IntroductionThe novel coronavirus SARS-CoV-2, which emerged in December 2019, has caused millions of deaths and severe illness worldwide. Numerous vaccines are currently under development of which a ...few have now been authorised for population-level administration by several countries. As of 20 September 2021, over 48 million people have received their first vaccine dose and over 44 million people have received their second vaccine dose across the UK. We aim to assess the uptake rates, effectiveness, and safety of all currently approved COVID-19 vaccines in the UK.Methods and analysisWe will use prospective cohort study designs to assess vaccine uptake, effectiveness and safety against clinical outcomes and deaths. Test-negative case–control study design will be used to assess vaccine effectiveness (VE) against laboratory confirmed SARS-CoV-2 infection. Self-controlled case series and retrospective cohort study designs will be carried out to assess vaccine safety against mild-to-moderate and severe adverse events, respectively. Individual-level pseudonymised data from primary care, secondary care, laboratory test and death records will be linked and analysed in secure research environments in each UK nation. Univariate and multivariate logistic regression models will be carried out to estimate vaccine uptake levels in relation to various population characteristics. VE estimates against laboratory confirmed SARS-CoV-2 infection will be generated using a generalised additive logistic model. Time-dependent Cox models will be used to estimate the VE against clinical outcomes and deaths. The safety of the vaccines will be assessed using logistic regression models with an offset for the length of the risk period. Where possible, data will be meta-analysed across the UK nations.Ethics and disseminationWe obtained approvals from the National Research Ethics Service Committee, Southeast Scotland 02 (12/SS/0201), the Secure Anonymised Information Linkage independent Information Governance Review Panel project number 0911. Concerning English data, University of Oxford is compliant with the General Data Protection Regulation and the National Health Service (NHS) Digital Data Security and Protection Policy. This is an approved study (Integrated Research Application ID 301740, Health Research Authority (HRA) Research Ethics Committee 21/HRA/2786). The Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub meets NHS Digital’s Data Security and Protection Toolkit requirements. In Northern Ireland, the project was approved by the Honest Broker Governance Board, project number 0064. Findings will be made available to national policy-makers, presented at conferences and published in peer-reviewed journals.
Trusted Research Environments provide a legitimate basis for data access along with a set of technologies to support implementation of the "five-safes" framework for privacy protection. Lack of ...standard approaches in achieving compliance with the "five-safes" framework results in a diversity of approaches across different TREs. Data access and analysis across multiple TREs has a range of benefits including improved precision of analysis due to larger sample sizes and broader availability of out-of-sample records, particularly in the study of rare conditions. Knowledge of governance approaches used across UK-TREs is limited.
To document key governance features in major UK-TRE contributing to UK wide analysis and to identify elements that would directly facilitate multi TRE collaborations and federated analysis in future.
We summarised three main characteristics across 15 major UK-based TREs: 1) data access environment; 2) data access requests and disclosure control procedures; and 3) governance models. We undertook case studies of collaborative analyses conducted in more than one TRE. We identified an array of TREs operating on an equivalent level of governance. We further identify commonly governed TREs with architectural considerations for achieving an equivalent level of information security management system standards to facilitate multi TRE functionality and federated analytics.
All 15 UK-TREs allow pooling and analysis of aggregated research outputs only when they have passed human-operated disclosure control checks. Data access requests procedures are unique to each TRE. We also observed a variability in disclosure control procedures across various TREs with no or minimal researcher guidance on best practices for file out request procedures. In 2023, six TREs (40.0%) held ISO 20071 accreditation, while 9 TREs (56.2%) participated in four-nation analyses.
Secure analysis of individual-level data from multiple TREs is possible through existing technical solutions but requires development of a well-established governance framework meeting all stakeholder requirements and addressing public and patient concerns. Formation of a standard model could act as the catalyst for evolution of current TREs governance models to a multi TRE ecosystem within the UK and beyond.
