Objectives An update to the NICE Type 2 diabetes (T2DM) guideline in February 2022 recommended an SGLT2 inhibitor be offered to people with cardiovascular disease (CVD) or heart failure (HF) as comorbidities and considered for people at high CVD risk. We report uptake of this guideline in England 18 months after its publication. Design Observational cohort study. Setting General practices contributing to the Clinical Practice Research Data Link, linked to hospital admission records. Participants 587,826 people aged over 18 with T2DM on 1st September 2023, stratified according to their CVD category (low CVD risk score; high CVD risk score; CVD only; HF only; CVD and HF) and CKD status, and further by age, gender, ethnicity, deprivation, and T2DM diagnosis duration. Main outcome measures Percentage of patients with a current SGLT2 inhibitor prescription; odds ratios for association between patient characteristics and a current prescription. Results In people with T2DM, the percentage with a current SGLT2 inhibitor prescription was 19.5% for people with CVD, 29.4% for people with HF, 30.5% for people with both CVD and HF, and 19.9% and 20.2% respectively for people at high and low CVD risk. In age-stratified analyses, uptake ordered from lowest to highest was as follows: low CVD risk score, high CVD risk score, CVD only, HF only, CVD and HF. In models adjusted for clinical and patient characteristics uptake was lower in people aged >60, women, Black people, and people living in areas of higher deprivation. Conclusions Whilst prescribing of SGLT2 inhibitors continues to rise in England, an opportunity remains to increase uptake and to reduce inequalities in people with T2DM in 2026. We report inequalities by ethnicity and deprivation, and lower uptake for people with CVD without HF than people with HF, despite an equal guideline recommendation for these two groups. Additional evidence is needed on the effectiveness of SGLT2 inhibitors in frailer populations. ### Competing Interest Statement DJC has received investigator-initiated grants from Astra Zeneca and Novo Nordisk, support for education from Perspectum and consultancy fees from Madrigal with any financial renumeration from pharmaceutical company consultation made to the University of Liverpool. All other authors declare no competing interests. ### Funding Statement PM, JW, MR, JH, RW, EY, SR, MW, LSR and LO are employees of the National Institute for Health and Care Excellence. AA is supported by funding from NIHR Oxford Biomedical Research Centre. The authors are solely responsible for any errors or omissions. The opinions expressed in this article are those of the authors and do not necessarily reflect the position of their affiliations. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was based on data from the Clinical Practice Research Datalink obtained under licence from the UK Medicines and Healthcare products Regulatory Agency. The study was approved by the Clinical Practice Research Datalink Research Data Governance process (ID: 23_003530). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes No additional data are available; the authors are not the data controllers and do not have permission to share the data.

BACKGROUND:Modifiable risks-tobacco use, poor diet, alcohol consumption, physical inactivity and mental ill-health-drive substantial disease in UK. NICE evidence on preventive interventions targeting these risks and estimates of eligible populations and disease burden demonstrate the potential for prevention and reducing health inequalities. METHODS:Deaths and DALYs from behavioural risks and mental health conditions were estimated using GBOD 2021 data. Prevalence by deprivation quintile came from national surveys. NICE guidelines were reviewed to identify cost effective preventive interventions. RESULTS:In 2021, tobacco and dietary risks caused the highest mortality and disease burden: tobacco nearly 58 000 deaths and 1·4 million DALYs; diet 48 000 deaths and 1.05 million DALYs. Mental health had low mortality (5·7 deaths) but high DALYs (1·45 million), especially in younger people. Alcohol and inactivity had lower death counts and moderate DALY impacts. Most risks were more prevalent in deprived areas. NICE-recommended interventions such as smoking cessation, alcohol brief advice, obesity treatments, and psychological therapies, are relevant to millions, especially high-need groups. CONCLUSION:(Re-)investing in prevention and equitable strategies could substantially reduce disease burden and address inequalities, with the greatest gains likely to arise from sustained and targeted investment in populations and areas that have been left behind.

