospital doctors? The Care Under Pressure 3 (CUP3) realist evaluation study protocol
INTRODUCTION: The growing incidence of mental ill health in doctors was a major issue in the UK and internationally, even prior to the COVID-19 pandemic. It has significant and far-reaching implications, including poor quality or inconsistent patient care, absenteeism, workforce attrition and retention issues, presenteeism, and increased risk of suicide. Existing approaches to workplace support do not take into account the individual, organisational and social factors contributing to mental ill health in doctors, nor how interventions/programmes might interact with each other within the workplace. The aim of this study is to work collaboratively with eight purposively selected National Health Service (NHS) trusts within England to develop an evidence-based implementation toolkit for all NHS trusts to reduce doctors' mental ill health and its impacts on the workforce. METHODS AND ANALYSIS: The project will incorporate three phases. Phase 1 develops a typology of interventions to reduce doctors' mental ill health. Phase 2 is a realist evaluation of the existing combinations of strategies being used by acute English healthcare trusts to reduce doctors' mental ill health (including preventative promotion of well-being), based on 160 interviews with key stakeholders. Phase 3 synthesises the insights gained through phases 1 and 2, to create an implementation toolkit that all UK healthcare trusts can use to optimise their strategies to reduce doctors' mental ill health and its impact on the workforce and patient care. ETHICS AND DISSEMINATION: Ethical approval has been granted for phase 2 of the project from the NHS Research Ethics Committee (REC reference number 22/WA/0352). As part of the conditions for our ethics approval, the sites included in our study will remain anonymous. To ensure the relevance of the study's outputs, we have planned a wide range of dissemination strategies: an implementation toolkit for healthcare leaders, service managers and doctors; conventional academic outputs such as journal manuscripts and conference presentations; plain English summaries; cartoons and animations; and a media engagement campaign.
Preventable deaths involving opioids in England and Wales, 2013-2022: a systematic case series of coroners' reports.
BACKGROUND: Opioid deaths have increased in England and Wales. Coroners' Prevention of Future Deaths reports (PFDs) provide important insights that may enable safer use and avert harms, yet reports implicating opioids have not been synthesized. We aimed to identify opioid-related PFDs and explore coroners' concerns to prevent future deaths. METHODS: In this systematic case series, we screened 3897 coronial PFDs dated between 01 July 2013 and 23 February 2022, obtained by web scraping the UK's Courts and Tribunals Judiciary website. PFDs were included when an opioid was implicated in the death. Included PFDs were descriptively analysed, and content analysis was used to assess concerns reported by coroners. RESULTS: Opioids were involved in 219 deaths reported in PFDs (5·6% of PFDs), equating to 4418 years of life lost (median 33 years/person). Morphine (29%), methadone (23%) and diamorphine (16%) were the most common implicated opioids. Coroners most frequently raised concerns regarding systems and protocols (52%) or safety issues (15%). These concerns were most often addressed to National Health Service (NHS) organizations (51%), but response rates were low overall (47%). CONCLUSIONS: Opioids could be used more safely if coroners' concerns in PFDs were addressed by national organizations such as NHS bodies, government agencies and policymakers, as well as individual prescribing clinicians.
Selling antibiotics without prescriptions among community pharmacies and drug outlets: a simulated client study from Ghana
Background: Selling antibiotics without prescriptions is mostly illegal worldwide, including in Ghana, and promotes antimicrobial resistance. We evaluated the prevalence and practice of selling antibiotics without prescriptions among community pharmacies (CPs) and drug outlets, for the first time, in Ghana to quantify and characterize this issue to inform future interventions. Research design and methods: Two scenarios utilizing the Simulated Client Methodology were enacted: an upper respiratory tract infection of viral origin (scenario one); and pediatric diarrhea (scenario two). CPs/Outlets were selected by stratified proportional random sampling from four metropolitan cities (~14% of the total Ghanaian population). Selling of antibiotics was assessed at three demand levels and its overall prevalence was estimated, then stratified by the study variables. Results: Out of the 265 sampled CPs/outlets, the prevalence of selling antibiotic without prescription was 88.3% (n = 234/265), with variations not only across the four regions [92.5% (n = 123/133) in Kumasi, 87.5% (n = 14/16) in Cape Coast, 84.1% (n = 69/82) in Accra, and 82.4% (n = 28/34) in Tamale] but also across CPs [90% (n = 121/134)] and drug outlets [86% (n = 113/131)]. Conclusions: A very high prevalence/sub-optimal practice of selling antibiotics without prescriptions was found. This highlights the need to increase compliance with antibiotic dispensing legislation through evidence-based interventions including education of key stakeholders.
Dissemination of Registered COVID-19 Clinical Trials (DIRECCT): a cross-sectional study.