In developing countries, women are 3.5 times more likely than men to participate in unpaid work. As a traditionally patriarchal society, strict gender roles existed in Iran but there is no empirical ...evidence to show whether profound socio-economic and demographic changes in the society have altered these deep-rooted stratified gender roles. This paper uses data from the 2014-2015 Time Use Survey, conducted in the urban areas of Iran, to describe the spouses' division of household labour and determine the correlates of this division. The correlates are selected based on the relative resources and time availability approaches. The results suggest that wives are five times more likely than husbands to participate in the household labour, which is wider than the average gender gap observed in developing countries. The findings provide partial support for the relative resources and time availability approaches, with wives' experience being more consistent with these approaches. The existing profound gender gap in the division of household labour and its correlates suggests that in urban areas of Iran gender roles are defined beyond socio-economic and demographic attributes, at least on the individual level.
IntroductionCritical Care is a specialty in medicine providing a service for severely ill and high-risk patients who, due to the nature of their condition, may require long periods recovering after ...discharge. Consequently, focus on the routine data collection carried out in Intensive Care Units (ICUs) leads to reporting that is confined to the critical care episode and is typically insensitive to variation in individual patient pathways through critical care to recovery.
A resource which facilitates efficient research into interactions with healthcare services surrounding critical admissions, capturing the complete patient's healthcare trajectory from primary care to non-acute hospital care prior to ICU, would provide an important longer-term perspective for critical care research.
ObjectiveTo describe and apply a reproducible methodology that demonstrates how both routine administrative and clinically rich critical care data sources can be integrated with primary and secondary healthcare data to create a single dataset that captures a broader view of patient care.
MethodTo demonstrate the INTEGRATE methodology, it was applied to routine administrative and clinical healthcare data sources in the Secure Anonymised Data Linking (SAIL) Databank to create a dataset of patients' complete healthcare trajectory prior to critical care admission. SAIL is a national, data safe haven of anonymised linkable datasets about the population of Wales.
ResultsWhen applying the INTEGRATE methodology in SAIL, between 2010 and 2019 we observed 91,582 critical admissions for 76,019 patients. Of these, 90,632 (99%) had an associated non-acute hospital admission, 48,979 (53%) hadan emergency admission, and 64,832 (71%) a primary care interaction in the week prior to the critical care admission.
ConclusionThis methodology, at population scale, integrates two critical care data sources into a single dataset together with data sources on healthcare prior to critical admission, thus providing a key research asset to study critical care pathways.
The COVID-19 pandemic has placed a spotlight on existing and enduring health inequalities experienced by different ethnic groups. There has been a longstanding call to generate and improve the use of ...ethnicity data available across different data sources, in order to improve our understanding of health risks, behaviours and outcomes.
We used multiple anonymised individual-level population-scale data sources available within the Secure Anonymised Information Linkage (SAIL) Databank to develop a harmonised ethnicity spine for the population of Wales. We documented ethnicity information in multiple longitudinal records from January 2000 onwards. Data sources included: health and social care, birth and mortality records, national census records, specialist clinical audits and registers, surveys and other routine electronic data. To enable multi-source harmonisation, we explored the ethnicity categorisation as well as temporal changes in recording and classifications by obtaining distribution of records for population, which informed our harmonisation algorithm for standardisation of ethnicity records.
We used over 20-data sources on ~5-million individuals, spanning varying time-periods starting from January 2000 upto a maximum of 22-years. We harmonised available recorded ethnicity values into standardised ethnic classification groups within a national ethnicity-spine. Furthermore, we investigated the impact of different harmonisation methods, including composite, latest date of recording, modal and weighted modal results. With the main focus of the methodological development being in response to the COVID-19 pandemic, when linked to the ~3.1 million individuals alive and resident in Wales from January 2020, we generated harmonised ethnic groups towards ~95% completeness in data coverage for the whole population of Wales. The predominant ethnic group in Wales observed was White, accounting for 89% of the population when using the latest date of recording method.
This research highlights challenges in using longitudinal ethnicity data across different sources. Further work is needed to understand the basis on which individuals / organisations record ethnicity overtime. We recommend improvements recognising differences between ethnicity and other social constructs (e.g. ancestry, nationality, country of origin) are better documented / understood.
ObjectivesVarious analgesics are frequently prescribed to cancer patients for whom pain contributes to poor physical and emotional health and well-being. We examined changes in trends of analgesic ...prescribing in over 35,000 cancer patients diagnosed in the Welsh population before and during the COVID-19 pandemic in order to gain insight into the COVID-19 pandemic effects on cancer patients’ ability to receive analgesia and their potential ability to control their pain via medications.
