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Background No current guidance is available in the UK on the choice of preference-based measure (PBM) that should be used in obtaining health-related quality of life from children. The aim of this study is to review the current usage of PBMs for obtaining health state utility values in child and adolescent populations, and to obtain information on patient and parent-proxy respondent preferences in completing PBMs in the UK. Methods A literature review was conducted to determine which instrument is most frequently used for child-based economic evaluations and whether child or proxy responses are used. Instruments were compared on dimensions, severity levels, elicitation and valuation methods, availability of value sets and validation studies, and the range of utility values generated. Additionally, a series of focus groups of parents and young people (11-20 years) were convened to determine patient and proxy preferences. Results Five PBMs suitable for child populations were identified, although only the Health Utilities Index 2 (HUI2) and Child Heath Utility 9D (CHU-9D) have UK value sets. 45 papers used PBMs in this population, but many used non-childspecific PBMs. Most respondents were parent proxies, even in adolescent populations. Reported missing data ranged from 0.5 to 49.3%. The focus groups reported their experiences with the EQ-5D-Y and CHU-9D. Both the young persons' group and parent/proxy groups felt that the CHU-9D was more comprehensive but may be harder for a proxy to complete. Some younger children had difficulty understanding the CHU-9D questions, but the young persons' group nonetheless preferred responding directly. Conclusion The use of PBMs in child populations is increasing, but many studies use PBMs that do not have appropriate value sets. Parent proxies are the most common respondents, but the focus group responses suggest it would be preferred, and may be more informative, for older children to self-report or for child-parent dyads to respond.

ObjectivesRates of overweight and obesity vary across England, but local rates have not been estimated for over 10 years. We aimed to produce new small area estimates of body mass index (BMI) by age and sex for each lower tier and unitary local authority in England, to provide up-to-date and more detailed estimates for the use of policy-makers and academics working in non-communicable disease risk and health inequalities.DesignWe used generalised linear modelling to estimate the relationship between BMI with social/demographic markers in a cross-sectional survey, then used this model to impute a BMI for each adult in locally-representative populations. These groups were then disaggregated by 5-year age group, sex and local authority group.SettingThe Health Survey for England 2018 (cross-sectional BMI data for England) and Census microdata 2011 (locally representative).ParticipantsA total of 6174 complete cases aged 16 and over were included.Outcome measuresModelled group-level BMI as mean and SD of log-BMI. Extensive internal validation was performed, against the original data and external validation against the National Diet and Nutrition Survey and Active Lives Survey and previous small area estimates.ResultsIn 94% of age–sex are groups, mean BMI was in the overweight or obese ranges. Older and more deprived areas had the highest overweight and obesity rates, which were particularly in coastal areas, the West Midlands, Yorkshire and the Humber. Validation showed close concordance with previous estimates by local area and demographic groups.ConclusionThis work updated previous estimates of the distribution of BMI in England and contributes considerable additional detail to our understanding of the local epidemiology of overweight and obesity. Raised BMI now affects the vast majority of demographic groups by age, sex and area in England, regardless of geography or deprivation.

Surveys in various countries suggest 17% to 80% of doctors prescribe 'placebos' in routine practice, but prevalence of placebo use in UK primary care is unknown. We administered a web-based questionnaire to a representative sample of UK general practitioners. Following surveys conducted in other countries we divided placebos into 'pure' and 'impure'. 'Impure' placebos are interventions with clear efficacy for certain conditions but are prescribed for ailments where their efficacy is unknown, such as antibiotics for suspected viral infections. 'Pure' placebos are interventions such as sugar pills or saline injections without direct pharmacologically active ingredients for the condition being treated. We initiated the survey in April 2012. Two reminders were sent and electronic data collection closed after 4 weeks. We surveyed 1715 general practitioners and 783 (46%) completed our questionnaire. Our respondents were similar to those of all registered UK doctors suggesting our results are generalizable. 12% (95% CI 10 to 15) of respondents used pure placebos while 97% (95% CI 96 to 98) used impure placebos at least once in their career. 1% of respondents used pure placebos, and 77% (95% CI 74 to 79) used impure placebos at least once per week. Most (66% for pure, 84% for impure) respondents stated placebos were ethical in some circumstances. Placebo use is common in primary care but questions remain about their benefits, harms, costs, and whether they can be delivered ethically. Further research is required to investigate ethically acceptable and cost-effective placebo interventions.

Healthcare interventions, and particularly those in public health may affect multiple diseases and significantly prolong life. No consensus currently exists for how to estimate comparable healthcare costs across multiple diseases for use in health and public health cost-effectiveness models. We aim to describe a method for estimating comparable disease specific English healthcare costs as well as future healthcare costs from diseases unrelated to those modelled. We use routine national datasets including programme budgeting data and cost curves from NHS England to estimate annual per person costs for diseases included in the PRIMEtime model as well as age and sex specific costs due to unrelated diseases. The 2013/14 annual cost to NHS England per prevalent case varied between £3,074 for pancreatic cancer and £314 for liver disease. Costs due to unrelated diseases increase with age except for a secondary peak at 30-34 years for women reflecting maternity resource use. The methodology described allows health and public health economic modellers to estimate comparable English healthcare costs for multiple diseases. This facilitates the direct comparison of different health and public health interventions enabling better decision making.