AIMS:An update to the NICE Type 2 diabetes (T2DM) guideline in February 2022 recommended an SGLT2 inhibitor be offered to people with cardiovascular disease (CVD) or heart failure (HF) as comorbidities and considered for people at high CVD risk. We report uptake of this guideline in England 18 months after its publication. MATERIALS AND METHODS:Observational cohort study using Clinical Practise Research Data Link records linked to hospital admissions. Presence of a current prescription for an SGLT2 inhibitor was evaluated in people with T2DM on 1 September 2023, stratified by CVD category (CVD only; HF only; both; high CVD risk; low CVD risk) and chronic kidney disease status, and by age, gender, ethnicity, deprivation and T2DM duration. Adjusted associations between patient characteristics and uptake were evaluated using logistic regression. RESULTS:In the cohort of 587 826 people with T2DM, the percentage with a current prescription was 19.5% for people with CVD, 29.4% for people with HF, 30.5% for people with both CVD and HF, and 19.9% and 20.2% respectively for people at high and low CVD risk. In age-stratified analyses, uptake was higher in people with more comorbidities. In adjusted models, uptake was lower in people aged > 60, women, Black people and people living in areas of higher deprivation. CONCLUSIONS:Whilst prescribing of SGLT2 inhibitors continues to rise in England, recent trends indicate an opportunity remains to increase uptake. Action is necessary to address inequalities by ethnicity and deprivation, and lower uptake for people with T2DM and CVD without HF.

Background Health inequalities remain a major public health challenge in England, with people living in more deprived areas experiencing poorer outcomes. Although SGLT2 inhibitors (SGLT2i) are clinically and cost-effective for type 2 diabetes mellitus (T2DM) and related cardiovascular and renal conditions, little is known about how their health benefits are distributed across deprivation groups. We examined the distribution of health benefits associated with SGLT2i across deprivation and clinical subgroups, and the implications for health inequalities. Methods We used data from a 2023 cross-sectional analysis of the Clinical Practice Research Datalink (CPRD), linked to Hospital Episodes Statistics (HES) and small-area deprivation data in England. T2DM prevalence and selected comorbidities and SGLT2i uptake were estimated across deprivation quintiles. A distributional cost-effectiveness analysis was used to estimate total and net health benefits (QALYs) and opportunity costs. Scenario analyses examined increased uptake and alternative distributions of opportunity costs. Results T2DM and associated comorbidities were more prevalent in more deprived areas across all subgroups. SGLT2i uptake varied modestly by deprivation but more substantially across clinical subgroups. SGLT2i generated positive net health benefits across all groups, with the largest gains accruing to more deprived populations, reflecting disease burden and baseline risk. Increasing uptake increased health gains, with similar distributional patterns across deprivation groups. Conclusions SGLT2i generate substantial net health benefits across all deprivation groups, with the greatest gains in more deprived populations. Improving uptake represents an important opportunity to improve population health while reducing health inequalities.

Health inequalities refer to systematic, unfair and avoidable differences in health across the population and between different groups in society. We reviewed health inequalities related to breast cancer to inform National Institute for Health and Care Excellence (NICE) recommendations. This was a pragmatic, targeted review to identify examples of health inequalities related to breast cancer in England. The search focused on national cancer registries, screening programme datasets, patient experience surveys and reports from key organisations. The results were synthesised using 5 domains of interest, covering health status, risk factors, wider determinants, access to and quality and experience of care. These domains were subdivided across 4 dimensions of health inequalities, including deprivation, geography, protected characteristics, and inclusion health groups. It was found that although breast cancer is less common in more deprived groups, these groups have worse health outcomes and higher mortality rates compared to less deprived groups. Many disadvantaged groups are less likely to participate in breast cancer screening, leading to delayed diagnosis and more advanced cancers. Behavioural risk factors such as obesity, physical inactivity and alcohol consumption vary across groups and impact breast cancer risks and outcomes. While people from ethnic minority groups have lower breast cancer incidence, evidence suggests that the incidence of breast cancer in some groups is increasing. Ethnic minority groups are also often diagnosed at advanced stages due to presenting through non-screening routes. Low health literacy is an issue for many disadvantaged groups. This review demonstrates that late diagnosis and low screening uptake significantly contribute to health inequalities among different groups, including deprived and ethnic minority groups. There are many gaps in the evidence, and this review further highlights potential research areas for the broader health and care system from the perspective of health inequalities.

