Use of record-linkage to handle non-response and improve alcohol consumption estimates in health survey data: a study protocol

<p>Introduction: Reliable estimates of health-related behaviours, such as levels of alcohol consumption in the population, are required to formulate and evaluate policies. National surveys provide such data; validity depends on generalisability, but this is threatened by declining response levels. Attempts to address bias arising from non-response are typically limited to survey weights based on sociodemographic characteristics, which do not capture differential health and related behaviours within categories. This project aims to explore and address non-response bias in health surveys with a focus on alcohol consumption.</p> <p>Methods and analysis: The Scottish Health Surveys (SHeS) aim to provide estimates representative of the Scottish population living in private households. Survey data of consenting participants (92% of the achieved sample) have been record-linked to routine hospital admission (Scottish Morbidity Records (SMR)) and mortality (from National Records of Scotland (NRS)) data for surveys conducted in 1995, 1998, 2003, 2008, 2009 and 2010 (total adult sample size around 40 000), with maximum follow-up of 16 years. Also available are census information and SMR/NRS data for the general population. Comparisons of alcohol-related mortality and hospital admission rates in the linked SHeS-SMR/NRS with those in the general population will be made. Survey data will be augmented by quantification of differences to refine alcohol consumption estimates through the application of multiple imputation or inverse probability weighting. The resulting corrected estimates of population alcohol consumption will enable superior policy evaluation. An advanced weighting procedure will be developed for wider use.</p> <p>Ethics and dissemination: Ethics approval for SHeS has been given by the National Health Service (NHS) Multi-Centre Research Ethics Committee and use of linked data has been approved by the Privacy Advisory Committee to the Board of NHS National Services Scotland and Registrar General. Funding has been granted by the MRC. The outputs will include four or five public health and statistical methodological international journal and conference papers.</p&gt

Assessing the Representativeness of Population-Sampled Health Surveys Through Linkage to Administrative Data on Alcohol-Related Outcomes

Health surveys are an important resource for monitoring population health, but selective nonresponse may impede valid inference. This study aimed to assess nonresponse bias in a population-sampled health survey in Scotland, with a focus on alcohol-related outcomes. Nonresponse bias was assessed by examining whether rates of alcohol-related harm (i.e., hospitalization or death) and all-cause mortality among respondents to the Scottish Health Surveys (from 1995 to 2010) were equivalent to those in the general population, and whether the extent of any bias varied according to sociodemographic attributes or over time. Data from consenting respondents (aged 20–64 years) to 6 Scottish Health Surveys were confidentially linked to death and hospitalization records and compared with general population counterparts. Directly age-standardized incidence rates of alcohol-related harm and all-cause mortality were lower among Scottish Health Survey respondents compared with the general population. For all years combined, the survey-to-population rate ratios were 0.69 (95% confidence interval: 0.61, 0.76) for the incidence of alcohol-related harm and 0.89 (95% confidence interval: 0.83, 0.96) for all-cause mortality. Bias was more pronounced among persons residing in more deprived areas; limited evidence was found for regional or temporal variation. This suggests that corresponding underestimation of population rates of alcohol consumption is likely to be socially patterne

Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK

Background: To determine the extent and nature of changes associated with COVID-19 infection in terms of healthcare utilisation, this study observed healthcare contact 1 to 4 and 5 to 24 weeks following a COVID-19 diagnosis compared to propensity-matched controls. Methods: Two hundred forty nine thousand three hundred ninety Welsh individuals with a positive reverse transcription–polymerase chain reaction (RT-PCR) test were identified from data from national PCR test results. After elimination criteria, 98,600 positive individuals were matched to test negative and never tested controls using propensity matching. Cohorts were split on test location. Tests could be taken in either the hospital or community. Controls were those who had tested negative in their respective environments. Survival analysis was utilised for first clinical outcomes which are grouped into primary and secondary. Primary outcomes include post-viral-illness and fatigue as an indication of long-COVID. Secondary outcomes include clinical terminology concepts for embolism, respiratory conditions, mental health conditions, fit notes, or hospital attendance. Increased instantaneous risk for positive individuals was quantified using hazard ratios (HR) from Cox regression, while absolute risk (AR) and relative risk were quantified using life table analysis. Results: Analysis was conducted using all individuals and stratified by test location. Cases are compared to controls from the same test location. Fatigue (HR: 1.77, 95% CI: 1.34–2.25, p = < 0.001) and embolism (HR: 1.50, 95% CI: 1.15–1.97, p = 0.003) were more likely to occur in all positive individuals in the first 4 weeks; however, anxiety and depression (HR: 0.83, 95% CI: 0.73–0.95, p = 0.007) were less likely. Positive individuals continued to be more at risk of fatigue (HR: 1.47, 95% CI: 1.24–1.75, p = < 0.001) and embolism (HR: 1.51, 95% CI: 1.13–2.02, p = 0.005) after 4 weeks. All positive individuals are also at greater risk of post-viral illness (HR: 4.57, 95% CI: 1.77–11.80, p = 0.002). Despite statistical association between testing positive and several conditions, life table analysis shows that only a small minority of the study population were affected. Conclusions: Community COVID-19 disease is associated with increased risks of post-viral-illness, fatigue, embolism, and respiratory conditions. Despite elevated risks, the absolute healthcare burden is low. Subsequently, either very small proportions of people experience adverse outcomes following COVID-19 or they are not presenting to healthcare

