Burden of disease and costs of aneurysmal subarachnoid haemorrhage (aSAH) in the United Kingdom

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>All UK residents in 2005 with aSAH (International Classification of Diseases 10^threvision (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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

Patient preferences for management of high blood pressure in the UK:A discrete choice experiment

Background: With a variety of potentially effective hypertension management options, it is important to determine how patients value different models of care, and the relative importance of factors in their decision-making process. Aim: To explore patient preferences for the management of hypertension in the UK. Design and setting: Online survey of patients who have hypertension in the UK including an unlabelled discrete choice experiment (DCE). Method: A DCE was developed to assess patient preferences for the management of hypertension based on four attributes: model of care, frequency of blood pressure (BP) measurement, reduction in 5-year cardiovascular risk, and costs to the NHS. A mixed logit model was used to estimate preferences, willingness-to-pay was modelled, and a scenario analysis was conducted to evaluate the impact of changes in attribute levels on the uptake of different models of care. Results: One hundred and sixty-seven participants completed the DCE (aged 61.4 years, 45.0% female, 82.0% >5 years since diagnosis). All four attributes were significant in choice (P<0.05). Reduction in 5-year cardiovascular risk was the main driver of patient preference as evidenced in the scenario and willingness-to-pay analyses. GP management was significantly preferred over self-management. Patients preferred scenarios with more frequent BP measurement, and lower costs to the NHS. Conclusion: Participants had similar preferences for GP management, pharmacist management, and telehealth, but a negative preference for self-management. When introducing new models of care for hypertension to patients, discussion of the potential benefits in terms of risk reduction should be prioritised to maximise uptake

Valuation and modeling of EQ-5D-5L health states using a hybrid approach

Background: The EQ-5D instrument is the most widely used preference-based health-related quality of life questionnaire in cost-effectiveness analysis of health care technologies. Recently, a version called EQ-5D-5L with 5 levels on each dimension was developed. This manuscript explores the performance of a hybrid approach for the modeling of EQ-5D-5L valuation data. Methods: Two elicitation techniques, the composite time trade-off, and discrete choice experiments, were applied to a sample of the Spanish population (n=1000) using a computer-based questionnaire. The sampling process consisted of 2 stages: stratified sampling of geographic area, followed by systematic sampling in each area. A hybrid regression model combining composite time trade-off and discrete choice data was used to estimate the potential value sets using main effects as starting point. The comparison between the models was performed using the criteria of logical consistency, goodness of fit, and parsimony. Results: Twenty-seven participants from the 1000 were removed following the exclusion criteria. The best-fitted model included 2 significant interaction terms but resulted in marginal improvements in model fit compared to the main effects model. We therefore selected the model results with main effects as a potential value set for this methodological study, based on the parsimony criteria. The results showed that the main effects hybrid model was consistent, with a range of utility values between 1 and -0.224. Conclusion: This paper shows the feasibility of using a hybrid approach to estimate a value set for EQ-5D-5L valuation data.</p

Exploring women's preferences for birth settings in England:a discrete choice experiment

<div><p>Objective</p><p>To explore pregnant women’s preferences for birth setting in England.</p><p>Design</p><p>Labelled discrete choice experiment (DCE).</p><p>Setting</p><p>Online survey.</p><p>Sample</p><p>Pregnant women recruited through social media and an online panel.</p><p>Methods</p><p>We developed a DCE to assess women’s preferences for four hypothetical birth settings based on seven attributes: reputation, continuity of care, distance from home, time to see a doctor, partner able to stay overnight, chance of straightforward birth and safety for baby. We used a mixed logit model, with setting modelled as an alternative-specific constant, and conducted a scenario analysis to evaluate the impact of changes in attribute levels on uptake of birth settings.</p><p>Main outcome measures</p><p>Women’s preferences for birth setting.</p><p>Results</p><p>257 pregnant women completed the DCE. All birth setting attributes, except ‘time to see doctor’, were significant in women’s choice (p<0.05). There was significant heterogeneity in preferences for some attributes. Changes to levels for ‘safety for the baby’ and ‘partner able to stay overnight’ were associated with larger changes from baseline uptake of birth setting. If the preferences identified were translated into the real-world context up to a third of those who reported planning birth in an obstetric unit might choose a midwifery unit assuming universal access to all settings, and knowledge of the differences between settings.</p><p>Conclusions</p><p>We found that ‘safety for the baby’, ‘chance of a straightforward birth’ and ‘can the woman’s partner stay overnight following birth’ were particularly important in women’s preferences for hypothetical birth setting. If all birth settings were available to women and they were aware of the differences between them, it is likely that more low risk women who currently plan birth in OUs might choose a midwifery unit.</p></div

EQ-5D-5L valuation project for the Spanish population: a descriptive overview and preliminary results

