Case finding for hepatitis C in primary care: a cost utility analysis (original) (raw)
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Cost-effectiveness analysis and formulary decision making in England: Findings from research
Social Science & Medicine, 2007
In a context of rapid technological advances in health care and increasing demand for expensive treatments, local formulary committees are key players in the management of scarce resources. However, little is known about the information and processes used when making decisions on the inclusion of new treatments. This paper reports research on the use of economic evaluations in technology coverage decisions in England, although the findings have a relevance to other health care systems with devolved responsibility for resource allocation. It reports a study of four local formulary committees in which both qualitative and quantitative data were collected. Our main research finding is that it is an exception for cost-effectiveness analysis to inform technology coverage decisions. Barriers to use include access and expertise levels, concerns relating to the independence of analyses and problems with implementation of study recommendations. Further barriers derive from the constraints on decision makers, a lack of clarity over functions and aims of local committees, and the challenge of disinvestment in medical technologies. The relative weakness of the research-practice dynamics in this context suggests the need for a rethinking of the role of both analysts and decision makers. Our research supports the view that in order to be useful, analysis needs to better reflect the constraints of the local decision-making environment. We also recommend that local decision-making committees and bodies in the National Health Service more clearly identify the ‘problems’ which they are charged with solving and how their outputs contribute to broader finance and commissioning functions. This would help to establish the ways in which the routine use of cost-effectiveness analysis might become a reality.Summary of findingsLocal formulary decision-making committees vary in their capacity, functions and scope of responsibility. Their primary function appears to be to control spending rather than evidence-based technology coverage.Most committees routinely request information on clinical effect and costs but few request cost-effectiveness information.Case study committees had only limited capacity to access and interpret economic evaluations. Further barriers included concerns regarding bias in studies, the inability to implement savings, and ethical objections to underlying values of health economics.A number of features of the decision-making environment appeared to militate against emphasis on cost-effectiveness analysis including: unclear relationships with resource allocators; an explicitly political decision-making process, and; poorly specified decision-making criteria.These factors, combined with constraints on the capacity to generate, access and interpret information, led to a minor role for cost-effectiveness analysis in the decision-making process.
Whither trial-based economic evaluation for health care decision making?
The randomised controlled trial (RCT) has developed a central role in applied costeffectiveness studies in health care as the vehicle for analysis. That is, data are collected on resource use and health effects on all or a sample of patients in the trial. This proves the basis of a trial-based estimate of cost-effectiveness of the technology of interest relative to one or more comparator(s). Increasingly, economic evaluation is being used as an explicit input into formalised decision-making about new technologies by specific agencies (e.g. NICE in the UK). This paper considers the role of trial-based economic evaluation in this era of explicit decision making. It is argued that any framework for economic analysis can only be judged insofar as it can inform two key decisions and be consistent with the objectives of a health care system subject to its resource constraints. The two decisions are, firstly, whether to adopt a health technology given existing evidence and, secondly, an assessment of whether more evidence is required to support this decision in the future. We argue that a framework of economic analysis is needed which can estimate costs and effects, based on all the available evidence, across the full range of possible alternative interventions and clinical strategies, over a relevant time horizon and for specific patient groups. It must also enable the accumulated evidence to be synthesised in an explicit and transparent way in order to fully represent the decision uncertainty. These requirements suggest that, in most circumstances, the use of a single RCT as a vehicle for economic analysis will be an inadequate and partial basis for decision making. It is argued that RCT evidence, with or without economic content, should be viewed as simply one of the sources of evidence which must be placed in a broader framework of evidence synthesis and decision analysis. Given the reality that a large proportion of evaluative health services research is funded around RCTs, trials will remain an important source of all forms of evidence for economic evaluation, but economic components to trial proposals need to include an explicit evidence synthesis and decision modelling component.
On the Estimation of the Cost-Effectiveness Threshold: Why, What, How?
Value in Health, 2016
Background: Many health care systems claim to incorporate the costeffectiveness criterion in their investment decisions. Information on the system's willingness to pay per effectiveness unit, normally measured as quality-adjusted life-years (QALYs), however, is not available in most countries. This is partly because of the controversy that remains around the use of a cost-effectiveness threshold, about what the threshold ought to represent, and about the appropriate methodology to arrive at a threshold value. Objectives: The aim of this article was to identify and critically appraise the conceptual perspectives and methodologies used to date to estimate the costeffectiveness threshold. Methods: We provided an in-depth discussion of different conceptual views and undertook a systematic review of empirical analyses. Identified studies were categorized into the two main conceptual perspectives that argue that the threshold should reflect 1) the value that society places on a QALY and 2) the opportunity cost of investment to the system given budget constraints. Results: These studies showed different underpinning assumptions, strengths, and limitations, which are highlighted and discussed. Furthermore, this review allowed us to compare the cost-effectiveness threshold estimates derived from different types of studies. We found that thresholds based on society's valuation of a QALY are generally larger than thresholds resulting from estimating the opportunity cost to the health care system. Conclusions: This implies that some interventions with positive social net benefits, as informed by individuals' preferences, might not be an appropriate use of resources under fixed budget constraints.
