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INTRODUCTION: The COVID-19 pandemic has raised concerns about the persistence of symptoms after infection, commonly referred to as 'post-COVID' or 'long-COVID'. While countries in high-resource countries have highlighted the increased risk of disadvantaged communities, there is limited understanding of how COVID-19 and post-COVID conditions affect marginalised populations in low-income and middle-income countries. We study the longitudinal patterns of COVID-19, post-COVID symptoms and their impact on the health-related quality of life through the IndiQol Project. METHODS AND ANALYSIS: The IndiQol Project conducts household surveys across India to collect data on the incidence of COVID-19 and multidimensional well-being using a longitudinal design. We select a representative sample across six states surveyed over four waves. A two-stage sampling design was used to randomly select primary sampling units in rural and urban areas of each State. Using power analysis, we select an initial sample of 3000 household and survey all adult household members in each wave. The survey data will be analysed using limited dependent variable models and matching techniques to provide insights into the impact of COVID-19 pandemic and post-COVID on health and well-being of individuals in India. ETHICS AND DISSEMINATION: Ethics approval for the IndiQol Project was obtained from the Macquarie University Human Research Ethics Committee in Sydney, Australia and Institutional Review Board of Morsel in India. The project results will be published in peer-reviewed journals. Data collected from the IndiQol project will be deposited with the EuroQol group and will be available to use by eligible researchers on approval of request.
Subject(s)
COVID-19 , Quality of Life , SARS-CoV-2 , Humans , COVID-19/epidemiology , COVID-19/psychology , India/epidemiology , Longitudinal Studies , Adult , Research Design , Male , Female , Vulnerable Populations , PandemicsABSTRACT
PURPOSE: Decision models are time-consuming to develop; therefore, adapting previously developed models for new purposes may be advantageous. We provide methods to prioritize efforts to 1) update parameter values in existing models and 2) adapt existing models for distributional cost-effectiveness analysis (DCEA). METHODS: Methods exist to assess the influence of different input parameters on the results of a decision models, including value of information (VOI) and 1-way sensitivity analysis (OWSA). We apply 1) VOI to prioritize searches for additional information to update parameter values and 2) OWSA to prioritize searches for parameters that may vary by socioeconomic characteristics. We highlight the assumptions required and propose metrics that quantify the extent to which parameters in a model have been updated or adapted. We provide R code to quickly carry out the analysis given inputs from a probabilistic sensitivity analysis (PSA) and demonstrate our methods using an oncology case study. RESULTS: In our case study, updating 2 of 21 probabilistic model parameters addressed 71.5% of the total VOI and updating 3 addressed approximately 100% of the uncertainty. Our proposed approach suggests that these are the 3 parameters that should be prioritized. For model adaptation for DCEA, 46.3% of the total OWSA variation came from a single parameter, while the top 10 input parameters were found to account for more than 95% of the total variation, suggesting efforts should be aimed toward these. CONCLUSIONS: These methods offer a systematic approach to guide research efforts in updating models with new data or adapting models to undertake DCEA. The case study demonstrated only very small gains from updating more than 3 parameters or adapting more than 10 parameters. HIGHLIGHTS: It can require considerable analyst time to search for evidence to update a model or to adapt a model to take account of equity concerns.In this article, we provide a quantitative method to prioritze parameters to 1) update existing models to reflect potential new evidence and 2) adapt existing models to estimate distributional outcomes.We define metrics that quantify the extent to which the parameters in a model have been updated or adapted.We provide R code that can quickly rank parameter importance and calculate quality metrics using only the results of a standard probabilistic sensitivity analysis.