Background Non-communicable diseases are the leading cause of death in England, and poor diet and physical inactivity are two of the principle behavioural risk factors. In the context of increasingly constrained financial resources, decision makers in England need to be able to compare the potential costs and health outcomes of different public health policies aimed at improving these risk factors in order to know where to invest so that they can maximise population health. This paper describes PRIMEtime CE, a multistate life table cost-effectiveness model that can directly compare interventions affecting multiple disease outcomes. Methods The multistate life table model, PRIMEtime Cost Effectiveness (PRIMEtime CE), is developed from the Preventable Risk Integrated ModEl (PRIME) and the PRIMEtime model. PRIMEtime CE uses routinely available data to estimate how changing diet and physical activity in England affects morbidity and mortality from heart disease, stroke, diabetes, liver disease, and cancers either directly or via raised blood pressure, cholesterol, and body weight. Results Model outcomes are change in quality adjusted life years, and change in English National Health Service and social care costs. Conclusion This paper describes PRIMEtime CE and highlights its main strengths and limitations. The model can be used to compare any number of public policies affecting diet and physical activity, allowing decision makers to understand how they can maximise population health with limited financial resources.

Historically, the NHS did not routinely collect cost data, unlike many countries with private insurance markets. In 1998, for the first time the government mandated NHS trusts to submit estimates of their costs of service, known as reference costs. These have informed a wide range of health economic evaluations and important functions in the health service, such as setting prices.Reference costs are collected by progressively disaggregating budgets top-down into disease and treatment groups. Despite ongoing improvements to methods and guidance, these submissions continued to suffer a lack of accuracy and comparability, fundamentally undermining their credibility for critical functions.To overcome these issues, there was a long-held ambition to collect “patient-level” cost data. Patient-level costs are estimated with a combination of disaggregating budgets but also capturing the patient-level “causality of costs” bottom-up in the allocation of resources to patient episodes. These not only aim to capture more of the drivers of costs, but also improve consistency of reporting between providers.The change in methods may confer improvements to data quality, though judgement is still required and achieving consistency between trusts will take further work. Estimated costs may also change in important ways that may take many years to fully understand. We end on a cautionary note that patient-level cost methods may unlock potential, they alone contribute little to our understanding of the complexities involved with service quality or need, while that potential will require substantial investment to realise. Many healthcare resources cannot be attributed to individual patients so the very notion of “patient-level” costs may be misplaced. High hopes have been put in these new data, though much more work is now necessary to understand their quality, what they show and how their use will impact the system.

Quality of life (QoL) is an important measure of disease burden and general health perception. The relationship between early chronic kidney disease (CKD) and QoL remains poorly understood. The Oxford Renal Study (OxRen) cohort comprises 1063 adults aged [greater than or equal to]60 years from UK primary care practices screened for early CKD, grouped according to existing or screen-detected CKD diagnoses, or biochemistry results indicative of reduced renal function (referred to as transient estimated glomerular filtration rate (eGFR) reduction). This study aimed to compare QoL in participants known to have CKD at recruitment to those identified as having CKD through a screening programme. Health profile data and multi-attribute utility scores were reported for two generic questionnaires: 5-level EuroQol-5 Dimension (EQ-5D-5L) and ICEpop CAPability measure for Adults (ICECAP-A). QoL was compared between patients with existing and screen-detected CKD; those with transient eGFR reduction served as the reference group in univariable and multivariable linear regression. Mean and standard deviation utility scores were not significantly different between the subgroups for EQ-5D-5L (screen-detected:0.785±0.156, n = 480, transient:0.779±0.157, n = 261, existing CKD:0.763±0.171, n = 322, p = 0.216) or ICECAP-A (screen-detected:0.909±0.094, transient:0.904±0.110, existing CKD:0.894±0.115, p = 0.200). Age, smoking status, and number of comorbidities were identified as independent predictors of QoL in this cohort. QoL of participants with existing CKD diagnoses was not significantly different from those with screen-detected CKD or transient eGFR reduction and was similar to UK mean scores for the same age, suggesting that patient burden of early CKD is minor. Moreover, CKD-related comorbidities contribute more significantly to disease burden in earlier stages of CKD than renal function per se. Larger prospective studies are required to define the relationship between QoL and CKD progression more precisely. These data also confirm the essentially asymptomatic nature of CKD, implying that routine screening or case finding are required to diagnose it.

