Development and use of methods to estimate chronic disease prevalence in small populations

Introduction National data on the prevalence of chronic diseases on general practice registers is now available. The aim of this PhD was to develop and validate epidemiological models for the expected prevalence of chronic obstructive pulmonary disease (COPD), coronary heart disease (CHD), stroke, hypertension, overall cardiovascular disease (CVD) and high CVD risk at general practice and small area level, and to explore the extent of undiagnosed disease, factors associated with it, and its impact on population health. Methods Multinomial logistic regression models were fitted to pooled Health Survey for England data to derive odds ratios for disease risk factors. These were applied to general practice and small area level population data, split by age, sex, ethnicity, deprivation, rurality and smoking status, to estimate expected disease prevalence at these levels. Validation was carried out using external data, including population-based epidemiological research and case-finding initiatives. Practice-level undiagnosed disease prevalence i.e. expected minus registered disease prevalence, and hospital admission rates for these conditions, were evaluated as outcome indicators of the quality and supply of primary health care services, using ordinary least squares (OLS) regression, geographically-weighted regression (GWR), and other spatial analytic methods. Results Risk factors, odds of disease and expected prevalence were consistent with external data sources. Spatial analysis showed strong evidence of spatial non-stationarity of undiagnosed disease prevalence, with high levels of undiagnosed disease in London and other conurbations, and associations with low supply of primary health care services. Higher hospital admission rates were associated with population deprivation, poorer quality and supply of primary health care services and poorer access to them, and for COPD, with higher levels of undiagnosed disease. Conclusion The epidemiologic prevalence models have been implemented in national data sources such as NHS Comparators, the Association of Public Health Observatories website, and a number of national reports. Early experience suggests that they are useful for guiding case-finding at practice level and improving and regulating the quality of primary health care. Comparisons with external data, in particular prevalence of disease detected by general practices, suggest that model predictions are valid. Practice-level spatial analyses of undiagnosed disease prevalence and hospital admission rates failed to demonstrate superiority of GWR over OLS methods. Disease modellers should be encouraged to collaborate more effectively, and to validate and compare modelling methods using an agreed framework. National leadership is needed to further develop and implement disease models. It is likely that prevalence models will prove to be most useful for identifying undiagnosed diseases with a slow and insidious onset, such as COPD, diabetes and hypertension

Ethnic inequalities in the treatment and outcome of diabetes in three English Primary Care Trusts

BACKGROUND:Although the prevalence of diabetes is three to five times higher in UK South Asians than Whites, there are no reports of the extent of ethnicity recording in routine general practice, and few population-based published studies of the association between ethnicity and quality of diabetes care and outcomes. We aimed to determine the association between ethnicity and healthcare factors in an English population.METHODS:Data was obtained in 2002 on all 21,343 diabetic patients registered in 99% of all computerised general practitioner (GP) practices in three NW London Primary Care Trusts (PCTs), covering a total registered population of 720,000. Previously practices had been provided with training, data entry support and feedback. Treatment and outcome measures included drug treatment and blood pressure (BP), total cholesterol and haemoglobin A1c (HbA1c) levels.RESULTS:Seventy per cent of diabetic patients had a valid ethnicity code. In the relatively older White population, we expected a smaller proportion with a normal BP, but BP differences between the groups were small and suggested poorer control in non-White ethnic groups. There were also significant differences between ethnic groups in the proportions of insulin-treated patients, with a smaller proportion of South Asians - 4.7% compared to 7.1% of Whites - receiving insulin, although the proportion with a satisfactory HbA1c was smaller- 25.6% compared to 37.9%.CONCLUSION:Recording the ethnicity of existing primary care patients is feasible, beginning with patients with established diseases such as diabetes. We have shown that the lower proportion of South Asian patients with good diabetes control, and who are receiving insulin, is at least partly due to poorer standards of care in South Asians, although biological and cultural factors could also contribute. This study highlights the need to capture ethnicity data in clinical trials and in routine care, to specifically investigate the reasons for these ethnic differences, and to consider more intensive management of diabetes and education about the disease in South Asian patient