BACKGROUND: The results of clinical trials should be completely and rapidly reported during public health emergencies such as COVID-19. This study aimed to examine when, and where, the results of COVID-19 clinical trials were disseminated throughout the first 18 months of the pandemic. METHODS: Clinical trials for COVID-19 treatment or prevention were identified from the WHO ICTRP database. All interventional trials with a registered completion date ≤ 30 June 2021 were included. Trial results, published as preprints, journal articles, or registry results, were located using automated and manual techniques across PubMed, Google Scholar, Google, EuropePMC, CORD-19, the Cochrane COVID-19 Study Register, and clinical trial registries. Our main analysis reports the rate of dissemination overall and per route, and the time from registered completion to results using Kaplan-Meier methods, with additional subgroup and sensitivity analyses reported. RESULTS: Overall, 1643 trials with completion dates ranging from 46 to 561 days prior to the start of results searches were included. The cumulative probability of reporting was 12.5% at 3 months from completion, 21.6% at 6 months, and 32.8% at 12 months. Trial results were most commonly disseminated in journals (n = 278 trials, 69.2%); preprints were available for 194 trials (48.3%), 86 (44.3%) of which converted to a full journal article. Trials completed earlier in the pandemic were reported more rapidly than those later in the pandemic, and those involving ivermectin were more rapidly reported than other common interventions. Results were robust to various sensitivity analyses except when considering only trials in a "completed" status on the registry, which substantially increased reporting rates. Poor trial registry data on completion status and dates limits the precision of estimates. CONCLUSIONS: COVID-19 trials saw marginal increases in reporting rates compared to standard practice; most registered trials failed to meet even the 12-month non-pandemic standard. Preprints were common, complementing journal publication; however, registries were underutilized for rapid reporting. Maintaining registry data enables accurate representation of clinical research; failing to do so undermines these registries' use for public accountability and analysis. Addressing rapid reporting and registry data quality must be emphasized at global, national, and institutional levels.
Estimating the effect of COVID-19 on trial design characteristics: A registered report
There have been reports of poor-quality research during the COVID-19 pandemic. This registered report assessed design characteristics of registered clinical trials for COVID-19 compared to non-COVID-19 trials to empirically explore the design of clinical research during a pandemic and how it compares to research conducted in non-pandemic times. We did a retrospective cohort study with a 1: 1 ratio of interventional COVID-19 registrations to non-COVID-19 registrations, with four trial design outcomes: use of control arm, randomization, blinding and prospective registration. Logistic regression was used to estimate the odds ratio of investigating COVID-19 versus not COVID-19 and estimate direct and total effects of investigating COVID-19 for each outcome. The primary analysis showed a positive direct and total effect of COVID-19 on the use of control arms and randomization. It showed a negative direct effect of COVID-19 on blinding but no evidence of a total effect. There was no evidence of an effect on prospective registration. Taken together with secondary and sensitivity analyses, our findings are inconclusive but point towards a higher prevalence of key design characteristics in COVID-19 trials versus controls. The findings do not support much existing COVID-19 research quality literature, which generally suggests that COVID-19 led to a reduction in quality. Limitations included some data quality issues, minor deviations from the pre-registered plan and the fact that trial registrations were analysed which may not accurately reflect study design and conduct. Following in-principle acceptance, the approved stage 1 version of this manuscript was pre-registered on the Open Science Framework at https://doi.org/10.17605/OSF.IO/5YAEB. This pre-registration was performed prior to data analysis.
The Open Science Framework at Oxford
The Bodleian Libraries, in partnership with MSD, are operating a 2 year pilot of institutional membership of the Open Science Framework at (OSF) Oxford. This session will begin an overview of the Open Science Framework and how it fits into Oxford’s wider Research Data Management ecosystem. This will be followed by some researchers at Oxford presenting their experiences with OSF.
Completeness and consistency of primary outcome reporting in COVID-19 publications in the early pandemic phase: a descriptive study
Background: The COVID-19 pandemic saw a steep increase in the number of rapidly published scientific studies, especially early in the pandemic. Some have suggested COVID-19 trial reporting is of lower quality than typical reports, but there is limited evidence for this in terms of primary outcome reporting. The objective of this study was to assess the prevalence of completely defined primary outcomes reported in registry entries, preprints, and journal articles, and to assess consistent primary outcome reporting between these sources. Methods: This is a descriptive study of a cohort of registered interventional clinical trials for the treatment and prevention of COVID-19, drawn from the DIssemination of REgistered COVID-19 Clinical Trials (DIRECCT) study dataset. The main outcomes are: 1) Prevalence of complete primary outcome reporting; 2) Prevalence of consistent primary outcome reporting between registry entry and preprint as well as registry entry and journal article pairs. Results: We analyzed 87 trials with 116 corresponding publications (87 registry entries, 53 preprints and 63 journal articles). All primary outcomes were completely defined in 47/87 (54%) registry entries, 31/53 (58%) preprints and 44/63 (70%) journal articles. All primary outcomes were consistently reported in 13/53 (25%) registry-preprint pairs and 27/63 (43%) registry-journal article pairs. No primary outcome was specified in 13/53 (25%) preprints and 8/63 (13%) journal articles. In this sample, complete primary outcome reporting occurred more frequently in trials with vs. without involvement of pharmaceutical companies (76% vs. 45%), and in RCTs vs. other study designs (68% vs. 49%). The same pattern was observed for consistent primary outcome reporting (with vs. without pharma: 56% vs. 12%, RCT vs. other: 43% vs. 22%). Conclusions: In COVID-19 trials in the early phase of the pandemic, all primary outcomes were completely defined in 54%, 58%, and 70% of registry entries, preprints and journal articles, respectively. Only 25% of preprints and 43% of journal articles reported primary outcomes consistent with registry entries.
