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

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

Mark versus Luke? Appropriate Methods for the Evaluation of Public Health Interventions

The purpose of this paper is to demonstrate that a social decision making approach to evaluation can be generalised to interventions such as public health and national policies which have multiple objectives and impact on multiple constraints within and beyond the health sector. We demonstrate that a mathematical programming solution to this problem is possible, but the information requirements make it impractical. Instead we propose a simple compensation test for interventions with multiple and cross-sectoral effects. However, rather than compensation based on individual preferences, it can be based on the net benefits falling on different sectors. The valuation of outcomes is based on the shadow prices of the existing budget constraints, which are implicit in existing public expenditure and its allocation across different sectors. A ‘welfarist’ societal perspective is not sufficient; rather, a multiple perspective evaluation which accounts for costs and effects falling on each sector is required.cost-effectiveness analysis, decision rules, public health

Economic evaluation of minimal access surgery: The case of surgical treatment for menorrhagia

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The purpose of this thesis is to explore the methodological and empirical issues relating to the economic evaluation of minimal access surgery (MAS). Given the likely increase in the utilisation of economic analysis in this area, it is crucial to explore whether the methods of economic evaluation have limitations in the face of the particular characteristics of MAS. The comparison of abdominal hysterectomy (AH) and transcervical endometrial resection (TCRE), for the treatment of menorrhagia, is used as a vehicle to develop methods in relation to MAS. Having reviewed the literature and issues relating to the economic analysis of this group of technologies, the empirical starting point of the thesis is the assessment of the limitations of economic evaluations alongside clinical trials, using a trial comparing AH and TCRE. Three major areas of weakness are identified, and alternative ways of addressing these weaknesses are explored in the remainder of the thesis. The first area of methodological development relates to the measure of benefit used in economic evaluation of MAS. In this clinical context, it is argued that the trade-offs that exist between MAS and conventional surgery, in terms of process characteristics and outcomes, should result in an important role for patients' preferences in the construction of a benefit measure. A cost-utility analysis using the standard quality-adjusted life year (GALY) is undertaken, using trial data augmented with valuation data from a further study. The lack of consistency between individual preferences and standard QALYs suggests a major weakness with this measure of benefit. The strengths and weaknesses of an alternative measure of benefit in cost-utility analysis - the ex ante healthy years equivalent (HYE) - are assessed based on a further valuation study. It is shown that it is feasible to elicit ex ante HYEs from patients and that this measure of benefit exhibits some consistency with other expressions of patients' preferences. However, the HYE is likely to impose a greater measurement burden than the standard QALY. The second area of methodological development in the thesis is the analysis of the generalisability of trial-based economic evaluation, given the limitations that often exist with the external validity of trials. A framework is developed within which trial and observational data can be synthesised. This facilitates the use of sensitivity analysis to explore the robustness of base-case (trial-generated) results to alternative sources of data, which may be more representative of routine practice. The third area of methodological development stems from the importance of patients' preferences in relation to MAS. This element relates to the use of methods to model and to evaluate management strategies which use patients' preferences to determine treatment allocation. It is concluded that preference-based decision making has the potential to be cost effective in relation to TCRE and AH, and MAS applications more generally. The thesis demonstrates the importance of continued development in the detailed methods of economic evaluation.Funding was obtained from the Department of Healt

Defining and characterising structural uncertainty in decision analytic models

An inappropriate structure for a decision analytic model can potentially invalidate estimates of cost-effectiveness and estimates of the value of further research. However, there are often a number of alternative and credible structural assumptions which can be made. Although it is common practice to acknowledge potential limitations in model structure, there is a lack of clarity about methods to characterize the uncertainty surrounding alternative structural assumptions and their contribution to decision uncertainty. A review of decision models commissioned by the NHS Health Technology Programme was undertaken to identify the types of model uncertainties described in the literature. A second review was undertaken to identify approaches to characterise these uncertainties. The assessment of structural uncertainty has received little attention in the health economics literature. A common method to characterise structural uncertainty is to compute results for each alternative model specification, and to present alternative results as scenario analyses. It is then left to decision maker to assess the credibility of the alternative structures in interpreting the range of results. The review of methods to explicitly characterise structural uncertainty identified two methods: 1) model averaging, where alternative models, with different specifications, are built, and their results averaged, using explicit prior distributions often based on expert opinion and 2) Model selection on the basis of prediction performance or goodness of fit. For a number of reasons these methods are neither appropriate nor desirable methods to characterize structural uncertainty in decision analytic models. When faced with a choice between multiple models, another method can be employed which allows structural uncertainty to be explicitly considered and does not ignore potentially relevant model structures. Uncertainty can be directly characterised (or parameterised) in the model itself. This method is analogous to model averaging on individual or sets of model inputs, but also allows the value of information associated with structural uncertainties to be resolved.