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INTRODUCTION: The aim of this study is to demonstrate a practical framework that can be applied to estimate the health impact of changes in waiting times across a range of elective procedures in the National Health Service (NHS) in England. We apply this framework by modeling 2 procedures: coronary artery bypass graft (CABG) and total hip replacement (THR). METHODS: We built a Markov model capturing health pre- and postprocedure, including the possibility of exiting preprocedure to acute NHS care or self-funded private care. We estimate the change in quality-adjusted life-years (QALYs) over a lifetime horizon for 10 subgroups defined by sex and Index of Multiple Deprivation quintile groups and for 7 alternative scenarios. We include 18 wk as a baseline waiting time consistent with current NHS policy. The model was populated with data from routinely collected data sets where possible (Hospital Episode Statistics, Patient-Reported Outcome Measures, and Office for National Statistics Mortality records), supplemented by the academic literature. RESULTS: Compared with 18 wk, increasing the wait time to 36 wk resulted in a mean discounted QALY loss in the range of 0.034 to 0.043 for CABG and 0.193 to 0.291 for THR. The QALY impact of longer NHS waits was greater for those living in more deprived areas, partly as fewer patients switch to private care. DISCUSSION/CONCLUSION: The proposed framework was applied to 2 different procedures and patient populations. If applied to an expanded group of procedures, it could provide decision makers with information to inform prioritization of waiting lists. There are a number of limitations in routine data on waiting for elective procedures, primarily the lack of information on people still waiting. HIGHLIGHTS: We present a modeling framework that allows for an estimation of the health impact (measured in quality-adjusted life-years) of waiting for elective procedures in the NHS in England.We apply our model to waiting for coronary artery bypass graft (CABG) and total hip replacement (THR). Increasing the wait for THR results in a larger health loss than an equivalent increase in wait for CABG.This model could potentially be used to estimate the impact across an expanded group of procedures to inform prioritization of activities to reduce waiting times.
Subject(s)
Arthroplasty, Replacement, Hip , Coronary Artery Bypass , Elective Surgical Procedures , Markov Chains , Quality-Adjusted Life Years , State Medicine , Waiting Lists , Humans , Arthroplasty, Replacement, Hip/statistics & numerical data , England , Coronary Artery Bypass/statistics & numerical data , Elective Surgical Procedures/statistics & numerical data , Male , Female , Aged , Middle AgedABSTRACT
BACKGROUND: People with serious mental illness are more likely to experience physical illnesses. The onset of many of these illnesses can be prevented if detected early. Physical health screening for people with serious mental illness is incentivised in primary care in England through the Quality and Outcomes Framework (QOF). GPs are paid to conduct annual physical health checks on patients with serious mental illness, including checks of body mass index (BMI), cholesterol, and alcohol consumption. AIM: To assess the impact of removing and reintroducing QOF financial incentives on uptake of three physical health checks (BMI, cholesterol, and alcohol consumption) for patients with serious mental illness. DESIGN AND SETTING: Cohort study using UK primary care data from the Clinical Practice Research Datalink between April 2011 and March 2020. METHOD: A difference-in-difference analysis was employed to compare differences in the uptake of physical health checks before and after the intervention, accounting for relevant observed and unobserved confounders. RESULTS: An immediate change was found in uptake after physical health checks were removed from, and after they were added back to, the QOF list. For BMI, cholesterol, and alcohol checks, the overall impact of removal was a reduction in uptake of 14.3, 6.8, and 11.9 percentage points, respectively. The reintroduction of BMI screening in the QOF increased the uptake by 10.2 percentage points. CONCLUSION: This analysis supports the hypothesis that QOF incentives lead to better uptake of physical health checks.
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Body Mass Index , Mental Disorders , Primary Health Care , Humans , Male , Female , Middle Aged , Cohort Studies , Adult , Mass Screening , Cholesterol/blood , Cholesterol/metabolism , Physical Examination , Alcohol Drinking , England , Motivation , Reimbursement, IncentiveABSTRACT
OBJECTIVE: To examine the association between being born into relative deprivation and hospital costs during childhood. DESIGN: Retrospective cohort study. METHODS: We created a birth cohort using Hospital Episode Statistics for children born in NHS hospitals in 2003/2004. The Index of Multiple Deprivation (IMD) rank at birth was missing from 75% of the baby records, so we linked mother and baby records to obtain the IMD decile from the mother's record. We aggregated and costed each child's hospital inpatient admissions, and outpatient and emergency department (ED) attendances up to 15 years of age. We used 2019/2020 NHS tariffs to assign costs. We constructed an additional cohort, all children born in 2013/2014, to explore any changes over time, comparing the utilisation and costs up to 5 years of age. RESULTS: Our main cohort comprised 567 347 babies born in 2003/2004, of which we could include 91%. Up to the age of 15 years, children born into the most deprived areas used more hospital services than those born in the least deprived, reflected in higher costs of inpatient, outpatient and ED care. The highest costs and greatest differences are in the year following birth. Comparing this with the later cohort (up to age 5 years), the average cost per child increased across all deprivation deciles, but differences between the most and least deprived deciles appeared to narrow slightly. CONCLUSIONS: Healthcare utilisation and costs are consistently higher for children who are born into the most deprived areas compared with the least.