The latest EQ-5D instrument, EQ-5D-5L, needs new country-specific valuation studies to obtain a value set adapted to the characteristics of the updated instrument. Eight countries from Europe, North and South America and Asia have participated on pilot exercises to develop a final protocol which will be commonly used to perform the valuation studies in each country. Spain is the first country where this protocol has been introduced as part of the Valuation Project for the Spanish Population. This discussion paper reports a descriptive overview of EQ-5D-5L valuation results in the Spanish population and its preliminary results.The survey has a two-stage sample plan. The first stage concentrates on the selection of Spanish regions. The 50 Spanish regions were ordered by population size, and the first 20 regions covering 80% of the total Spanish population were selected. In the second stage, a simple random sampling strategy on each of the selected regions was conducted. The sample size on each region was calculated multiplying the total sample size (1,000) by the percentage of the population on the region respect the total population of the select 20 regions. Data will be collected between 21st May and 15th June 2012 using the final agreed protocol by the EuroQol group. Primary data collection will be conducted by a specialist survey company with a second company conducting a strict quality control process to ensure interviews and data collection of highest quality. The final survey has three blocks of questions. The first block includes patient characteristics (age, gender, socioeconomic status and so on), and a respondent valuation of own health using the EQ-5D-5L. The second block contains 10 composite time trade-offs (TTO) questions, for states better than death classic TTO is used and the “Lead Time” TTO is used for those health states considered worse than death. In this case the lead time (period in full health) is 10 years and the time in the disease is another 10 years to be comparable with the classical TTO were there are 10 years in full health and 10 years in the disease. The last block contains 7 discrete choice experiments questions, where the participant has to choose between two states. Finally some questions about the difficulties of the survey are also included. Descriptive statistics of the final sample are reported. A detailed overview of summary statistics for the health state valuations is included. Different models were explored; hybrid TTO and DC model and DC conditional logistic rescaled with TTO values were used and compared

Neonatal health care costs of very preterm babies in England: a retrospective analysis of a national birth cohort

© 2023 The Authors. Due to be published by BMJ. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://bmjpaedsopen.bmj.com/content/7/1/e001818Objectives: Babies born between 27+0 and 31+6 weeks of gestation represent the largest group of very preterm babies requiring NHS care, however up-to-date cost figures for the UK are not currently available. This study estimates neonatal costs to hospital discharge for this group of very preterm babies in England. Design: Retrospective analysis of resource use data recorded within the National Neonatal Research Database (NNRD). Setting: Neonatal units in England. Patients: Babies born between 27+0 and 31+6 weeks of gestation in England and discharged from a neonatal unit between 2014 and 2018. Main outcome measures: Days receiving different levels of neonatal care were costed, along with other specialised clinical activities. Mean resource use and costs per baby are presented by gestational age at birth, along with total costs for the cohort. Results: Based upon data for 28,154 very preterm babies, the annual total costs of neonatal care were estimated to be £262 million, with 95% of costs attributable to routine daily care provided by units. The mean (SD) total cost per baby of this routine care varied by gestational age at birth; £75,594 (£34,874) at 27 weeks as compared with £27,401 (£14,947) at 31 weeks. Conclusions: Neonatal healthcare costs for very preterm babies vary substantially by gestational age at birth. The findings presented here are a useful resource to stakeholders including NHS managers, clinicians, researchers, and policy makers.This work is supported by the National Institute for Health Research, Health Services and Delivery Research Stream, project number 15/70/104 CRN accrual was approved by the NIHR for the period (1 August 2017 to 31 August 2018)

Lean participative process improvement : outcomes and obstacles in trauma orthopaedics

To examine the effectiveness of a “systems” approach using Lean methodology to improve surgical care, as part of a programme of studies investigating possible synergy between improvement approaches. Setting A controlled before-after study using the orthopaedic trauma theatre of a UK Trust hospital as the active site and an elective orthopaedic theatre in the same Trust as control. Participants All staff involved in surgical procedures in both theatres. Interventions A one-day “lean” training course delivered by an experienced specialist team was followed by support and assistance in developing a 6 month improvement project. Clinical staff selected the subjects for improvement and designed the improvements. Outcome Measures We compared technical and non-technical team performance in theatre using WHO checklist compliance evaluation, “glitch count” and Oxford NOTECHS II in a sample of directly observed operations, and patient outcome (length of stay, complications and readmissions) for all patients. We collected observational data for 3 months and clinical data for 6 months before and after the intervention period. We compared changes in measures using 2-way analysis of variance. Results We studied 576 cases before and 465 after intervention, observing the operation in 38 and 41 cases respectively. We found no significant changes in team performance or patient outcome measures. The intervention theatre staff focused their efforts on improving first patient arrival time, which improved by 20 minutes after intervention. Conclusions This version of “lean” system improvement did not improve measured safety processes or outcomes. The study highlighted an important tension between promoting staff ownership and providing direction, which needs to be managed in “lean” projects. Space and time for staff to conduct improvement activities are important for success