Chronic obstructive pulmonary disease (COPD) is a common lung disease that negatively affects health-related quality of life (QoL). Utility values, which measure QoL by weighting health states with societal preferences, are required for the cost-utility models that drive economic evaluations and policy decisions. Moayeri et al. published a systematic review and meta-analysis of utilities (EQ-5D) in COPD in June 2016. The current study investigated changes in mean utilities in more recent studies thereafter, exploring heterogeneity in utilities across diverse clinical and study characteristics. Systematic searches of databases, such as MEDLINE and Embase were undertaken from 1 July 2015 until 20 May 2024. A random-effects meta-analysis of utilities (EQ-5D) was performed which addressed inter-study heterogeneity and subgroup analyses. The pooled general mean (95% CI) utility value was 0.761 (0.726-0.795) from 43 studies, whereas Moayeri et al. reported 0.673 (0.653-0.693) from 32 studies. This improvement in mean utilities could be due to increased awareness, early detection, and better medical interventions over the past decade, but demonstrates that a general utility value should be approached with caution given significant heterogeneity. Four meta-regressions were performed on each subgroup: region, method of elicitation, reported comorbidities, and disease stage; of which, method of elicitation, disease stage, and region were found to be significant moderators of utilities. It is, therefore, important to use meta-analysed utilities for cost-utility analyses that reflect the context and patient population of the model. Moreover, these results provide additional evidence for the precision and sensitivity of EQ-5D-5L over EQ-5D-3L.

Key points NICE seeks to reduce health inequalities through its guidance. NICE uses equality and health inequalities assessment (EHIA) to identify and address health inequalities. A health inequalities briefing was developed for breast cancer‐related guidance to consider and address health inequalities more systematically. The committee made recommendations that consider the impact of health inequalities on access and adherence. Further research is recommended for interventions targeting specific population subgroups. The health inequalities briefing identified late diagnosis and screening variations as key issues among deprived women and ethnic minority groups, which was passed on to the National Institute for Health and Care Research as a research priority.

Background Tailored smoking cessation interventions, which combine behavioural and pharmaceutical support, are effective in populations with severe mental illness (SMI). We establish the cost-effectiveness of two tailored interventions in the UK: (i) a bespoke smoking cessation intervention (BSCI) versus usual care, and (ii) integrated tobacco cessation and mental health care (IC) versus standard smoking cessation clinic (SCC) referral.Methods This economic evaluation was conducted between January 15th 2019 and August 4th 2022. We adapted a Markov model estimating smoking status, healthcare costs and quality-adjusted life years (QALYs) across the lifetime. Intervention effectiveness and costs were obtained from a systematic review and a meta-analysis. We obtained specific parameter values for populations with SMI for mortality, risk of smoking related comorbidities, and health utility. Uncertainty was analysed in deterministic and probabilistic sensitivity analysis (PSA).Findings The BSCI was cost-effective versus usual care with an incremental cost-effectiveness ratio (ICER) of 3145 pound per QALY (incremental costs: 165; pound incremental QALYs: 0.05). Integrated care was cost-effective versus SCC with an ICER of 6875 pound per QALY (incremental costs: 292; pound incremental QALYs: 0.04). The BSCI and IC were cost-effective in 89% and 83% of PSA iterations respectively. The main area of uncertainty related to relapse rates.Interpretation Our findings suggested that the tailored interventions were cost-effective and could increase QALYs and decrease expenditure on treating smoking related morbidities if offered to people with SMI.