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Hospital Costs , Hospitalization , Humans , England , Retrospective Studies , Child, Preschool , Female , Child , Infant , Male , Hospital Costs/statistics & numerical data , Adolescent , Hospitalization/economics , Hospitalization/statistics & numerical data , State Medicine/economics , Infant, Newborn , Emergency Service, Hospital/statistics & numerical data , Emergency Service, Hospital/economics , Social DeprivationABSTRACT
INTRODUCTION: The waiting list for elective surgery in England recently reached over 7.8 million people and waiting time targets have been missed since 2010. The high-volume low complexity (HVLC) surgical hubs programme aims to tackle the backlog of patients awaiting elective surgery treatment in England. This study will evaluate the impact of HVLC surgical hubs on productivity, patient care and the workforce. METHODS AND ANALYSIS: This 4-year project consists of six interlinked work packages (WPs) and is informed by the Consolidated Framework for Implementation Research. WP1: Mapping current and future HVLC provision in England through document analysis, quantitative data sets (eg, Hospital Episodes Statistics) and interviews with national service leaders. WP2: Exploring the effects of HVLC hubs on key performance outcomes, primarily the volume of low-complexity patients treated, using quasi-experimental methods. WP3: Exploring the impact and implementation of HVLC hubs on patients, health professionals and the local NHS through approximately nine longitudinal, multimethod qualitative case studies. WP4: Assessing the productivity of HVLC surgical hubs using the Centre for Health Economics NHS productivity measure and Lord Carter's operational productivity measure. WP5: Conducting a mixed-methods appraisal will assess the influence of HVLC surgical hubs on the workforce using: qualitative data (WP3) and quantitative data (eg, National Health Service (NHS) England's workforce statistics and intelligence from WP2). WP6: Analysing the costs and consequences of HVLC surgical hubs will assess their achievements in relation to their resource use to establish value for money. A patient and public involvement group will contribute to the study design and materials. ETHICS AND DISSEMINATION: The study has been approved by the East Midlands-Nottingham Research Ethics Committee 23/EM/0231. Participants will provide informed consent for qualitative study components. Dissemination plans include multiple academic and non-academic outputs (eg, Peer-reviewed journals, conferences, social media) and a continuous, feedback-loop of findings to key stakeholders (eg, NHS England) to influence policy development. TRIAL REGISTRATION: Research registry: Researchregistry9364 (https://www.researchregistry.com/browse-the-registry%23home/registrationdetails/64cb6c795cbef8002a46f115/).
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Research Design , State Medicine , Humans , England , Qualitative Research , PatientsABSTRACT
BACKGROUND: Arthroplasty registries are rarely used to inform encounters between clinician and patient. This study is part of a larger one which aimed to develop an information tool allowing both to benefit from previous patients' experience after total hip arthroplasty (THA). This study focuses on generating the information tool specifically for pain outcomes. METHODS: Data from the Geneva Arthroplasty Registry (GAR) about patients receiving a primary elective THA between 1996 and 2019 was used. Selected outcomes were identified from patient and surgeon surveys: pain walking, climbing stairs, night pain, pain interference, and pain medication. Clusters of patients with homogeneous outcomes at 1, 5, and 10 years postoperatively were generated based on selected predictors evaluated preoperatively using conditional inference trees (CITs). RESULTS: Data from 6,836 THAs were analysed and 14 CITs generated with 17 predictors found significant (p < 0.05). Baseline WOMAC pain score, SF-12 self-rated health (SRH), number of comorbidities, SF-12 mental component score, and body mass index (BMI) were the most common predictors. Outcome levels varied markedly by clusters whilst predictors changed at different time points for the same outcome. For example, 79% of patients with good to excellent SRH and less than moderate preoperative night pain reported absence of night pain at 1 year after THA; in contrast, for those with fair/poor SHR this figure was 50%. Also, clusters of patients with homogeneous levels of night pain at 1 year were generated based on SRH, Charnley, WOMAC night and pain scores, whilst those at 10 years were based on BMI alone. CONCLUSIONS: The information tool generated under this study can provide prospective patients and clinicians with valuable and understandable information about the experiences of "patients like them" regarding their pain outcomes.