Multiple imputation for patient reported outcome measures in randomised controlled trials : advantages and disadvantages of imputing at the item, subscale or composite score level

Background Missing data can introduce bias in the results of randomised controlled trials (RCTs), but are typically unavoidable in pragmatic clinical research, especially when patient reported outcome measures (PROMs) are used. Traditionally applied to the composite PROMs score of multi-item instruments, some recent research suggests that multiple imputation (MI) at the item level may be preferable under certain scenarios. This paper presents practical guidance on the choice of MI models for handling missing PROMs data based on the characteristics of the trial dataset. The comparative performance of complete cases analysis, which is commonly used in the analysis of RCTs, is also considered. Methods Realistic missing at random data were simulated using follow-up data from an RCT considering three different PROMs (Oxford Knee Score (OKS), EuroQoL 5 Dimensions 3 Levels (EQ-5D-3L), 12-item Short Form Survey (SF-12)). Data were multiply imputed at the item (using ordinal logit and predicted mean matching models), sub-scale and score level; unadjusted mean outcomes, as well as treatment effects from linear regression models were obtained for 1000 simulations. Performance was assessed by root mean square errors (RMSE) and mean absolute errors (MAE). Results Convergence problems were observed for MI at the item level. Performance generally improved with increasing sample sizes and lower percentages of missing data. Imputation at the score and subscale level outperformed imputation at the item level in small sample sizes (n ≤ 200). Imputation at the item level is more accurate for high proportions of item-nonresponse. All methods provided similar results for large sample sizes (≥500) in this particular case study. Conclusions Many factors, including the prevalence of missing data in the study, sample size, the number of items within the PROM and numbers of levels within the individual items, and planned analyses need consideration when choosing an imputation model for missing PROMs data

Economic evaluation plan of a randomised controlled trial of intra-nodular injection of anti-TNF and placebo among patients with early Dupuytren’s disease: Repurposing Anti-TNF for Treating Dupuytren’s Disease (RIDD) [version 1; referees: 2 approved]

Dupuytren’s disease (DD) is a common fibroproliferative condition of the palmar and digital fascia of the hand; however, there is currently no approved treatment for early stage DD. The objective of this paper is to describe the methods applied to assess the cost-effectiveness of adalimumab injections compared to placebo for controlling the progression of early stage DD in the Repurposing Anti-TNF for Treating Dupuytren’s Disease (RIDD) trial. Measure of effectiveness and resource use will be obtained from a randomised clinical trial, carried out in three healthcare centres, and recruiting a minimum of 138 patients aged 18 years and above with a diagnosis of early stage DD. Resource use and utility measures (quality-adjusted life years) will be collected at 3, 6, 9, 12 (primary outcome endpoint) and 18 months post-randomisation. A within-trial cost-utility analysis (CUA) will be conducted at 12 months and if the intervention is effective, a decision analytic model will be applied to estimate the lifetime effectiveness and costs. The analysis will be performed from a health system (National Health Service and personal social services) perspective. Sensitivity analysis will be conducted to assess the robustness of the results. RIDD is the first randomised controlled trial with an economic evaluation conducted among patients with early stage DD. The protocol described here records our intent to conduct both a within-trial CUA alongside the RIDD study and a lifetime CUA using decision-analytic modelling

Handling data quality issues to estimate the Spanish EQ-5D-5L value set using a hybrid interval regression approach

Background The Spanish five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) valuation study was the first to use the EuroQol Valuation Technology protocol, including composite time trade-off (C-TTO) and discrete choice experiments (DCE). In this study, its investigators noticed that some interviewers did not fully explain the C-TTO task to respondents. Evidence from a follow-up study in 2014 confirmed that when interviewers followed the protocol, the distribution of C-TTO responses widened. Objectives To handle the data quality issues in the C-TTO responses by estimating a hybrid interval regression model to produce a Spanish EQ-5D-5L value set. Methods Four different models were tested. Model 0 integrated C-TTO and DCE responses in a hybrid model and models 1 to 3 altered the interpretation of the C-TTO responses: model 1 allowed for censoring of the C-TTO responses, whereas model 2 incorporated interval responses and model 3 included the interviewer-specific protocol violations. For external validation, the predictions of the four models were compared with those of the follow-up study using the Lin’s concordance correlation coefficient. Results This stepwise approach to modeling C-TTO and DCE responses improved the concordance between the valuation and follow-up studies (concordance correlation coefficient: 0.948 [model 0], 0.958 [model 1], 0.952 [model 2], and 0.989 [model 3]). We recommend the estimates from model 3, because its hybrid interval regression model addresses the data quality issues found in the valuation study. Conclusions Protocol violations may occur in any valuation study; handling them in the analysis can improve external validity. The resulting EQ-5D-5L value set (model 3) can be applied to inform Spanish health technology assessments