Sociodemographic and health-related differences in undiagnosed hypertension in the health survey for England 2015-2019: a cross-sectional cohort study.

Background: Hypertension is a leading cause of morbidity and mortality worldwide, yet a substantial proportion of cases are undiagnosed. Understanding the scale of undiagnosed hypertension and identifying groups most at risk is important to inform approaches to detection. Methods: In this cross-sectional cohort study, we used data from the 2015 to 2019 Health Survey for England, an annual, cross-sectional, nationally representative survey. The survey follows a multi-stage stratified probability sampling design, involving a random sample of primary sampling units based on postcode sectors, followed by a random sample of postal addresses within these units. Within each selected household, all adults (aged ≥16 years) and up to four children, were eligible for participation. For the current study, individuals aged 16 years and over who were not pregnant and had valid blood pressure data were included in the analysis. The primary outcome was undiagnosed hypertension, defined by a measured blood pressure of 140/90 mmHg or above but no history of diagnosis. Age-adjusted prevalence of undiagnosed hypertension was estimated across sociodemographic and health-related characteristics, including ethnicity, region, rural-urban classification, relationship status, highest educational qualification, National Statistics Socio-Economic Classification (NS-SEC), Body Mass Index (BMI), self-reported general health, and smoking status. To assess the independent association between undiagnosed hypertension and each characteristic, we fitted a logistic regression model adjusted for sociodemographic factors. Findings: The sample included 21,476 individuals, of whom 55.8% were female and 89.3% reported a White ethnic background. An estimated 30.7% (95% confidence interval 29.0-32.4) of men with hypertension and 27.6% (26.1-29.1) of women with hypertension were undiagnosed. Younger age, lower BMI, and better self-reported general health were associated with an increased likelihood of hypertension being undiagnosed for men and women. Living in rural areas and in regions outside of London and the East of England were also associated with an increased likelihood of hypertension being undiagnosed for men, as were being married or in a civil partnership and having higher educational qualifications for women. Interpretation: Hypertension is commonly undiagnosed, and some of the groups that are at the lowest risk of hypertension are the most likely to be undiagnosed. Given the high lifetime risk of hypertension and its strong links with morbidity and mortality, our findings suggest a need for greater awareness of the potential for undiagnosed hypertension, including among those typically considered 'low risk'. Further research is needed to assess the impact of extending hypertension screening to lower-risk groups. Funding: None.

Qualitative interviews to understand methods and systems used to collect ethnicity information in health administrative data sources in England.

Background: This article is one of a series aiming to inform analytical methods to improve comparability of estimates of ethnic health disparities based on different sources. This article explores the quality of ethnicity data and identifies potential sources of bias when ethnicity information is collected in three key NHS data sources. Future research can build on these findings to explore analytical methods to mitigate biases. Methods: Thematic analysis of semi-structured qualitative interviews to explore potential sources of error and bias in the process of collecting ethnicity information across three NHS data sources: General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR), Hospital Episode Statistics (HES) and Improving Access to Psychological Therapies (IAPT). The study included feedback from 22 experts working on different aspects of health admin data collection for England (including staff from NHS Digital, IT system suppliers and relevant healthcare service providers). Results: Potential sources of error and bias were identified across data collection, data processing and quality assurance processes. Similar issues were identified for all three sources. Our analysis revealed three main themes which can result in bias and inaccuracies in ethnicity data recorded: data infrastructure challenges, human challenges, and institutional challenges. Conclusions: Findings highlighted that analysts using health admin data should be aware of the main sources of potential error and bias in health admin data, and be mindful that the main sources of error identified are more likely to affect the ethnicity data for ethnic minority groups. Where possible, analysts should describe and seek to account for this bias in their research.

Ethnic differences in COVID-19 mortality in the second and third waves of the pandemic in England during the vaccine rollout: a retrospective, population-based cohort study.

BACKGROUND: Ethnic minority groups in England have been disproportionately affected by the COVID-19 pandemic and have lower vaccination rates than the White British population. We examined whether ethnic differences in COVID-19 mortality in England have continued since the vaccine rollout and to what extent differences in vaccination rates contributed to excess COVID-19 mortality after accounting for other risk factors. METHODS: We conducted a retrospective, population-based cohort study of 28.8 million adults aged 30-100 years in England. Self-reported ethnicity was obtained from the 2011 Census. The outcome was death involving COVID-19 during the second (8 December 2020 to 12 June 2021) and third wave (13 June 2021 to 1 December 2021). We calculated hazard ratios (HRs) for death involving COVID-19, sequentially adjusting for age, residence type, geographical factors, sociodemographic characteristics, pre-pandemic health, and vaccination status. RESULTS: Age-adjusted HRs of death involving COVID-19 were elevated for most ethnic minority groups during both waves, particularly for groups with lowest vaccination rates (Bangladeshi, Pakistani, Black African, and Black Caribbean). HRs were attenuated after adjusting for geographical factors, sociodemographic characteristics, and pre-pandemic health. Further adjusting for vaccination status substantially reduced residual HRs for Black African, Black Caribbean, and Pakistani groups in the third wave. Fully adjusted HRs only remained elevated for the Bangladeshi group (men: 2.19 [95% CI 1.72-2.78]; women: 2.12 [1.58-2.86]) and Pakistani men (1.24 [1.06-1.46]). CONCLUSIONS: Lower COVID-19 vaccination uptake in several ethnic minority groups may drive some of the differences in COVID-19 mortality compared to White British. Public health strategies to increase vaccination uptake in ethnic minority groups would help reduce inequalities in COVID-19 mortality, which have remained substantial since the start of the vaccination campaign.