Association between individual level characteristics and take-up of a Minimum Income Guarantee for Pensioners: Panel Data Analysis using data from the British Household Panel survey 1999–2002

\ua9 2024 The AuthorsA Minimum Income Guarantee (MIG) ensures people have a minimum amount of income for essentials such as healthy food, housing, health care, social and digital networks to support health and well-being. MIGs could be a useful tool to reduce inequalities. A MIG will only be effective if those who are eligible take it up. The aim of this paper is to explore how individual characteristics were associated with take-up of a MIG for pensioners (aged 60+ for women and aged 65+ for men) in England. The data used is from the British Household Panel Survey including 9430 observations from 1893 people, from 1999 to 2002. We estimated a random effects logistic regression. Results show that women were less likely to claim than men (OR ranging from 0.17 [95% CI 0.10–0.29]-0.73 [95% CI 0.40–1.34]), and couples were less likely to claim (OR ranging from 0.04 [95% CI 0.03–0.06]-0.01 [95%CI 0.01–0.02]) than single person households. People with better mental health (OR 1.05 95% CI 1.02–1.08), older pensioners (75+) (OR ranging from 1.98 [95% CI 1.52–2.59]-2.81 [95%CI 2.16–3.67]), those who were registered disabled (OR 4.03 95% CI 2.50–6.52), and those with no formal qualification (OR ranging from 1.74 [95%CI 0.93–3.26]-2.07 [95% CI 1.22–3.51]) were more likely to claim. Understanding who is likely to claim MIGs is important to avoid social security policy inadvertently increasing inequalities

Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK

Background: To determine the extent and nature of changes associated with COVID-19 infection in terms of healthcare utilisation, this study observed healthcare contact 1 to 4 and 5 to 24 weeks following a COVID-19 diagnosis compared to propensity-matched controls. Methods: Two hundred forty nine thousand three hundred ninety Welsh individuals with a positive reverse transcription–polymerase chain reaction (RT-PCR) test were identified from data from national PCR test results. After elimination criteria, 98,600 positive individuals were matched to test negative and never tested controls using propensity matching. Cohorts were split on test location. Tests could be taken in either the hospital or community. Controls were those who had tested negative in their respective environments. Survival analysis was utilised for first clinical outcomes which are grouped into primary and secondary. Primary outcomes include post-viral-illness and fatigue as an indication of long-COVID. Secondary outcomes include clinical terminology concepts for embolism, respiratory conditions, mental health conditions, fit notes, or hospital attendance. Increased instantaneous risk for positive individuals was quantified using hazard ratios (HR) from Cox regression, while absolute risk (AR) and relative risk were quantified using life table analysis. Results: Analysis was conducted using all individuals and stratified by test location. Cases are compared to controls from the same test location. Fatigue (HR: 1.77, 95% CI: 1.34–2.25, p = &lt; 0.001) and embolism (HR: 1.50, 95% CI: 1.15–1.97, p = 0.003) were more likely to occur in all positive individuals in the first 4 weeks; however, anxiety and depression (HR: 0.83, 95% CI: 0.73–0.95, p = 0.007) were less likely. Positive individuals continued to be more at risk of fatigue (HR: 1.47, 95% CI: 1.24–1.75, p = &lt; 0.001) and embolism (HR: 1.51, 95% CI: 1.13–2.02, p = 0.005) after 4 weeks. All positive individuals are also at greater risk of post-viral illness (HR: 4.57, 95% CI: 1.77–11.80, p = 0.002). Despite statistical association between testing positive and several conditions, life table analysis shows that only a small minority of the study population were affected. Conclusions: Community COVID-19 disease is associated with increased risks of post-viral-illness, fatigue, embolism, and respiratory conditions. Despite elevated risks, the absolute healthcare burden is low. Subsequently, either very small proportions of people experience adverse outcomes following COVID-19 or they are not presenting to healthcare

Protocol for the development of guidance for stakeholder engagement in health and healthcare guideline development and implementation

Stakeholder engagement has become widely accepted as a necessary component of guideline development and implementation. While frameworks for developing guidelines express the need for those potentially affected by guideline recommendations to be involved in their development, there is a lack of consensus on how this should be done in practice. Further, there is a lack of guidance on how to equitably and meaningfully engage multiple stakeholders. We aim to develop guidance for the meaningful and equitable engagement of multiple stakeholders in guideline development and implementation. METHODS: This will be a multi-stage project. The first stage is to conduct a series of four systematic reviews. These will (1) describe existing guidance and methods for stakeholder engagement in guideline development and implementation, (2) characterize barriers and facilitators to stakeholder engagement in guideline development and implementation, (3) explore the impact of stakeholder engagement on guideline development and implementation, and (4) identify issues related to conflicts of interest when engaging multiple stakeholders in guideline development and implementation. DISCUSSION: We will collaborate with our multiple and diverse stakeholders to develop guidance for multi-stakeholder engagement in guideline development and implementation. We will use the results of the systematic reviews to develop a candidate list of draft guidance recommendations and will seek broad feedback on the draft guidance via an online survey of guideline developers and external stakeholders. An invited group of representatives from all stakeholder groups will discuss the results of the survey at a consensus meeting which will inform the development of the final guidance papers. Our overall goal is to improve the development of guidelines through meaningful and equitable multi-stakeholder engagement, and subsequently to improve health outcomes and reduce inequities in health