Searching for cost effectiveness thresholds in the NHS
Health Policy, 2009
Objectives: The UK's National Institute of Health and Clinical Excellence (NICE) has an explicit cost-effectiveness threshold for deciding whether or not services are to be provided in the National Health Service (NHS), but there is currently little evidence to support the level at which it is set. This study examines whether it is possible to obtain such evidence by examining decision making elsewhere in the NHS. Its objectives are to set out a conceptual model linking NICE decision making based on explicit thresholds with the thresholds implicit in local decision making and to gauge the feasibility of (a) identifying those implicit local cost effectiveness thresholds and (b) using these to gauge the appropriateness of NICE's explicit threshold. Methods: Structured interviews with senior staff, together with financial and public health information, from six NHS purchasers and 18 providers. A list of health care services introduced or discontinued in 2006/7 was constructed. Those that were in principle amenable to estimation of a cost-effectiveness ratio were examined. Results: It was feasible to identify decisions and to estimate the cost-effectiveness of some. These were not necessarily 'marginal' services. Issues include: services that are dominated (or dominate); decisions about how, rather than what, services should be delivered; the lack of local cost effectiveness evidence; and considerations other than cost-effectiveness.
Health Economics, 2004
The decisions made by the National Institute for Clinical Excellence (NICE) give rise to two questions: how is costeffectiveness evidence used to make judgements about the 'value for money' of health technologies? And how are factors other than cost-effectiveness taken into account? The aim of this paper is to explore NICE's cost-effectiveness threshold(s) and the tradeoffs between cost effectiveness and other factors apparent in its decisions. Binary choice analysis is used to reveal the preferences of NICE and to consider the consistency of its decisions. For each decision to accept or reject a technology, explanatory variables include: the cost per life year or per QALY gained; uncertainty regarding cost effectiveness; the net cost to the NHS; the burden of disease; the availability (or not) of alternative treatments; and specific factors indicated by NICE. Results support the broad notion of a threshold, where the probability of rejection increases as the cost per QALY increases. Cost effectiveness, together with uncertainty and the burden of disease, explain NICE decisions better than cost effectiveness alone. The results suggest a threshold somewhat higher than NICEs stated 'range of acceptable cost effectiveness' of d20 000-d30 000 per QALY -although the exact meaning of a 'range' in this context remains unclear.
2014
Background The inclusion of cost-effectiveness data, as a basis for priority setting rankings, is a distinguishing feature in the formulation of the Swedish national guidelines. Guidelines are generated with the direct intent to influence health policy and support decisions about the efficient allocation of scarce healthcare resources. Certain medical conditions may be given higher priority rankings i.e. given more resources than others, depending on how serious the medical condition is. This study investigated how a decision-making group, the Priority Setting Group (PSG), used cost-effectiveness data in ranking priority setting decisions in the national guidelines for heart diseases. Methods A qualitative case study methodology was used to explore the use of such data in ranking priority setting healthcare decisions. The study addressed availability of cost-effectiveness data, evidence understanding, interpretation difficulties, and the reliance on evidence. We were also interested in the explicit use of data in ranking decisions, especially in situations where economic arguments impacted the reasoning behind the decisions. Results This study showed that cost-effectiveness data was an important and integrated part of the decision-making process. Involvement of a health economist and reliance on the data facilitated the use of cost-effectiveness data. Economic arguments were used both as a fine-tuning instrument and a counterweight for dichotomization. Cost-effectiveness data were used when the overall evidence base was weak and the decision-makers had trouble making decisions due to lack of clinical evidence and in times of uncertainty. Cost-effectiveness data were also used for decisions on the introduction of new expensive medical technologies. Conclusion Cost-effectiveness data matters in decision-making processes and the results of this study could be applicable to other jurisdictions where health economics is implemented in decision-making. This study contributes to knowledge on how cost-effectiveness data is used in actual decision-making, to ensure that the decisions are offered on equal terms and that patients receive medical care according their needs in order achieve maximum benefit.