The updated NICE guidelines on tobacco recommend cost-effective and evidence-based interventions to prevent smoking initiation and promote smoking cessation across the life course. E-cigarettes are a cost-effective adjunct to support smoking cessation in adults, but their long-term effects are yet to be fully understood. Concerted efforts from healthcare and public health providers are required to reach underserved groups and hence address stark and longstanding inequalities in smoking prevalence and associated ill health in England.

The National Institute for Health and Care Excellence (NICE) was originally created to reduce the so-called postcode lottery in health care, but there have been regional inequalities in the implementation of NICE guidelines, especially regarding access to specialist care for people with epilepsy.1NHS EnglandNeurological focus pack tool.http://tools.england.nhs.uk/cfv2016/neurological/atlas.htmlDate accessed: January 16, 2022Google Scholar A national audit, carried out annually by the Healthcare Quality Improvement Partnership, showed that, in 2020, fewer than one in five children and young people (ie, aged 18 years or younger) with epilepsy could access certain specialised diagnostic and treatment procedures (eg, EEG or sedated MRI) locally.2HQIPRCPHCHEpilepsy12: national clinical audit of seizures and epilepsies for children and young people.https://www.rcpch.ac.uk/sites/default/files/202107/Epilepsy12%20summary%20report%203.3_0.pdfDate: 2020Date accessed: March 2, 2022Google Scholar Accessing these services farther from their homes might not be feasible for individuals from deprived background because of financial or logistical barriers which could, in turn, exacerbate inequalities. A similar audit on epilepsy services for adults could provide much-needed evidence to inform guidelines and commissioning. However, national audits require large investments of resources and the engagement of multiple stakeholders to assess the drivers of inequalities (eg, age, disability, ethnicity, and sex) beyond regional considerations. Moreover, national audits are, by themselves, insufficient to provide the evidence needed for NICE guidelines, which rely primarily on evidence from randomised clinical trials. Populations that experience inequalities are under-represented in randomised clinical trials, particularly when drivers of inequalities (eg, old age, disability) are used as exclusion criteria, even in the absence of a sound rationale to do so.3Shenoy P Harugeri A Elderly patients' participation in clinical trials.Perspect Clin Res. 2015; 6: 184-189Crossref PubMed Google Scholar, 4Shankar R Rowe C Van Hoorn A et al.Under representation of people with epilepsy and intellectual disability in research.PLoS One. 2018; 13e0198261Crossref Scopus (12) Google Scholar, 5Ernst LD Let's Talk About Sex: Integrating sex as a biological variable into epilepsy research.Epilepsy Curr. 2018; 18: 292-294Crossref PubMed Scopus (3) Google Scholar The original NICE guidelines on the diagnosis and management of epilepsy (NG137) were published in 2004 and an update is expected in 2022. The absence of high-quality evidence will preclude NICE from making specific recommendations for patient subgroups who might experience inequalities in diagnosis or management on the basis of age, sex, socioeconomic status, ethnicity, or disability. Although some evidence from observational or small non-randomised studies is available, lowering the standards used to make recommendations for these patient subgroups would put their safety at risk. Furthermore, lowering these standards could exacerbate inequalities by incentivising non-evidence-based care in already disadvantaged or underserved patient subgroups. NICE has formally acknowledged its commitment to address inequalities in its 5-year strategy, but the absence of evidence has been a substantial hindrance. Data are not disaggregated by factors associated with inequalities. Furthermore, datasets are not publicly available in accessible repositories. De-anonymised and aggregated data should be shared between agencies within the Department for Health and Social Care. If high-quality data are not collected and made available to NICE, its commitment to address inequalities will be in jeopardy. We declare no competing interests