Background PRIMEtime CE is a multistate life table model that can directly compare the cost effectiveness of public health interventions affecting diet and physical activity levels, helping to inform decisions about how to spend finite resources. This paper estimates the costs and health outcomes in England of two scenarios: reformulating salt and expanding subsidised access to leisure centres. The results are used to help validate PRIMEtime CE, following the steps outlined in the Assessment of the Validation Status of Health-Economic decision models (AdViSHE) tool. Methods The PRIMEtime CE model estimates the difference in quality adjusted life years (QALYs) and difference in NHS and social care costs of modelled interventions compared with doing nothing. The salt reformulation scenario models how salt consumption would change if food producers met the 2017 UK Food Standards Agency salt reformulation targets. The leisure centre scenario models change in physical activity levels if the Birmingham Be Active scheme (where swimming pools and gym access is free to residents during defined periods) was rolled out across England. The AdViSHE tool was developed by health economic modellers and divides model validation into five parts: validation of the conceptual model, input data validation, validation of computerised model, operational validation, and other validation techniques. PRIMEtime CE is discussed in relation to each part. Results Salt reformulation was dominant compared with doing nothing, and had a 10-year return on investment of £1.44 (£0.50 to £2.94) for every £1 spent. By contrast, over 10 years the Be Active expansion would cost £727,000 (£514,000 to £1,064,000) per QALY. PRIMEtime CE has good face validity of its conceptual model and has robust input data. Cross-validation produces mixed results and shows the impact of model scope, input parameters, and model structure on cost-per-QALY estimates. Conclusions This paper illustrates how PRIMEtime CE can be used to compare the cost-effectiveness of two different public health measures affecting diet and physical activity levels. The AdViSHE tool helps to validate PRIMEtime CE, identifies some of the key drivers of model estimates, and highlights the challenges of externally validating public health economic models against independent data.

Background To estimate life years and quality-adjusted life years (QALYs) lost and the economic burden of aneurysmal subarachnoid haemorrhage (aSAH) in the United Kingdom including healthcare and non-healthcare costs from a societal perspective. Methods All UK residents in 2005 with aSAH (International Classification of Diseases 10 th revision (ICD-10) code I60). Sex and age-specific abridged life tables were generated for a general population and aSAH cohorts. QALYs in each cohort were calculated adjusting the life tables with health-related quality of life (HRQL) data. Healthcare costs included hospital expenditure, cerebrovascular rehabilitation, primary care and community health and social services. Non-healthcare costs included informal care and productivity losses arising from morbidity and premature death. Results A total of 80,356 life years and 74,807 quality-adjusted life years were estimated to be lost due to aSAH in the UK in 2005. aSAH costs the National Health Service (NHS) £168.2 million annually with hospital inpatient admissions accounting for 59%, community health and social services for 18%, aSAH-related operations for 15% and cerebrovascular rehabilitation for 6% of the total NHS estimated costs. The average per patient cost for the NHS was estimated to be £23,294. The total economic burden (including informal care and using the human capital method to estimate production losses) of a SAH in the United Kingdom was estimated to be £510 million annually. Conclusion The economic and disease burden of aSAH in the United Kingdom is reported in this study. Decision-makers can use these results to complement other information when informing prevention policies in this field and to relate health care expenditures to disease categories.

Background At least 5 years of adjuvant endocrine therapy substantially reduces risks of recurrence and mortality in oestrogen-receptor positive early breast cancer. However, adherence to endocrine therapy is sub-optimal; poor adherence is associated with higher risks of recurrence and death from breast cancer, worse cancer-specific health-related quality-of-life, and increased healthcare costs. The SWEET randomised control trial aims to evaluate effectiveness and cost-effectiveness of the HT&Me intervention in reducing poor adherence to adjuvant endocrine therapy and improve cancer-specific health-related quality-of-life in women with oestrogen-receptor positive early breast cancer. Methods This is a UK based, pragmatic, open label randomised control trial. Participants (stages 1–3 oestrogen-receptor positive breast cancer, completed surgery, within 14 weeks of first endocrine therapy prescription; n  = 1460) complete a baseline questionnaire, and are randomised to the HT&Me intervention plus usual care, or usual care alone. The HT&Me intervention is evidence-based, theory-informed and patient-centred. It consists of viewing an animation, two consultations with a SWEET study practitioner (a health care professional trained in delivering the intervention) approximately 3 months apart, access to the interactive HT&Me web-app for the 18 months, and regular monthly nudges. All participants complete follow-up questionnaires at 6, 12, and 18 months. A multi-method process evaluation will be conducted involving quantitative analysis exploring mechanisms of action of the intervention, and qualitative interviews with a sample of participants and health care professionals involved in the trial. Primary endpoints are adjuvant endocrine therapy adherence (combined self-report (Medication Adherence Report Scale) and Proportion of Days Covered calculated from prescription encashment records) and cancer-specific health-related quality-of-life (Functional Assessment of Cancer Therapy Scale- General). Secondary endpoints are adjuvant endocrine therapy-specific health-related quality-of-life and within-trial cost-utility analysis which will evaluate cost-effectiveness. Discussion The SWEET trial seeks to address a significant issue affecting the growing population of breast cancer survivors: poor adherence to adjuvant endocrine therapy. Challenges addressed and resolved within the protocol include the following: capacity at sites to deliver the intervention; variations in breast cancer services nationally; and measuring adherence. This trial has potential to improve quality of life and adherence to endocrine therapy; reducing numbers of recurrences and breast cancer deaths, benefiting women, their families and the health service. Trial registration ISRCTN Number: ISRCTN24852890 registered on 02.08.2023.