Subject(s)
Arthroplasty, Replacement, Hip , Humans , Arthroplasty, Replacement, Hip/adverse effects , Treatment Outcome , Prospective Studies , Routinely Collected Health Data , Pain/etiologyABSTRACT
To date there have been no attempts to construct composite measures of healthcare provider performance which reflect preferences for health and non-health benefits, as well as costs. Health and non-health benefits matter to patients, healthcare providers and the general public. We develop a novel provider performance measurement framework that combines health gain, non-health benefit, and cost and illustrate it with an application to 54 English mental health providers. We apply estimates from a discrete choice experiment eliciting the UK general population's valuation of non-health benefits relative to health gains, to administrative and patient survey data for years 2013-2015 to calculate equivalent health benefit (eHB) for providers. We measure costs as forgone health and quantify the relative performance of providers in terms of equivalent net health benefit (eNHB): the value of the health and non-health benefits minus the forgone benefit equivalent of cost. We compare rankings of providers by eHB, eNHB, and by the rankings produced by the hospital sector regulator. We find that taking account of the non-health benefits in the eNHB measure makes a substantial difference to the evaluation of provider performance. Our study demonstrates that the provider performance evaluation space can be extended beyond measures of health gain and cost, and that this matters for comparison of providers.
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Health Personnel , Hospitals , Humans , Mental HealthABSTRACT
Many healthcare systems prohibit primary care physicians from dispensing the drugs they prescribe due to concerns that this encourages excessive, ineffective or unnecessarily costly prescribing. Using data from the English National Health Service for 2011-2018, we estimate the impact of physician dispensing rights on prescribing behavior at the extensive margin (comparing practices that dispense and those that do not) and the intensive margin (comparing practices with different proportions of patients to whom they dispense). We control for practices selecting into dispensing based on observable (OLS, entropy balancing) and unobservable practice characteristics (2SLS). We find that physician dispensing increases drug costs per patient by 3.1%, due to more, and more expensive, drugs being prescribed. Reimbursement is partly based on a fixed fee per package dispensed and we find that dispensing practices prescribe smaller packages. As the proportion of the practice population for whom they can dispense increases, dispensing practices behave more like non-dispensing practices.
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Motivation , Physicians , Humans , State Medicine , Drug Costs , Primary Health CareABSTRACT
The COVID-19 pandemic has had a significant impact on population mental health and the need for mental health services in many countries, while also disrupting critical mental health services and capacity, as a response to the pandemic. Mental health providers were asked to reconfigure wards to accommodate patients with COVID-19, thereby reducing capacity to provide mental health services. This is likely to have widened the existing mismatch between demand and supply of mental health care in the English NHS. We quantify the impact of these rapid service reconfigurations on activity levels for mental health providers in England during the first thirteen months (March 2020-March 2021) of the COVID-19 pandemic. We use monthly mental health service utilisation data for a large subset of mental health providers in England from January 1, 2015 to March 31, 2021. We use multivariate regression to estimate the difference between observed and expected utilisation from the start of the pandemic in March 2020. Expected utilisation levels (i.e. the counterfactual) are estimated from trends in utilisation observed during the pre-pandemic period January 1, 2015 to February 31, 2020. We measure utilisation as the monthly number of inpatient admissions, discharges, net admissions (admissions less discharges), length of stay, bed days, number of occupied beds, patients with outpatient appointments, and total outpatient appointments. We also calculate the accumulated difference in utilisation from the start of the pandemic period. There was a sharp reduction in total inpatient admissions and net admissions at the beginning of the pandemic, followed by a return to pre-pandemic levels from September 2020. Shorter inpatient stays are observed over the whole period and bed days and occupied bed counts had not recovered to pre-pandemic levels by March 2021. There is also evidence of greater use of outpatient appointments, potentially as a substitute for inpatient care.
