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Congenital thrombotic thrombocytopenic purpura (cTTP) is an ultra rarehaematological disorder. This study aimed to estimate the clinical burden, healthcareresource use (HCRU) and associated costs of cTTP in England using primary andsecondary care data. A retrospective cohort study was undertaken using the ClinicalPractice Research Datalink (Aurum) linked to Hospital Episode Statistics data. Thestudy period was from 01 January 2000 to 31 December 2019. Patients with cTTPwere identified using an algorithm and matched 1:2 to patients without thromboticthrombocytopenic purpura (TTP) (non-TTP cohort) to contextualise the findings. Atotal of 36 cTTP patients were identified. The mean follow-up for cTTP patients was4.4 and 5.7 years in primary and secondary care, respectively, and 4.9 and 5.8 yearsfor the non-TTP cohort. Of the 36 patients, 38.9% experienced an acute episodeand 19.4% experienced an organ damage event during follow-up. HCRU (includinginpatient admission, outpatient appointments and primary care appointments) washigher in the cTTP cohort relative to the non-TTP cohort. The average yearly cost ofhealthcare for a cTTP patient was £6155, relative to £858 in the non-TTP cohort. Thisstudy demonstrates the high clinical and economic burden of cTTP and providesevidence to inform healthcare planning.
BACKGROUND: The long-term use of strong opioids for chronic non-cancer pain puts people at risk of serious harm.
OBJECTIVES: To test the effectiveness and cost-effectiveness of a multicomponent intervention targeting opioid use for the treatment of chronic pain.
INTERVENTIONS: Participants were randomised 1 : 1 (using a minimisation programme stratified by geographical locality, baseline pain intensity score and baseline morphine equivalent dose) to either usual care (an educational booklet and relaxation compact disc) or usual care plus the I-WOTCH intervention; 3 day-long group sessions delivered by a nurse and lay facilitator, plus a one-to-one session and ongoing telephone contact from the nurse to support opioid tapering.
RESULTS: We randomised 608 people. At 12 months, there was no between-group difference in Patient-Reported Outcomes Measurement Information System Pain Interference Short Form (8A) scores; mean difference, −0.52 (95% confidence interval −1.94 to 0.89). At 12 months, 65/225 (29%) of people in the intervention group and 15/208 (7%) of people in usual-care group reported using no opioids [odds ratio 5.55 (95% confidence interval 2.80 to 10.99)], absolute difference, 21.7% (95% confidence interval 14.8 to 28.6). Over a lifetime horizon, I-WOTCH is on average associated with an incremental cost of £9277 per person, and provides an additional 0.314 quality-adjusted life-years. The deterministic incremental cost per quality-adjusted life-year gained was £29,543. The I-WOTCH intervention may be cost-effective compared to best usual care. The process evaluation suggested group support and shared experience were important to those trying to taper.
LIMITATIONS: The opioid use analysis is based solely on participant self-report. The findings only apply to people willing to consider opioid reduction and may not apply to a more complex secondary care population. The results may not be applicable to people using very high opioid doses.
CONCLUSIONS: The I-WOTCH intervention helps substantially more people stop opioids than best usual care without adversely affecting pain interference.
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.
Poor mental wellbeing is one of the leading causes of long-term sickness absence from work and may lead to absenteeism, presenteeism and staff turnover, costing UK employers an estimated £51 billion annually. This study uses economic modelling to provide data on costs and benefits to employers who are considering implementing a workplace intervention to improve wellbeing. Additionally, the analysis is used to assess any changes in employee outcomes (e.g., productivity and staff turnover). A cost-consequence model with a one-year time horizon was developed to assess the impact of workplace mental wellbeing interventions. Because all workplaces are different, it is not useful to present one single base case to generalise across all settings. Instead, the model generates a series of hypothetical case studies, with varying levels of absenteeism, presenteeism and staff turnover, as well as different levels of productivity and staff replacement costs. Several mental wellbeing interventions are compared with ‘no intervention’ (current practice) to calculate the total incremental costs and incremental cost per employee. In a hypothetical case study with 50 employees and an intervention cost of £100, the intervention has a net cost saving of £4,207 per employee. Savings are due to reductions in absenteeism and presenteeism. Sensitivity analysis and scenario analysis assess the impact of varying each input, to reflect that inputs will vary substantially for each individual organisation and setting. The intervention is more likely to be cost saving when the baseline levels of absenteeism, presenteeism and staff turnover are high, and the intervention cost is low. Mental wellbeing interventions may influence a range of outcomes, but outcomes demonstrating a mental wellbeing benefit to employees may be challenging to translate into monetary value. The model can be used by decision makers and employers to understand the potential economic and wellbeing implications of implementing workplace mental wellbeing interventions.