Practice size, caseload, deprivation and quality of care of patients with coronary heart disease, hypertension and stroke in primary care: national cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Reports of higher quality care by higher-volume secondary care providers have fuelled a shift of services from smaller provider units to larger hospitals and units. In the United Kingdom, most patients are managed in primary care. Hence if larger practices provide better quality of care; this would have important implications for the future organization of primary care services. We examined the association between quality of primary care for cardiovascular disease achieved by general practices in England and Scotland by general practice caseload, practice size and area based deprivation measures, using data from the New General Practitioner (GP) Contract.</p> <p>Methods</p> <p>We analyzed data from 8,970 general practices with a total registered population of 55,522,778 patients in England and Scotland. We measured practice performance against 26 cardiovascular disease (coronary heart disease, left ventricular disease, and stroke) Quality and Outcomes Framework (QOF) indicators for patients on cardiovascular disease registers and linked this with data on practice characteristics and census data.</p> <p>Results</p> <p>Despite wide variations in practice list sizes and deprivation, the prevalence of was remarkably consistent, (coronary heart disease, left ventricular dysfunction, hypertension and cerebrovascular disease was 3.7%; 0.45%; 11.4% and 1.5% respectively). Achievement in quality of care for cardiovascular disease, as measured by QOF, was consistently high regardless of caseload or size with a few notable exceptions: practices with larger list sizes, higher cardiovascular disease caseloads and those in affluent areas had higher achievement of indicators requiring referral for further investigation. For example, small practices achieved lower scores 71.4% than large practices 88.6% (P < 0.0001) for referral for exercise testing and specialist assessment of patients with newly diagnosed angina.</p> <p>Conclusion</p> <p>The volume-outcome relationship found in hospital settings is not seen between practices in the UK in management of cardiovascular disorders in primary care. Further work is warranted to explain apparently poorer quality achievement in some aspects of cardiovascular management relating to initial diagnosis and management among practices in deprived areas, smaller practices and those with a smaller caseload.</p

Evaluation of complex integrated care programmes: the approach in North West London

Background: Several local attempts to introduce integrated care in the English National Health Service have been tried, with limited success. The Northwest London Integrated Care Pilot attempts to improve the quality of care of the elderly and people with diabetes by providing a novel integration process across primary, secondary and social care organisations. It involves predictive risk modelling, care planning, multidisciplinary management of complex cases and an information technology tool to support information sharing. This paper sets out the evaluation approach adopted to measure its effect. Study design: We present a mixed methods evaluation methodology. It includes a quantitative approach measuring changes in service utilization, costs, clinical outcomes and quality of care using routine primary and secondary data sources. It also contains a qualitative component, involving observations, interviews and focus groups with patients and professionals, to understand participant experiences and to understand the pilot within the national policy context. Theory and discussion: This study considers the complexity of evaluating a large, multi-organisational intervention in a changing healthcare economy. We locate the evaluation within the theory of evaluation of complex interventions. We present the specific challenges faced by evaluating an intervention of this sort, and the responses made to mitigate against them. Conclusions: We hope this broad, dynamic and responsive evaluation will allow us to clarify the contribution of the pilot, and provide a potential model for evaluation of other similar interventions. Because of the priority given to the integrated agenda by governments internationally, the need to develop and improve strong evaluation methodologies remains strikingly important

Variations in cardiovascular disease under-diagnosis in England: national cross-sectional spatial analysis

BACKGROUND: There is under-diagnosis of cardiovascular disease (CVD) in the English population, despite financial incentives to encourage general practices to register new cases. We compared the modelled (expected) and diagnosed (observed) prevalence of three cardiovascular conditions- coronary heart disease (CHD), hypertension and stroke- at local level, their geographical variation, and population and healthcare predictors which might influence diagnosis. METHODS: Cross-sectional observational study in all English local authorities (351) and general practices (8,372) comparing model-based expected prevalence with diagnosed prevalence on practice disease registers. Spatial analyses were used to identify geographic clusters and variation in regression relationships. RESULTS: A total of 9,682,176 patients were on practice CHD, stroke and transient ischaemic attack, and hypertension registers. There was wide spatial variation in observed: expected prevalence ratios for all three diseases, with less than five per cent of expected cases diagnosed in some areas. London and the surrounding area showed statistically significant discrepancies in observed: expected prevalence ratios, with observed prevalence much lower than the epidemiological models predicted. The addition of general practitioner supply as a variable yielded stronger regression results for all three conditions. CONCLUSIONS: Despite almost universal access to free primary healthcare, there may be significant and highly variable under-diagnosis of CVD across England, which can be partially explained by persistent inequity in GP supply. Disease management studies should consider the possible impact of under-diagnosis on population health outcomes. Compared to classical regression modelling, spatial analytic techniques can provide additional information on risk factors for under-diagnosis, and can suggest where healthcare resources may be most needed

Model for estimating the population prevalence of chronic obstructive pulmonary disease: cross sectional data from the Health Survey for England