Optimising process and methods for a living systematic review - 30 search updates and three review updates later.
Living systematic reviews (LSR) are systematic reviews that are regularly updated, allowing new evidence to be incorporated as it becomes available. LSR are ideally suited to policy-relevant topics where there is uncertainty and new evidence will likely impact the interpretation and/or certainty of outcomes. To be of benefit, updates must be published in a timely manner. Many LSR do not publish more than one update. As authors of a systematic review that has been 'living' for two years, with monthly search updates and three full updates published in this time, we describe the steps in our LSR process with the aim of informing and assisting authors carrying out their own regularly updated LSR. Key features of the process that require consideration are as follows: specifying the frequency of searches and triggers for full updates in the protocol; stakeholder input; publishing and disseminating monthly search findings. A strong team, incorporating methodological and topic expertise, with core members that meet regularly is essential. Regular search updates make it important to have a clear cyclical schedule of activity. To achieve timely updates this process should be streamlined, for example, using automated monthly searches, and systematic reviewing software for screening. LSR provide a unique opportunity to incorporate stakeholder feedback; as soon as a review update is complete you may be planning your next, and can incorporate useful feedback. We suggest seeking feedback on your findings and methods and, where appropriate, incorporating them with transparency.
Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform
Background: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. Methods: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. Findings: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. Interpretation: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. Funding: LSHTM COVID-19 Response Grant ( DONAT15912).
Trends, variation, and clinical characteristics of recipients of antiviral drugs and neutralising monoclonal antibodies for covid-19 in community settings: retrospective, descriptive cohort study of 23.4 million people in OpenSAFELY.
OBJECTIVE: To ascertain patient eligibility status and describe coverage of antiviral drugs and neutralising monoclonal antibodies (nMAB) as treatment for covid-19 in community settings in England. DESIGN: Retrospective, descriptive cohort study, approved by NHS England. SETTING: Routine clinical data from 23.4 million people linked to data on covid-19 infection and treatment, within the OpenSAFELY-TPP database. PARTICIPANTS: Outpatients with covid-19 at high risk of severe outcomes. INTERVENTIONS: Nirmatrelvir/ritonavir (paxlovid), sotrovimab, molnupiravir, casirivimab/imdevimab, or remdesivir, used in the community by covid-19 medicine delivery units. RESULTS: 93 870 outpatients with covid-19 were identified between 11 December 2021 and 28 April 2022 to be at high risk of severe outcomes and therefore potentially eligible for antiviral or nMAB treatment (or both). Of these patients, 19 040 (20%) received treatment (sotrovimab, 9660 (51%); molnupiravir, 4620 (24%); paxlovid, 4680 (25%); casirivimab/imdevimab, 50 (<1%); and remdesivir, 30 (<1%)). The proportion of patients treated increased from 9% (190/2220) in the first week of treatment availability to 29% (460/1600) in the latest week. The proportion treated varied by high risk group, being lowest in those with liver disease (16%; 95% confidence interval 15% to 17%); by treatment type, with sotrovimab favoured over molnupiravir and paxlovid in all but three high risk groups (Down's syndrome (35%; 30% to 39%), rare neurological conditions (45%; 43% to 47%), and immune deficiencies (48%; 47% to 50%)); by age, ranging from ≥80 years (13%; 12% to 14%) to 50-59 years (23%; 22% to 23%); by ethnic group, ranging from black (11%; 10% to 12%) to white (21%; 21% to 21%); by NHS region, ranging from 13% (12% to 14%) in Yorkshire and the Humber to 25% (24% to 25%) in the East of England); and by deprivation level, ranging from 15% (14% to 15%) in the most deprived areas to 23% (23% to 24%) in the least deprived areas. Groups that also had lower coverage included unvaccinated patients (7%; 6% to 9%), those with dementia (6%; 5% to 7%), and care home residents (6%; 6% to 7%). CONCLUSIONS: Using the OpenSAFELY platform, we were able to identify patients with covid-19 at high risk of severe outcomes who were potentially eligible to receive treatment and assess the coverage of these new treatments among these patients. In the context of a rapid deployment of a new service, the NHS analytical code used to determine eligibility could have been over-inclusive and some of the eligibility criteria not fully captured in healthcare data. However targeted activity might be needed to resolve apparent lower treatment coverage observed among certain groups, in particular (at present): different NHS regions, ethnic groups, people aged ≥80 years, those living in socioeconomically deprived areas, and care home residents.