Developing a User Reported Measure of Care Co-ordination.

INTRODUCTION: Older people with chronic conditions often receive poor care because of the fragmented way in which their services are delivered from multiple sources. Providers have limited tools to directly capture the views of older people about their experiences of care co-ordination. The study aim was to design and test a survey tool to capture the experiences of older people with chronic conditions regarding how well their health and (where applicable) social care was co-ordinated. METHOD: To inform the questionnaire development, we reviewed the literature on existing surveys and care co-ordination theory, and on the health status of our target audience (people aged 65 or over with one or more chronic conditions and not in hospital or residential institutions). We also consulted stakeholders including those working in health and social care services and those with expertise in the subject area. We grouped questions around experiences of care in three dimensions: care in the home environment, planned transitions in care and unplanned situations. We also designed the questions so they could be mapped onto three recognised dimensions of continuity of care - management continuity, information continuity and relational continuity - as articulated in the international literature. The questionnaire was tested using focus groups and cognitive interviews and piloted with people aged 65 and over with at least one chronic condition, using a postal survey. We used service user records in 32 general practices located in four areas and a population database held by one local authority in England as the sampling frame. RESULTS: The pilot achieved an overall response rate of 27.6% (n = 562 responses). Ninety five percent of respondents answered 30 or more of the 46 questions and three respondents answered fewer than 10 questions. Twenty four items achieved one or more positive correlations greater than 0.5 with other survey items and four instances of positive associations greater than 0.7 were found. DISCUSSION/CONCLUSION: The growing focus on care co-ordination demonstrates the need for a tool that can capture the experiences of patients accessing care across organisational and professional boundaries, to inform the improvement of care co-ordination activities from a patient perspective. Early results suggest that our tool may have a contribution to make in these areas. However, more work is required to test the efficacy of the tool on a larger scale and in different settings, and to find ways of improving response rates.

Impact of case-mix on comparisons of patient-reported experience in NHS acute hospital trusts in England.

OBJECTIVES: To examine the impact of patient-mix on National Health Service (NHS) acute hospital trust scores in two national NHS patient surveys. METHODS: Secondary analysis of 2012 patient survey data for 57,915 adult inpatients at 142 NHS acute hospital trusts and 45,263 adult emergency department attendees at 146 NHS acute hospital trusts in England. Changes in trust scores for selected questions, ranks, inter-trust variance and score-based performance bands were examined using three methods: no adjustment for case-mix; the current standardization method with weighting for age, sex and, for inpatients only, admission method; and a regression model adjusting in addition for ethnicity, presence of a long-term condition, proxy response (inpatients only) and previous emergency attendances (emergency department survey only). RESULTS: For both surveys, all the variables examined were associated with patients' responses and affected inter-trust variance in scores, although the direction and strength of impact differed between variables. Inter-trust variance was generally greatest for the unadjusted scores and lowest for scores derived from the full regression model. Although trust scores derived from the three methods were highly correlated (Kendall's tau coefficients 0.70-0.94), up to 14% of trusts had discordant ranks of when the standardization and regression methods were compared. Depending on the survey and question, up to 14 trusts changed performance bands when the regression model with its fuller case-mix adjustment was used rather than the current standardization method. CONCLUSIONS: More comprehensive case-mix adjustment of patient survey data than the current limited adjustment reduces performance variation between NHS acute hospital trusts and alters the comparative performance bands of some trusts. Given the use of these data for high-impact purposes such as performance assessment, regulation, commissioning, quality improvement and patient choice, a review of the long-standing method for analysing patient survey data would be timely, and could improve rigour and comparability across the NHS. Performance comparisons need to be perceived as fair and scientifically robust to maintain confidence in publicly reported data, and to support their use by both the public and the NHS.

Do some trusts deliver a consistently better experience for patients? An analysis of patient experience across acute care surveys in English NHS trusts.

INTRODUCTION: Data were used from inpatient, outpatient and accident and emergency surveys in acute trusts in England to examine consistency in patient-reported experience across services, and factors associated with systematic variations in performance. METHODS: Standardised mean scores for six domains of patient experience were constructed for each survey for 145 non-specialist acute trusts. Hierarchical cluster analysis was used to investigate whether and how trust performance clusters. Multilevel regression analysis was used to determine trust characteristics associated with performance. RESULTS: Cluster analysis identified three groups: trusts that performed consistently above (30 trusts) or below (six trusts) average, and those with mixed performance. All the poor performing trusts were in London, none were foundation trusts or teaching hospitals, and they had the highest mean deprivation score and the lowest proportion of white inpatients and response rates. Foundation and teaching status, and the proportion of white inpatients, were positively associated with performance; deprivation and response rates showed less consistent positive associations. No regional effects were apparent after adjusting for independent variables. CONCLUSION: The results have significant implications for quality improvement in the NHS. The finding that some NHS providers consistently perform better than others suggests that there are system-wide determinants of patient experience and the potential for learning from innovators. However, there is room for improvement overall. Given the large samples of these surveys, the messages could also have relevance for healthcare systems elsewhere.

Is the new NHS outcomes framework fit for purpose?

The coalition government's new NHS outcomes framework aims to refocus the NHS on improving outcomes for patients, avoiding the 'bureaucracy' and 'clinical distortions' of previous target-based approaches. The authors argue that its implementation will need a wider focus than on outcomes alone if the underlying goals of the NHS reforms--improving healthcare quality and outcomes in England--are to be achieved.