A guide to cost-effectiveness acceptability curves

Use of cost-effectiveness acceptability curves, as a method for summarising information on uncertainty in cost-effectiveness, has become widespread within applied studies. This includes several studies in the mental health field. This editorial uses examples from recent papers to illustrate how cost-effectiveness acceptability curves are constructed, what they represent and how they should be interpreted

The value of implementation and the value of information: combined and uneven development

In a budget constrained healthcare system the decision to invest in strategies to improve the implementation of cost-effective technologies must be made alongside decisions regarding investment in the technologies themselves and investment in further research. This paper presents a single, unified framework that simultaneously addresses the problem of allocating funds between these separate but linked activities. The framework presents a simple 4 state world where both information and implementation can be either at the current level or ‘perfect’. Through this framework it is possible to determine the maximum return to further research and an upper bound on the value of adopting implementation strategies. The framework is illustrated through case studies of health care technologies selected from those previously considered by the UK National Institute for Health and Clinical Excellence (NICE). Through the case studies, several key factors that influence the expected values of perfect information and perfect implementation are identified. These factors include the maximum acceptable cost-effectiveness ratio, the level of uncertainty surrounding the adoption decision, the expected net benefits associated with the technologies, the current level of implementation and the size of the eligible population. Previous methods for valuing implementation strategies have confused the value of research and the value of implementation. This framework demonstrates that the value of information and the value of implementation can be examined separately but simultaneously in a single framework. This can usefully inform policy decisions about investment in healthcare services, further research and adopting implementation strategies which are likely to differ between technologies.Value of information analysis; value of implementation; healthcare decisionmaking, Bayesian analysis

The value of implementation and the value of information: combined and uneven development

<i>Aim</i>: In a budget-constrained health care system, the decision to invest in strategies to improve the implementation of cost-effective technologies must be made alongside decisions regarding investment in the technologies themselves and investment in further research. This article presents a single, unified framework that simultaneously addresses the problem of allocating funds between these separate but linked activities. <i>Methods</i>: The framework presents a simple 4-state world where both information and implementation can be either at the current level or "perfect". Through this framework, it is possible to determine the maximum return to further research and an upper bound on the value of adopting implementation strategies. The framework is illustrated through case studies of health care technologies selected from those previously considered by the UK National Institute for Health and Clinical Excellence (NICE). <i>Results</i>: Through the case studies, several key factors that influence the expected values of perfect information and perfect implementation are identified. These factors include the maximum acceptable cost-effectiveness ratio, the level of uncertainty surrounding the adoption decision, the expected net benefits associated with the technologies, the current level of implementation, and the size of the eligible population. <i>Conclusions</i>: Previous methods for valuing implementation strategies have not distinguished the value of efficacy research and the value of strategies to change the level of implementation. This framework demonstrates that the value of information and the value of implementation can be examined separately but simultaneously in a single framework. This can usefully inform policy decisions about investment in health care services, further research, and adopting implementation strategies that are likely to differ between technologies

Is primary angioplasty cost effective in the UK? Results of a comprehensive decision analysis

Objective: To assess the cost effectiveness of primary angioplasty, compared with medical management with thrombolytic drugs, to achieve reperfusion after acute myocardial infarction ( AMI) from the perspective of the UK NHS. Design: Bayesian evidence synthesis and decision analytic model. Methods: A systematic review was conducted and Bayesian statistical methods used to synthesise evidence from 22 randomised control trials. Resource utilisation was based on UK registry data, published literature and national databases, with unit costs taken from routine NHS sources and published literature. Main outcome measure: Costs from a health service perspective and outcomes measured as quality-adjusted life years (QALYs). Results: For the base case, the incremental cost-effectiveness ratio of primary angioplasty was pound 9241 for each additional QALY, with a probability of being cost effective of 0.90 for a cost-effectiveness threshold of pound 20 000. Results were sensitive to variations in the additional time required to initiate treatment with primary angioplasty. Conclusions: Primary angioplasty is cost effective for the treatment of AMI on the basis of threshold cost-effectiveness values used in the NHS and subject to a delay of up to about 80 minutes. These findings are mainly explained by the superior mortality benefit and the prevention of non-fatal outcomes associated with primary angioplasty for delays of up to this length

Assessing the effectiveness of primary angioplasty compared with thrombolysis and its relationship to time delay: a Bayesian evidence synthesis