2005
After many years searching for customers, economic evaluation is now being used explicitly in health service decision making -principally to inform decisions about whether to fund new pharmaceuticals. To what extent are the methods of economic evaluation in health care adequate for this more prominent role? This paper sets out to address this question by considering the alternative theoretical bases for economic evaluation. It argues that a social decision making perspective provides the most appropriate foundation and, from this, a range of necessary analytical features are required in any study. The paper goes on to describe recent methods developments in the field including statistical methods to analyse patient-level data; techniques to handle uncertainty in cost-effectiveness measures; methods to synthesise available data whilst reflecting their imprecision and heterogeneity; decision analytic techniques to identify cost-effective options under conditions of uncertainty; and value of information methods to help prioritise and design future research. The paper argues, that although the methods of cost-effectiveness have progressed markedly over the last decade, these developments also emphasises how far the field still have to go. Two particular methods challenges are discussed which relate to the methods of constrained maximisation and developments and value of information methods.
EQ-5D-5L versus EQ-5D-3L: The Impact on Cost Effectiveness in the United Kingdom
Value in Health, 2018
To model the relationship between EQ-5D-3L and EQ-5D-5L and examine how differences impact on costeffectiveness in case studies. Methods We used two datasets that included both EQ-5D-3L and EQ-5D-3L from the same respondents. The EuroQoL dataset (n=3551) included patients with different diseases and a healthy cohort. The NDB included patients with rheumatoid disease (n=5205). We estimated a system of ordinal regressions in each dataset using copula models, to link responses to the 3L instrument to 5L and its tariff, and vice versa. Results were applied to nine cost-effectiveness studies. Results Best-fitting models differed between EuroQoL and NDB datasets in terms of the explanatory variables, copulas and coefficients. In both cases the coefficients of the covariates and latent factor between-3L and-5L were significantly different, indicating that the two instruments are not a uniform realignment of the response levels for most dimensions. In the case studies, moving from 3L to 5L caused a decrease of up to 87% in incremental QALYs gained from effective technologies in almost all cases. ICERs increased, often substantially. Technologies with a significant mortality gain saw increases in incremental QALYs. Conclusion 5L shifts mean utility scores up the utility scale towards full health and compresses them into a smaller range, compared to-3L. Improvements in quality of life are valued less using 5L than with 3L. 3L and 5L produce substantially different estimates of cost effectiveness. There is no simple proportional adjustment that can be made to reconcile these differences.
An International Comparison of EQ-5D-5L and EQ-5D-3L for Use in Cost-Effectiveness Analysis
Value in Health, 2021
Methods 8 cost effectiveness analyses based on clinical studies with 3L provided 11 pairwise comparisons. We estimated cost-effectiveness by applying the appropriate country values for 3L to observed responses. We re-estimated cost effectiveness for each country by predicting the 5L tariff score for each respondent, for each country, using a previously published mapping method. We compared results in terms of impact on estimated incremental Quality Adjusted Life Year (QALY) gain and cost-effectiveness ratios. Results For most countries the impact of moving from 3L to 5L is to lower the incremental QALY gain in the majority of comparisons. The only exception to this was Japan, where 4/11 (37%) of cases saw lower QALYs gained when using 5L. The mean and median reductions in health gain, in those case studies where 5L does lead to lower health gain, are largest in the Netherlands (84% mean reduction, 41% median reduction), Germany (68% and 27%) and Spain (30% and 31%). For most countries, those studies where 5L leads to lower health gain see larger reductions than the gains in studies showing the opposite tendency. Conclusion 3L and 5L are not interchangeable in these countries. Differences between results are large but the direction of change can be unpredictable. These findings should prompt further investigation into the reasons for differences. HIGHLIGHTS i. What is already known about the topic? EQ5D-3L and the newer 5L version have been shown to value changes in health very differently in the UK. ii. What does the paper add to existing knowledge? This paper demonstrates how health benefit and cost effectiveness may be affected from using 5L instead of 3L in 6 countries that have value sets for both. iii. What insights does the paper provide for informing health care-related decision making? 3L and 5L cannot be treated as interchangeable. For some countries, there may be good reason to seek to improve current 5L value sets before making a decision to use 5L instead of 3L routinely.
Opportunity costs and uncertainty in the economic evaluation of health care interventions
Health Economics, 2002
Considerable methodological research has been conducted on handling uncertainty in cost-effectiveness analysis. The current literature suggests the concepts of net health benefits and cost-effectiveness acceptability curves to circumvent the technical shortcomings of cost-effectiveness ratio statistics. However, these approaches do not provide a solution for the inherent problem that the threshold cost-effectiveness ratio itself is unknown. The authors suggest analysing uncertainty in cost-effectiveness analysis by directly addressing the concept of opportunity costs using the decision rule described by and introduce a new graphical framework (the 'decision making plane') for communicating with policy makers.