ApproachWithin the Secure Anonymised Information Linkage (SAIL) Databank trusted research environment (TRE), patients diagnosed with incident primary breast, lung, colorectal or prostate cancers during 2017–2021 were obtained from Cancer Network Information System Cymru (CaNISC) dataset and patients’ prescription records were identified from Welsh Longitudinal General Practitioner (WLGP) dataset before being linked to their oncology e-record. We calculated opioid and non-opioid analgesic items prescribed per patient per year (PPPY) since cancer by clinical and demographic factors including cancer type, stage at diagnosis, diagnosis year, age at diagnosis, sex, comorbidities and patients’ socioeconomic status. These factors were included to model the effects of the COVID-19 pandemic on trends in analgesic prescribing for each cancer group.
ResultsWe detected significant differences in the number of analgesic items prescribed PPPY in patients diagnosed before the COVID-19 pandemic (2017–2019) and those during the pandemic (2020–2021), with 1.3 more items PPPY prescribed for the latter group (p<0.001). Differences were accounted for largely by prescriptions for lung cancer patients, having 2.74 more items PPPY prescribed (p<0.001), the highest among the four cancer types evaluated. Patients diagnosed with a late-stage cancer had significantly more items prescribed than patients diagnosed at an early stage (p<0.001), with stage IV patients having 15.7 opioid items PPPY prescribed. For patients diagnosed at stage I, this rate PPPY was 6.7. Significant differences were also identified between patients from different socioeconomic backgrounds (p<0.001), with patients from the most deprived areas prescribed 11.3 items PPPY, 5.8 more than those from the least deprived areas.
ConclusionsThe significant impact of COVID-19 pandemic on pain medication prescribing for cancer patients could be partly related to the impact of COVID-19 lockdowns on presentation, waiting lists and diagnosis timings, and access to healthcare for prescriptions after diagnosis. Explanatory factors revealed by this study can help inform policymakers and provide guidance in improving pain relief for cancer services.
Background and Aim: Total Knee Arthroplasty (TKA) aims to reduce the pain and improve the quality of life of patients with progressive osteoarthritis. When the indication of patientschr('39') disease ...is established, this type of surgery should be performed as soon as possible because patientschr('39') late attendance increases surgical complications. Therefore, identification of factors influencing the choice of this type of treatment approach is of great importance. The purpose of this study is to identify the factors that influence the choice of this treatment approach in patients using the Apriori algorithm in the form of Association Rules. Materials and Methods: This study is performed on 233 patients referring to Imam Khomeini Hospital in Tehran for a knee replacement surgery; the needed data have been registered at Bone and Joint Reconstruction Research Center. In this study, after the preprocessing stage, the important factors in decision making of knee replacement surgery have been identified by using the Apriori algorithm and by its implementation in the software environment of RStudio. After being extracted, these factors and the relationship among them are given to orthopedic practitioners for confirmation. Results: In this study, flexion contracture above 20 degrees, deformity (varous-valgus) above 15 degrees, final flexion between 51-75 degrees, and medial cartilage destruction were, respectively, the most important factors in selecting patients for knee replacement therapy. Conclusion: The results showed that data-mining Algorithms could be used to identify effective factors to select patients for this treatment approach.
IntroductionMonitoring social wellbeing and its relationship to health service utilisation by means of appropriate measurement tools can potentially provide a complementary view for influencing ...service development. Aspects of wellbeing have been collected in the Welsh Health Survey (WHS) while routine health data captures health service utilisation.
Objectives and ApproachWHS was used to link self-reported wellbeing to health outcomes, prior to linking to routinely collected data. Initially, a measure for personal wellbeing was developed using the four personal wellbeing questions defined by The Office of National Statistics (ONS), included in national surveys from 2011 onward. We conducted regression analysis to identify potential predictors of personal wellbeing scores our model included self-reported lifestyle behaviour, self-reported health, education, work, household and general demographics. Links to primary care, hospital and emergency department datasets are being developed to provide insight into the relationship between wellbeing, multi-morbidity and health service utilisation.