Background: Meta-analyses of trials have shown greater benefits from angioplasty than thrombolysis after an acute myocardial infarction, but the time delay in initiating angioplasty needs to be considered. Objective: To extend earlier meta-analyses by considering 1- and 6-month outcome data for both forms of reperfusion. To use Bayesian statistical methods to quantify the uncertainty associated with the estimated relationships. Methods: A systematic review and meta-analysis published in 2003 was updated. Data on key clinical outcomes and the difference between time-to-balloon and time-to-needle were independently extracted by two researchers. Bayesian statistical methods were used to synthesise evidence despite differences between reported follow-up times and outcomes. Outcomes are presented as absolute probabilities of specific events and odds ratios (ORs; with 95% credible intervals (Crl)) as a function of the additional time delay associated with angioplasty. \ Results: 22 studies were included in the meta-analysis, with 3760 and 3758 patients randomised to primary angioplasty and thrombolysis, respectively. The mean ( SE) angioplasty-related time delay ( over and above time to thrombolysis) was 54.3 (2.2) minutes. For this delay, mean event probabilities were lower for primary angioplasty for all outcomes. Mortality within 1 month was 4.5% after angioplasty and 6.4% after thrombolysis ( OR = 0.68 ( 95% Crl 0.46 to 1.01)). For non-fatal reinfarction, OR = 0.32 ( 95% Crl 0.20 to 0.51); for non-fatal stroke OR = 0.24 ( 95% Crl 0.11 to 0.50). For all outcomes, the benefit of angioplasty decreased with longer delay from initiation. Conclusions: The benefit of primary angioplasty, over thrombolysis, depends on the former's additional time delay. For delays of 30-90 minutes, angioplasty is superior for 1- month fatal and non-fatal outcomes. For delays of around 90 minutes thrombolysis may be the preferred option as assessed by 6-month mortality; there is considerable uncertainty for longer time delays

Assessing the value of orphan drugs using conventional cost-effectiveness analysis:Is it fit for purpose?

Conventional cost-effectiveness analysis-i.e., assessing pharmaceuticals through a cost per quality-adjusted life year (QALY) framework-originated from a societal commitment to maximize population health given limited resources. This "extra-welfarist" approach has produced pricing and reimbursement systems that are not well- aligned with the unique considerations of orphan drugs. This framework has been slow to evolve along with our increased understanding of the impact of rare diseases, which in turn has complicated the assessment of orphan drugs meant to treat rare diseases. Herein, we (i) discuss the limitations of conventional cost-effectiveness analysis as applied to assessing access to, as well as the pricing and reimbursement of, orphan drugs, (ii) critically appraise alternative and supplemental approaches, and (iii) offer insights on plausible steps forward

Impact of metabolic comorbidity on the association between body mass index and heatlh-related quality of life: a Scotland-wide cross-sectional study of 5,608 participants

<p/>Background: The prevalence of obesity is rising in Scotland and globally. Overall, obesity is associated with increased morbidity, mortality and reduced health-related quality of life. Studies suggest that "healthy obesity" (obesity without metabolic comorbidity) may not be associated with morbidity or mortality. Its impact on health-related quality of life is unknown. <p/>Methods: We extracted data from the Scottish Health Survey on self-reported health-related quality of life, body mass index (BMI), demographic information and comorbidity. SF-12 responses were converted into an overall health utility score. Linear regression analyses were used to explore the association between BMI and health utility, stratified by the presence or absence of metabolic comorbidity (diabetes, hypertension, hypercholesterolemia or cardiovascular disease), and adjusted for potential confounders (age, sex and deprivation quintile). <p/>Results: Of the 5,608 individuals, 3,744 (66.8%) were either overweight or obese and 921 (16.4%) had metabolic comorbidity. There was an inverted U-shaped relationship whereby health utility was highest among overweight individuals and fell with increasing BMI. There was a significant interaction with metabolic comorbidity (p = 0.007). Individuals with metabolic comorbidty had lower utility scores and a steeper decline in utility with increasing BMI (morbidly obese, adjusted coefficient: -0.064, 95% CI -0.115, -0.012, p = 0.015 for metabolic comorbidity versus -0.042, 95% CI -0.067, -0.018, p = 0.001 for no metabolic comorbidity). <p/>Conclusions: The adverse impact of obesity on health-related quality of life is greater among individuals with metabolic comorbidity. However, increased BMI is associated with reduced health-related quality of life even in the absence of metabolic comorbidity, casting doubt on the notion of "healthy obesity"