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BACKGROUND: Quality-adjusted life expectancy (QALE) combines mortality risk and multidimensional health-related quality of life (HRQoL) information to measure healthy life expectancy in terms of quality-adjusted life years (QALYs). This paper estimates the relative importance of individual quality of life dimensions in explaining inequalities in QALE. METHODS: We combined EQ-5D-5L data from the Health Survey for England for 2017 and 2018 (N = 14,412) with full population mortality data from the Office for National Statistics to calculate QALE by age, sex and deprivation quintile. The effect of HRQoL dimensions on the socioeconomic gradient in QALE was decomposed using an iterative imputation approach, in which inequalities associated with socioeconomic status in each domain were removed by imputing the response distribution of the richest quintile for all participants. Sampling uncertainty in the HRQoL data was evaluated using bootstrapping. RESULTS: People in the least deprived fifth of neighbourhoods in England can expect to live 7.0 years longer and experience 11.1 more QALYs than those in the most deprived fifth. Inequalities in HRQoL accounted for 28.0% and 45.7% of QALE inequalities for males and females, respectively. Pain/discomfort, anxiety/depression and mobility were the most influential HRQoL domains. DISCUSSION: Our results identify the extent of inequalities associated with socioeconomic status in lifetime health and the relative importance of inequalities by mortality and HRQoL. The contributions of the individual dimensions of HRQoL towards lifetime inequalities vary substantially by sex. Our findings can help to identify the types of interventions most likely to alleviate health inequalities, which may be different for males and females.
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Health Status Disparities , Quality of Life , Male , Female , Humans , Life Expectancy , Quality-Adjusted Life Years , Health SurveysABSTRACT
BACKGROUND: Health inequalities are often assessed in terms of life expectancy or health-related quality of life (HRQoL). Few studies combine both aspects into quality-adjusted life expectancy (QALE) to derive comprehensive estimates of lifetime health inequality. Furthermore, little is known about the sensitivity of estimated inequalities in QALE to different sources of HRQoL information. This study assesses inequalities in QALE by educational attainment in Norway using two different measures of HRQoL. METHODS: We combine full population life tables from Statistics Norway with survey data from the Tromsø study, a representative sample of the Norwegian population aged ≥ 40. HRQoL is measured using the EQ-5D-5L and EQ-VAS instruments. Life expectancy and QALE at 40 years of age are calculated using the Sullivan-Chiang method and are stratified by educational attainment. Inequality is measured as the absolute and relative gap between individuals with lowest (i.e. primary school) and highest (university degree 4 + years) educational attainment. RESULTS: People with the highest educational attainment can expect to live longer lives (men: + 17.9% (95%CI: 16.4 to 19.5%), women: + 13.0% (95%CI: 10.6 to 15.5%)) and have higher QALE (men: + 22.4% (95%CI: 20.4 to 24.4%), women: + 18.3% (95%CI: 15.2 to 21.6%); measured using EQ-5D-5L) than individuals with primary school education. Relative inequality is larger when HRQoL is measured using EQ-VAS. CONCLUSION: Health inequalities by educational attainment become wider when measured in QALE rather than LE, and the degree of this widening is larger when measuring HRQoL by EQ-VAS than by EQ-5D-5L. We find a sizable educational gradient in lifetime health in Norway, one of the most developed and egalitarian societies in the world. Our estimates provide a benchmark against which other countries can be compared.
Subject(s)
Health Status Disparities , Quality of Life , Male , Humans , Female , Adult , Life Expectancy , Educational Status , Surveys and Questionnaires , Health StatusABSTRACT
OBJECTIVES: The National Institute for Health and Care Excellence in England has implemented severity-of-disease modifiers that give greater weight to health benefits accruing to patients who experience a larger shortfall in quality-adjusted life-years (QALYs) under current standard of care than healthy individuals. This requires an estimate of quality-adjusted life expectancy (QALE) of the general population based on age and sex. Previous QALE population norms are based on nearly 30-year-old assessments of health-related quality of life in the general population. This study provides updated QALE estimates for the English population based on age and sex. METHODS: 5-level version of EQ-5D data for 14 412 participants from the Health Survey for England (waves 2017 and 2018) were pooled, and health-related quality of life population norms were calculated. These norms were combined with official life tables from the Office for National Statistics for 2017 to 2019 using the Sullivan method to derive QALE estimates based on age and sex. Values were discounted using 0%, 1.5%, and 3.5% discount rates. RESULTS: QALE at birth is 68.24 QALYs for men and 68.21 QALYs for women. These values are significantly lower than previously published QALE population norms based on the older 3-level version of EQ-5D data. CONCLUSION: This study provides new QALE population norms for England that serve to establish absolute and relative QALY shortfalls for the purpose of health technology assessments.