Improving the efficiency and relevance of health technology assessent: the role of iterative decision analytic modelling

Decision making in health care involves two sets of related decisions: those concerning appropriate service provision on the basis of existing information; and those concerned with whether to fund additional research to reduce the uncertainty relating to the decision. Information acquisition is not costless, and the allocation of funds to the enhancement of the decision makers’ information set, in a budgetconstrained health service, reduces the ‘pot’ of resources available for health service provision. Hence, a framework is necessary to unify these decisions and ensure that HTA is subject to the same evaluation of efficiency as service provision. A framework is presented which addresses these two sets of decisions through the employment of decision analytic models and Bayesian value of information analysis, early and regularly within the health technology assessment process. The model becomes the vehicle of health technology assessment, managing and directing future research effort on an iterative basis over the lifetime of the technology. This ensures consistency in decision making between service provision, research and development priorities and research methods. Fulfilling the aim of the National Health Service HTA programme, that research is “produced in the most economical way” using “cost effective research protocols”. The proposed framework is applied to the decision concerning the appropriate management of female patients with symptoms of urinary tract infection, which was the subject of a recent NHS HTA call for proposals. A probabilistic model is employed to fully characterise and assess the uncertainty surrounding the decision. The expected value of perfect information (EVPI) is then calculated for the full model, for each individual management strategy and for particular model parameters. Research effort can then be focused on those areas where the cost of uncertainty is high and where additional research is potentially cost-effective. The analysis can be used to identify the most appropriate research protocol and to concentrate research upon particular parameters where more precise estimates would be of most value.assessment

Appropriate Perspectives for Health Care Decisions

NICE uses cost-effectiveness analysis to compare the health benefits expected to be gained by using a technology with the health that is likely to be forgone due to additional costs falling on the health care budget and displacing other activities that improve health. This approach to informing decisions will be appropriate if the social objective is to improve health, the measure of health is adequate and the budget for health care can reasonably be regarded as fixed. If NICE were to recommend a broader =societal perspective‘, wider effects impacting on other areas of the public sector and the wider economy would be formally incorporated into analyses and decisions. The problem for policy is that, in the face of budgets legitimately set by government, it is not clear how or whether a societal perspective can be implemented, particularly if transfers between sectors are not possible. It poses the question of how the trade-offs between health, consumption and other social arguments, as well as the valuation of market and non market activities, ought to be undertaken.Perspective. Cost-effectiveness analysis. Economic evaluation.

A critical structured review of economic evaluations of interventions for the prevention and treatment of osteoporosis

Osteoporosis is a major cause of morbidity, mortality and resource cost amongst the elderly population. Hip fracture is the most serious of the osteoporotic fractures, with approximately 10-20% of patients dying within six months of sustaining a fracture. Furthermore, hip fractures are the most expensive manifestation of osteoporosis, incurring about 87% of the total costs of osteoporotic fractures. This public health and economic burden is likely to increase in developed nations due, in part, to ageing populations. In addition, there is strong evidence that the age-specific incidence of fracture is rising. There are a number of treatments which can be used to prevent fracture including hormone replacement therapy (HRT), bisphosphonates, vitamin D and calcium. These interventions have been used for primary prevention, secondary prevention and the treatment of established osteoporosis. This Discussion Paper details the results of a structured review, the purpose of which was to identify and critically appraise economic evaluations relating to interventions for osteoporosis. The focus of the work is a critical assessment of the methodology of those studies. A total of 16 economic evaluations was identified on the basis of a computerised search of three bibliographic databases. All studies were based on decision analytical models and all took the form of cost-effectiveness analysis. Seven studies were from the US and four from the UK. The majority of studies focused on either primary prevention alone (seven) or both primary and secondary prevention where high-risk women were identified on the basis of bone mineral density screening (seven). Most studies considered the cost-effectiveness of HRT. Most of the published studies conclude that treatment using HRT is relatively cost-effective among symptomatic women or women who have had a prior hysterectomy. In contrast, for asymptomatic women, the results are more equivocal. The most recent cost-effectiveness analysis was undertaken by the National Osteoporosis Foundation (NOF) which makes the explicit assumption that HRT is the treatment of choice. For women unwilling or unable to take HRT, the next recommended treatment was alendronate; should alendronate not be tolerated, calcitonin was recommended. Many of the models included in the review exhibit methodological weaknesses which suggest heir results should be treated with some caution. One of these concerns the dearth of formally elicited health state preference data from patients or members of the public: only two studies in the review derive preferences empirically rather than use the authors’ judgement. A second limitation of many studies is the inappropriate application of costeffectiveness decision rules with the frequent use of average cost-effectiveness ratios. Areas of methodological controversy, such as whether or not to include costs unrelated to osteoporosis in life-years added as a result of treatment, increase uncertainty regarding how to interpret the results of the studies.osteoporosis, HRT

Bridging the gap between methods research and the needs of policy makers: A review of the research priorities of the National Institute for Health and Clinical Excellence

Objectives: The aim of this study was to establish a list of priority topics for methods research to support decision making at the National Institute for Health and Clinical Excellence (NICE). Methods: Potential priorities for methods research topics were identified through a focused literature review, interviews, an email survey, a workshop and a Web-based feedback exercise. Participants were members of the NICE secretariat and its advisory bodies, representatives from academia, industry, and other organizations working closely with NICE. The Web exercise was open to anyone to complete but publicized among the above groups. Results: A list of potential topics was collated. Priorities for further research differed according to the type of respondent and the extent to which they work directly with NICE. Priorities emerging from the group closest to NICE included: methodology for indirect and mixed treatment comparisons; synthesis of qualitative evidence; research relating to the use of quality-adjusted life-years (QALYs) in decision making; methods and empirical research for establishing the cost-effectiveness threshold; and determining how data on the uncertainty of effectiveness and cost-effectiveness data should be taken into account in the decision-making process. Priorities emerging from the broadest group of respondents (through the Web exercise) included: methods for extrapolating beyond evidence observed in trials, methods for capturing benefits not included in the QALY and methods to assess when technologies should be recommended in the context of further evidence gathering. Conclusions: Consideration needs to be given to the needs of those who use the outputs of research for decision making when determining priorities for future methods research.NIHR Medical Research Council