Background: People with respiratory conditions are susceptible to health problems caused by exposure to indoor air pollutants. An economic framework was developed to inform a guideline developed by National Institute for Health and Care Excellence (NICE) to estimate the required level of efficacy necessary for an intervention to be cost-saving in dwellings across England. Methods: An economic modelling framework was built to estimate the incremental costs pre- and post-implementation of interventions designed to reduce exposure to indoor air pollution within dwellings of varying building-related risk factors and profiles. The intervention cost was varied simultaneously with the relative reduction in symptomatic cases of each health condition to estimate the point at which an intervention may become cost-saving. Four health conditions were considered. Results: People living in dwellings with either an extreme risk profile or usable floor area <90 m2 have the greatest capacity to benefit and save National Health Service (NHS) costs from interventions at any given level of effectiveness and upfront cost. Conclusions: At any effectiveness level, the threshold for the upfront intervention cost to remain cost-saving is equivalent across the different home characteristics. The flexible model can be used to guide decision-making under a range of scenarios.

Introduction: Reduction of health inequality is a goal in health policy, but commissioners lack information on how policies change health inequality. This study illustrates how decision models can be readily extended to produce information on health inequality impacts as well as for population health, using the example of smoking cessation therapies. Methods: We retrospectively adapt a model developed for public health guidance to undertake distributional cost effectiveness analysis. We identify and incorporate evidence on how inputs vary by area-level deprivation. Therapies are evaluated in terms of total population health, extent of inequality, and a summary measure of equally distributed equivalent health based on a societal value for inequality aversion. Last, we examine how accounting for social variation in different sets of parameters affects our results. Results: All interventions increase population health and increase the slope index of inequality. At estimated levels of health inequality aversion for England, our resultsindicate that the increases in inequality are compensated by the health gains. Discussion: The inequality impacts are driven by higher benefits of quitting and higher intervention uptake amongst advantaged groups, despite the greater proportion of smokers in disadvantaged groups. Failure to account for differential effects between groups leadsto different conclusions about health inequality impact but does not alter conclusionsabout value for money.

This article covers recent National Institute for Health and Care Excellence (NICE) guidance relevant to public health, with a focus on indoor air quality. It introduces the evidence behind this guideline, and the actions that need to be taken by a wide range of stakeholders to implement the guidance and help people to achieve good air quality in their homes. It also highlights the inequalities in exposure to poor quality indoor air and identifies groups that are more vulnerable to health impacts.

INTRODUCTION:We describe a simplified distributional cost-effectiveness analysis based on aggregate data to estimate the health inequality impact of public health interventions.METHODS:We extracted data on costs, health outcomes expressed as quality-adjusted life years (QALYs), and target populations for interventions within National Institute for Health and Care Excellence (NICE) public health guidance published up to October 2016. Evidence on variation by age, gender, and index of multiple deprivation informed socioeconomic distributions of incremental QALYs, health opportunity costs, and the baseline distribution of health. Total population QALYs, summary measures of inequality, and a health equity impact plane show results by intervention and by guideline. A value for inequality aversion from a general population survey in England let us combine impacts on health inequality and total health into a single measure of intervention value.RESULTS:Our estimates suggest that of 134 interventions considered by NICE, 70 (52%) reduce inequality and increase health, 21 (16%) involve a tradeoff between improving health and improving health inequality, and 43 (32%) reduce health and increase health inequality. Fully implemented, the potential impact of all recommendations was 23,336,181 additional QALYs for the population of England and Wales and a reduction of the gap in quality-adjusted life expectancy between the healthiest and least healthy from 13.78 to 13.34 QALYs. The combined value of the additional health and reduction in inequality was 28,723,776 QALYs.DISCUSSION:Our analysis takes account of the fact that existing public health spending likely benefits the most disadvantaged. This simple method applied separately to economic evaluation produces evidence of intervention impacts on the distribution of health that is vital in determining value for money when health inequality reduction is a policy goal.