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Life Expectancy , Quality of Life , Male , Infant, Newborn , Humans , Female , Adult , Quality-Adjusted Life Years , Health Status , Health SurveysABSTRACT
Effective policymaking in health care systems begins with a clear typology of the terminology - need, demand, supply and access to care - and their interrelationships. However, the terms are contested and their meaning is rarely stated explicitly. This paper offers working definitions of need, demand and supply. We draw on the international literature and use a Venn diagram to explain the terms. We then define access to care, reviewing alternative and competing definitions from the literature. We conclude by discussing potential applications of our conceptual framework to help to understand the interrelationships and trade-offs between need, demand, supply and access in health care.
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Health Services Accessibility , Health Services Needs and Demand , HumansABSTRACT
A largely unexplored part of the financial incentive for physicians to participate in preventive care is the degree to which they are the residual claimant from any resulting cost savings. We examine the impact of two preventive activities for people with serious mental illness (care plans and annual reviews of physical health) by English primary care practices on costs in these practices and in secondary care. Using panel two-part models to analyze patient-level data linked across primary and secondary care, we find that these preventive activities in the previous year are associated with cost reductions in the current quarter both in primary and secondary care. We estimate that there are large beneficial externalities for which the primary care physician is not the residual claimant: the cost savings in secondary care are 4.7 times larger than the cost savings in primary care. These activities are incentivized in the English National Health Service but the total financial incentives for primary care physicians to participate were considerably smaller than the total cost savings produced. This suggests that changes to the design of incentives to increase the marginal reward for conducting these preventive activities among patients with serious mental illness could have further increased welfare.
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Mental Disorders , Secondary Care , Humans , State Medicine , Mental Disorders/therapy , Primary Health CareABSTRACT
OBJECTIVES: To examine the effect of general practitioners (GPs) working in or alongside the emergency department (GPED) on patient outcomes and experience, and the associated impacts of implementation on the workforce. DESIGN: Mixed-methods study: interviews with service leaders and NHS managers; in-depth case studies (n=10) and retrospective observational analysis of routinely collected national data. We used normalisation process theory to map our findings to the theory's four main constructs of coherence, cognitive participation, collective action and reflexive monitoring. SETTING AND PARTICIPANTS: Data were collected from 64 EDs in England. Case site data included: non-participant observation of 142 clinical encounters; 467 semistructured interviews with policy-makers, service leaders, clinical staff, patients and carers. Retrospective observational analysis used routinely collected Hospital Episode Statistics alongside information on GPED service hours from 40 hospitals for which complete data were available. RESULTS: There was disagreement at individual, stakeholder and organisational levels regarding the purpose and potential impact of GPED (coherence). Participants criticised policy development and implementation, and staff engagement was hindered by tensions between ED and GP staff (cognitive participation). Patient 'streaming' processes, staffing and resource constraints influenced whether GPED became embedded in routine practice. Concerns that GPED may increase ED attendance influenced staff views. Our quantitative analysis showed no detectable impact on attendance (collective action). Stakeholders disagreed whether GPED was successful, due to variations in GPED model, site-specific patient mix and governance arrangements. Following statistical adjustment for multiple testing, we found no impact on: ED reattendances within 7 days, patients discharged within 4 hours of arrival, patients leaving the ED without being seen; inpatient admissions; non-urgent ED attendances and 30-day mortality (reflexive monitoring). CONCLUSIONS: We found a high degree of variability between hospital sites, but no overall evidence that GPED increases the efficient operation of EDs or improves clinical outcomes, patient or staff experience. TRIAL REGISTRATION NUMBER: ISCRTN5178022.