PURPOSE: Health-related quality of life (HRQoL) measures in the form of health utilities are valuable for economic evaluations of the effectiveness of food allergy interventions. However, traditional HRQoL instruments lack the sensitivity to generate health utilities that capture the impact that food allergies, such as peanut allergies, may have on children’s mental health and daily activities. This study used mapping and discrete choice experiment (DCE) methods to generate health utilities from the Food Allergy Quality of life Questionnaire–Parent Form (FAQLQ-PF), which were then applied to clinical trial data.
PATIENTS AND METHODS: Health utilities (HU) were generated using two methods: mapping and DCE. Parents of children with peanut allergies (N=159) completed the FAQLQ-PF and EQ-5D-Y-Proxy-1 questionnaires. Mapping algorithms were developed once the FAQLQ-PF responses were mapped onto the EQ-5D-3L utilities. A composite DCE with time trade-off and a vignette was conducted among parents without peanut allergic children (N=767). The utilities derived from the mapping and DCE methods were applied to clinical trial data (PEPITES and PEOPLE) for an epicutaneous peanut patch (DBV712).
RESULTS: The mapping algorithm showed an association of 0.199 between FAQLQ-PF and EQ-5D-3L utilities. The DCE disutilities were highest for severe food-related anxiety, emotional distress, and social limitations. Once applied to the clinical trial data, the HU derived from the mapping algorithm demonstrated statistically significant HRQoL improvements for the intervention group at 36 months. Using the DCE-derived utilities, statistically significant HRQoL improvements for the intervention group were demonstrated at both 24- and 36-months. The effect size analysis demonstrated that the DCE-derived utilities were more responsive than mapped utilities.
CONCLUSION: DCE-derived utilities demonstrated greater responsiveness to changes in HRQoL compared with mapped utilities, suggesting their potential use in economic evaluations and HTA submissions for peanut allergy interventions. The DCE-derived health utilities showed greater sensitivity to changes in HRQoL. These utilities can be used in health technology assessments to better capture the impact of peanut allergy treatments on children’s quality of life.
BACKGROUND: Lung cancer is a leading cause of cancer death, and smoking-related disease is a major cause of health inequality in England, driven by increased prevalence of smoking in deprived areas. Integrating smoking cessation support into the English Lung Cancer Screening (LCS) programme may optimize services and has been found cost-effective. However, limited evidence is available on its health equity impact.
AIM: The objective was to conduct an aggregate distributional cost-effectiveness analysis (DCEA) of providing smoking cessation as part of LCS compared with usual care (referral to stop smoking services) to estimate its impact on health inequalities and health-related social welfare in England.
METHODS: The DCEA used an aggregate approach, stratifying people who smoke, aged 55–74 who were attending LCS by Index of Multiple Deprivation (IMD) quintiles. Discounted incremental costs and quality-adjusted life years (QALYs) were derived from a Markov model, adapted from previous NICE guidelines. The base case analysis applied a Health Opportunity Cost (HOC) of £15,000 per QALY and an Atkinson inequality aversion parameter (IAP) of 6.5, assuming a equal distribution across groups for intervention uptake.
RESULTS: Under all base case assumptions, smoking cessation provided as part of targeted LCS had a positive net health benefit and health equity impact. The intervention dominated usual care, resulting in a total net health benefit of 142,035 QALYs. The distribution of benefit strongly favored the most deprived quintile (IMD1: 34,863 QALYs vs. IMD5: 23,612 QALYs), driven by smoking prevalence.
CONCLUSION: Reforming smoking cessation services as part of LCS would likely improve both population health and health equity. Uptake of smoking cessation is a key determinant of the impact on health inequalities, underscoring the importance of targeted implementation strategies for optimizing population health, while reducing health inequalities.
Undertaking health economic modelling to compare in vitro diagnostics (IVDs) with imaging tests in health technology assessment (HTA) is associated with several challenges. Ignoring these challenges can lead to inaccurate and misleading results. This research identified common challenges and developed practical recommendations for considering them. An iterative, multi-methods approach was taken, including a methods review of HTA submissions, journal articles and published reports; a workshop; and semi-structured interviews with experts in health economic modelling of diagnostics. Key challenges and potential solutions were identified in the methods review and expanded in the workshop. Interviews were conducted to validate and refine challenges and practical recommendations. Recommendations were scored (from 1 [strong disagreement] to 5 [strong agreement]) by experts before and after the interviews. Final recommendations had a median score ≥ 4 (post-interview). 85 challenges (from the methods review) were prioritised into 21 with 57 recommendations after the workshop. After the interviews, recommendations were categorised into those for overcoming general challenges or challenges arising from specific aspects of the value proposition. Overall, 19 challenges with 30 recommendations are presented. To our knowledge, this is the first study investigating challenges to health economic modelling when comparing IVDs with imaging tests in HTA. The recommendations cover several topics, including variability in the diagnostic pathway, uncertain data or lack of evidence, incidental findings, and capacity constraints. Our recommendations present non-binding, guiding principles for good practice. Researchers should judge the applicability of each challenge and consider those recommendations carefully.