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a major but neglected public health problem. Currently 1.4% of the England population has a clinical diagnosis of COPD, but the true burden of the disease has not been known with certainty, as many cases remain undiagnosed. METHODS: A mathematical model based on cross sectional data from a representative sample of the population in England (the Heath Survey for England 2001, n = 10,750) was developed allowing estimates on the prevalence of COPD (defined based on the presence of airflow obstruction) to be obtained. Logistic regression analysis was used to investigate and choose risk factors for inclusion in the model and to derive the prevalence estimates based on the strength of association between selected risk factors and the outcome COPD. The model allows the prevalence to be estimated in populations at national level and also at regional and large local areas, based on their compositions according to age, sex, smoking and ethnicity, and on area degrees of urbanisation and deprivation. We applied the model to measure the prevalence of COPD in England and in some sub-groups of the population within the country. RESULTS: The prevalence of COPD in England is estimated as 3.1% (3.9% in men and 2.4% in women) in the population over 15 years of age, and 5.3% (6.8% in men and 3.9% in women) in 45 year-olds and over. There was a 7-fold variation in the prevalence across subgroups of the population, with lowest values in Asian women from wealthy rural areas (1.7%), and highest in black men from deprived urban areas (12.5%). CONCLUSION: The model can be used to estimate population prevalence of COPD from large general practices to national level, and as a tool to identify areas of high levels of unmet needs for COPD priority health actions. The results from the model highlight the importance of including variables other than age, sex and smoking, i.e. levels of deprivation, urbanisation and ethnicity, when estimating population prevalence of COPD. The model should be validated at local level and incorporated into case-finding strategies

Prevalence and attributable health burden of chronic respiratory diseases, 1990–2017: A systematic analysis for the global burden of disease study 2017

© 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: Previous attempts to characterise the burden of chronic respiratory diseases have focused only on specific disease conditions, such as chronic obstructive pulmonary disease (COPD) or asthma. In this study, we aimed to characterise the burden of chronic respiratory diseases globally, providing a comprehensive and up-to-date analysis on geographical and time trends from 1990 to 2017. Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, we estimated the prevalence, morbidity, and mortality attributable to chronic respiratory diseases through an analysis of deaths, disability-adjusted life-years (DALYs), and years of life lost (YLL) by GBD super-region, from 1990 to 2017, stratified by age and sex. Specific diseases analysed included asthma, COPD, interstitial lung disease and pulmonary sarcoidosis, pneumoconiosis, and other chronic respiratory diseases. We also assessed the contribution of risk factors (smoking, second-hand smoke, ambient particulate matter and ozone pollution, household air pollution from solid fuels, and occupational risks) to chronic respiratory disease-attributable DALYs. Findings: In 2017, 544·9 million people (95% uncertainty interval [UI] 506·9–584·8) worldwide had a chronic respiratory disease, representing an increase of 39·8% compared with 1990. Chronic respiratory disease prevalence showed wide variability across GBD super-regions, with the highest prevalence among both males and females in high-income regions, and the lowest prevalence in sub-Saharan Africa and south Asia. The age-sex-specific prevalence of each chronic respiratory disease in 2017 was also highly variable geographically. Chronic respiratory diseases were the third leading cause of death in 2017 (7·0% [95% UI 6·8–7·2] of all deaths), behind cardiovascular diseases and neoplasms. Deaths due to chronic respiratory diseases numbered 3 914 196 (95% UI 3 790 578–4 044 819) in 2017, an increase of 18·0% since 1990, while total DALYs increased by 13·3%. However, when accounting for ageing and population growth, declines were observed in age-standardised prevalence (14·3% decrease), age-standardised death rates (42·6%), and age-standardised DALY rates (38·2%). In males and females, most chronic respiratory disease-attributable deaths and DALYs were due to COPD. In regional analyses, mortality rates from chronic respiratory diseases were greatest in south Asia and lowest in sub-Saharan Africa, also across both sexes. Notably, although absolute prevalence was lower in south Asia than in most other super-regions, YLLs due to chronic respiratory diseases across the subcontinent were the highest in the world. Death rates due to interstitial lung disease and pulmonary sarcoidosis were greater than those due to pneumoconiosis in all super-regions. Smoking was the leading risk factor for chronic respiratory disease-related disability across all regions for men. Among women, household air pollution from solid fuels was the predominant risk factor for chronic respiratory diseases in south Asia and sub-Saharan Africa, while ambient particulate matter represented the leading risk factor in southeast Asia, east Asia, and Oceania, and in the Middle East and north Africa super-region. Interpretation: Our study shows that chronic respiratory diseases remain a leading cause of death and disability worldwide, with growth in absolute numbers but sharp declines in several age-standardised estimators since 1990. Premature mortality from chronic respiratory diseases seems to be highest in regions with less-resourced health systems on a per-capita basis. Funding: Bill & Melinda Gates Foundation

Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

The UN’s Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030