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General Practitioners , Emergency Service, Hospital , Hospitalization , Humans , Inpatients , Retrospective StudiesABSTRACT
BACKGROUND: The literature on Inequality of opportunity (IOp) in health distinguishes between circumstances that lie outside of own control vs. efforts that - to varying extents - are within one's control. From the perspective of IOp, this paper aims to explain variations in individuals' health-related quality of life (HRQoL) by focusing on two separate sets of variables that clearly lie outside of own control: Parents' health is measured by their experience of somatic diseases, psychological problems and any substance abuse, while parents' wealth is indicated by childhood financial conditions (CFC). We further include own educational attainment which may represent a circumstance, or an effort, and examine associations of IOp for different health outcomes. HRQoL are measured by EQ-5D-5L utility scores, as well as the probability of reporting limitations on specific HRQoL-dimensions (mobility, self-care, usual-activities, pain & discomfort, and anxiety and depression). METHOD: We use unique survey data (N = 20,150) from the egalitarian country of Norway to investigate if differences in circumstances produce unfair inequalities in health. We estimate cross-sectional regression models which include age and sex as covariates. We estimate two model specifications. The first represents a narrow IOp by estimating the contributions of parents' health and wealth on HRQoL, while the second includes own education and thus represents a broader IOp, alternatively it provides a comparison of the relative contributions of an effort variable and the two sets of circumstance variables. RESULTS: We find strong associations between the circumstance variables and HRQoL. A more detailed examination showed particularly strong associations between parental psychological problems and respondents' anxiety and depression. Our Shapley decomposition analysis suggests that parents' health and wealth are each as important as own educational attainment for explaining inequalities in adult HRQoL. CONCLUSION: We provide evidence for the presence of the lasting effect of early life circumstances on adult health that persists even in one of the most egalitarian countries in the world. This suggests that there may be an upper limit to how much a generous welfare state can contribute to equal opportunities.
Subject(s)
Quality of Life , Adult , Child , Cross-Sectional Studies , Humans , Parents/psychology , Quality of Life/psychology , Surveys and QuestionnairesABSTRACT
BACKGROUND: Socioeconomic status is a key predictor of lifetime health: poorer people can expect to live shorter lives with lower average health-related quality-of-life (HRQoL) than richer people. In this study, we aimed to improve understanding of the socioeconomic gradient in HRQoL by exploring how inequalities in different dimensions of HRQoL differ by age. METHODS: Data were derived from the Health Survey for England for 2017 and 2018 (14,412 participants). HRQoL was measured using the EQ-5D-5L instrument. We estimated mean EQ-5D utility scores and reported problems on five HRQoL dimensions (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) for ages 16 to 90+ and stratified by neighbourhood deprivation quintiles. Relative and absolute measures of inequality were assessed. RESULTS: Mean EQ-5D utility scores declined with age and followed a socioeconomic gradient, with the lowest scores in the most deprived areas. Gaps between the most and least deprived quintiles emerged around the age of 35, reached their greatest extent at age 60 to 64 (relative HRQoL of most deprived compared to least deprived quintile: females = 0.77 (95% CI: 0.68-0.85); males = 0.78 (95% CI: 0.69-0.87)) before closing again in older age groups. Gaps were apparent for all five EQ-5D dimensions but were greatest for mobility and self-care. CONCLUSION: There are stark socioeconomic inequalities in all dimensions of HRQoL in England. These inequalities start to develop from early adulthood and increase with age but reduce again around retirement age.
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Depression , Quality of Life , Adolescent , Adult , Aged , Aged, 80 and over , Female , Health Status , Health Surveys , Humans , Male , Middle Aged , Pain , Social Class , Surveys and Questionnaires , Young AdultABSTRACT
OBJECTIVES: Emergency departments (EDs) in NHS hospitals in England have faced considerable increases in demand over recent years. Most hospitals have developed general practitioner services in emergency departments (GPEDs) to treat non-emergency patients, aiming to relieve pressure on other staff and to improve ED efficiency and patient experience. We measured the impact of GPED services on patient flows, health outcomes and ED workload. DESIGN: Retrospective observational study. Differences in GPED service availability across EDs and time of day were used to identify the causal effect of GPED, as patients attending the ED at the same hour of the day are quasi-randomly assigned to treatment or control groups based on their local ED's service availability. PARTICIPANTS: Attendances to 40 EDs in English NHS hospitals from April 2018 to March 2019, 4 441 349 observations. PRIMARY AND SECONDARY OUTCOMES MEASURED: Outcomes measured were volume of attendances, 'non-urgent' attendances, waiting times over 4 hours, patients leaving without being treated, unplanned reattendances within 7 days, inpatient admissions and 30-day mortality. RESULTS: We found a small, statistically significant reduction in unplanned reattendances within 7 days (OR 0.968, 95% CI 0.948 to 0.989), equivalent to 302 fewer reattendances per year for the average ED. The clinical impact of this was judged to be negligible. There was no detectable impact on any other outcome measure. CONCLUSIONS: We found no adverse effects on patient outcomes; neither did we find any evidence of the hypothesised benefits of placing GPs in emergency settings beyond a marginal reduction in reattendances that was not considered clinically significant.