Economic analysis of the health impacts of housing improvement studies: a systematic review

Background: Economic evaluation of public policies has been advocated but rarely performed. Studies from a systematic review of the health impacts of housing improvement included data on costs and some economic analysis. Examination of these data provides an opportunity to explore the difficulties and the potential for economic evaluation of housing. Methods: Data were extracted from all studies included in the systematic review of housing improvement which had reported costs and economic analysis (n=29/45). The reported data were assessed for their suitability to economic evaluation. Where an economic analysis was reported the analysis was described according to pre-set definitions of various types of economic analysis used in the field of health economics. Results: 25 studies reported cost data on the intervention and/or benefits to the recipients. Of these, 11 studies reported data which was considered amenable to economic evaluation. A further four studies reported conducting an economic evaluation. Three of these studies presented a hybrid ‘balance sheet’ approach and indicated a net economic benefit associated with the intervention. One cost-effectiveness evaluation was identified but the data were unclearly reported; the cost-effectiveness plane suggested that the intervention was more costly and less effective than the status quo. Conclusions: Future studies planning an economic evaluation need to (i) make best use of available data and (ii) ensure that all relevant data are collected. To facilitate this, economic evaluations should be planned alongside the intervention with input from health economists from the outset of the study. When undertaken appropriately, economic evaluation provides the potential to make significant contributions to housing policy

Cost-effectiveness of HBV and HCV screening strategies:a systematic review of existing modelling techniques

Introduction: Studies evaluating the cost-effectiveness of screening for Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) are generally heterogeneous in terms of risk groups, settings, screening intervention, outcomes and the economic modelling framework. It is therefore difficult to compare cost-effectiveness results between studies. This systematic review aims to summarise and critically assess existing economic models for HBV and HCV in order to identify the main methodological differences in modelling approaches. Methods: A structured search strategy was developed and a systematic review carried out. A critical assessment of the decision-analytic models was carried out according to the guidelines and framework developed for assessment of decision-analytic models in Health Technology Assessment of health care interventions. Results: The overall approach to analysing the cost-effectiveness of screening strategies was found to be broadly consistent for HBV and HCV. However, modelling parameters and related structure differed between models, producing different results. More recent publications performed better against a performance matrix, evaluating model components and methodology. Conclusion: When assessing screening strategies for HBV and HCV infection, the focus should be on more recent studies, which applied the latest treatment regimes, test methods and had better and more complete data on which to base their models. In addition to parameter selection and associated assumptions, careful consideration of dynamic versus static modelling is recommended. Future research may want to focus on these methodological issues. In addition, the ability to evaluate screening strategies for multiple infectious diseases, (HCV and HIV at the same time) might prove important for decision makers

'Pedometers cost buttons': the feasibility of implementing a pedometer based walking programme within the community

Background: Recent studies have suggested that walking interventions may be effective (at least in the short term) at increasing physical activity amongst those people who are the most inactive. This is a leading objective of contemporary public health policy in the UK and worldwide. However, before committing money from limited budgets to implement walking interventions more widely in the community, policymakers will want to know whether similar impacts can be expected and whether any changes will be required to the process to ensure uptake and success. This paper utilises the findings from a recent community-based pedometer study (Walking for Wellbeing in the West - WWW) undertaken in Glasgow, Scotland to address issues of feasibility. Methods: An economic analysis of the WWW study assessed the costs of the interventions (minimal and maximal) and combined these with the effects to present incremental cost-effectiveness ratios (cost/person achieving the target of an additional 15,000 steps/week). A qualitative evaluation, involving focus group discussions with WWW participants and short interviews with members of the WWW research team, explored perceived benefits and barriers associated with walking, as well as the successful aspects and challenges associated with the interventions. Results: The incremental cost effectiveness associated with the interventions was estimated as (sic)92 and (sic)591 per person achieving the target for the minimal and maximal interventions respectively. The qualitative evaluation gave insight into the process by which the results were achieved, and identified several barriers and facilitators that would need to be addressed before implementing the interventions in the wider community, in order to ensure their effective transfer. These included assessing the impact of the relationship between researchers and participants on the results, and the motivational importance of monitoring and assessing performance. Conclusions: The results suggest that pedometer based walking interventions may be considered cost-effective and suitable for implementation within the wider community. However, several research gaps remain, including the importance and impact of the researcher/participant relationship, the impact of assessment on motivation and effectiveness, and the longer term impact on physical and mental health, resource utilisation and quality of life