Household overcrowding and risk of SARS-CoV-2: analysis of the Virus Watch prospective community cohort study in England and Wales

Background: Household overcrowding is associated with increased risk of infectious diseases across contexts and countries. Limited data exist linking household overcrowding and risk of COVID-19. We used data collected from the Virus Watch cohort to examine the association between overcrowded households and SARS-CoV-2. // Methods: The Virus Watch study is a household community cohort of acute respiratory infections in England and Wales. We calculated overcrowding using the measure of persons per room for each household. We considered two primary outcomes: PCR-confirmed positive SARS-CoV-2 antigen tests and laboratory-confirmed SARS-CoV-2 antibodies. We used mixed-effects logistic regression models that accounted for household structure to estimate the association between household overcrowding and SARS-CoV-2 infection. // Results: 26,367 participants were included in our analyses. The proportion of participants with a positive SARS-CoV-2 PCR result was highest in the overcrowded group (9.0%; 99/1,100) and lowest in the under-occupied group (4.2%; 980/23,196). In a mixed-effects logistic regression model, we found strong evidence of an increased odds of a positive PCR SARS-CoV-2 antigen result (odds ratio 2.45; 95% CI:1.43–4.19; p-value=0.001) and increased odds of a positive SARS-CoV-2 antibody result in individuals living in overcrowded houses (3.32; 95% CI:1.54–7.15; p-value<0.001) compared with people living in under-occupied houses. // Conclusion: Public health interventions to prevent and stop the spread of SARS-CoV-2 should consider the risk of infection for people living in overcrowded households and pay greater attention to reducing household transmission

Studying the Long-term Impact of COVID-19 in Kids (SLICK). Healthcare use and costs in children and young people following community-acquired SARS-CoV-2 infection:protocol for an observational study using linked primary and secondary routinely collected healthcare data from England, Scotland and Wales

IntroductionSARS-CoV-2 infection rarely causes hospitalisation in children and young people (CYP), but mild or asymptomatic infections are common. Persistent symptoms following infection have been reported in CYP but subsequent healthcare use is unclear. We aim to describe healthcare use in CYP following community-acquired SARS-CoV-2 infection and identify those at risk of ongoing healthcare needs.Methods and analysisWe will use anonymised individual-level, population-scale national data linking demographics, comorbidities, primary and secondary care use and mortality between 1 January 2019 and 1 May 2022. SARS-CoV-2 test data will be linked from 1 January 2020 to 1 May 2022. Analyses will use Trusted Research Environments: OpenSAFELY in England, Secure Anonymised Information Linkage (SAIL) Databank in Wales and Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 in Scotland (EAVE-II). CYP aged ≥4 and &lt;18 years who underwent SARS-CoV-2 reverse transcription PCR (RT-PCR) testing between 1 January 2020 and 1 May 2021 and those untested CYP will be examined.The primary outcome measure is cumulative healthcare cost over 12 months following SARS-CoV-2 testing, stratified into primary or secondary care, and physical or mental healthcare. We will estimate the burden of healthcare use attributable to SARS-CoV-2 infections in the 12 months after testing using a matched cohort study of RT-PCR positive, negative or untested CYP matched on testing date, with adjustment for confounders. We will identify factors associated with higher healthcare needs in the 12 months following SARS-CoV-2 infection using an unmatched cohort of RT-PCR positive CYP. Multivariable logistic regression and machine learning approaches will identify risk factors for high healthcare use and characterise patterns of healthcare use post infection.Ethics and disseminationThis study was approved by the South-Central Oxford C Health Research Authority Ethics Committee (13/SC/0149). Findings will be preprinted and published in peer-reviewed journals. Analysis code and code lists will be available through public GitHub repositories and OpenCodelists with meta-data via HDR-UK Innovation Gateway

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background: Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods: Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (>= 65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0-100 based on the 2.5th and 97.5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target-1 billion more people benefiting from UHC by 2023-we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings: Globally, performance on the UHC effective coverage index improved from 45.8 (95% uncertainty interval 44.2-47.5) in 1990 to 60.3 (58.7-61.9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2.6% [1.9-3.3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010-2019 relative to 1990-2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0.79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388.9 million (358.6-421.3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3.1 billion (3.0-3.2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968.1 million [903.5-1040.3]) residing in south Asia. Interpretation: The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people-the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close-or how far-all populations are in benefiting from UHC