ResultsFour wellbeing questions had similar scoring patterns across age groups which is different to most health indicators that tend to show a marked health decline with increasing age. There is a difference between mean wellbeing score for males and females. Our finding showed that self-reported of ‘excellent’ or ‘very good’ general health has the largest positive effect on wellbeing while positive viewpoint on self-health has the second largest effect on our model. In addition, being retired from a paid job, eating at least one or 5+ portion of fruit and vegetables and giving up smoking have positive impact on population wellbeing. In contrast, not being able to work, intermediate household occupancy, consuming alcohol in last 12-months, having long-standing illness, showed a negative impact on wellbeing.
Conclusion/ImplicationsThis project established robust methodology on utilizing survey and routine health data for monitoring and evaluation purposes. We also evaluated the linkability of survey data The latest release of National Survey for Wales (NSW) will cover a combination of self-reported health measures and aims for a higher linkage consent rate.
Polycystic ovary syndrome (PCOS) is a common endocrine disease in women of reproduction age and a major cause of anovulatory infertility. Insulin resistance plays an important role in the development ...and durability of this disorder. ANGPTL2 is known as an inflammatory mediator derived from adipose tissue that links obesity to systemic insulin resistance, and obestatin has been identified as a hormone associated with insulin resistance that suppresses food reabsorption, inhibits gastric emptying and decreases weight gain. The aim of this study was to evaluate serum levels of ANGPTL2 and obestatin in PCOS women with normal body mass index (BMI).
In this case-control study, 26 PCOS women based on the Rotterdam 2003 diagnostic criteria as the case group and 26 women with normal menstrual cycles as the control group were enrolled. Serum levels of ANGPTL2, obestatin, insulin and other hormone factors related with PCOS were measured by ELISA method and biochemical parameters were measured by an autoanalyzer. Data were analyzed by independent samples-
test, Chi Square, Correlation and a single sample Kolmogrov⁻Smirnov test using SPSS software, version 16.
There were no significant variations in the amount of ANGPTL2, obestatin, cholesterol, low-density lipoprotein-cholesterol, high-density lipoprotein, cholesterol, creatinine and dehydroepiandrosterone-sulfate between the two groups. There were significant increases in serum levels of fasting blood sugar (
= 0.01), insulin (
= 0.04), homeostasis model assessments of insulin resistance (
= 0.04), testosterone (
= 0.02), luteinizing hormone (
= 0.004), luteinizing hormone/follicle stimulating hormone (
= 0.006) and prolactin (
= 0.04) in case group compared to the control group. A significant positive correlation was observed between ANGPTL2 and insulin (
= 0.02), HOMA-IR (
= 0.01) and, on the other hand, a significant negative correlation was observed between obestatin and insulin (
= 0.01), HOMA-IR (
= 0.008) in PCOS group.
In this study, no significant variations were observed in serum levels of ANGPTL2 and obestatin in PCOS women with normal BMI.
BackgroundMonitoring social wellbeing and its relationship to health service utilisation by means of appropriate measurement tools can provide a complementary view towards service development. Welsh ...Health Survey (WHS) collects aspects of wellbeing while routine health data captures details around health service utilisation.
ObjectiveThe aim of this project was to evaluate the linkage ability of routine health data with survey data and establish a methodology for utilizing survey data as a measure for self-reported health outcomes.
MethodWe used WHS data from UK data archive to link self-reported wellbeing to health outcomes, a measure for personal wellbeing was developed using the personal wellbeing questions defined by Office of National Statistics (ONS), included in national surveys from 2011 onward. WHS was then linked to routine health data using SAIL Databank. We conducted regression analysis to identify potential predictors of personal wellbeing by linking primary care, hospital and emergency department datasets, to develop and provide insight into the relationship between wellbeing, multi-morbidity and health service utilisation.
FindingsWellbeing questions had similar scoring patterns across age groups which is different to most health indicators that tend to show a marked health decline with increasing age. Our findings showed that self-reported of ‘excellent’ or ‘very good’general health has the largest positive effect on wellbeing while positive viewpoint on self-health has the second largest effect.
ConclusionsCombining and harmonising data from multiple sources and linking them to information from a longitudinal cohort create useful resources for population health research. These methods are reproducible and can be utilised by other researchersand projects.
PDF
