How to assess an article on economic evaluation.
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Biomedical subjects
Publications and source records attributed to M Sculpher.
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Markov models are often employed to represent stochastic processes, that is, random processes that evolve over time. In a healthcare context, Markov models are particularly suited to modelling chronic disease. In this article, we describe the use of Markov models for economic evaluation of healthcare interventions. The intuitive way in which Markov models can handle both costs and outcomes make them a powerful tool for economic evaluation modelling. The time component of Markov models can offer advantages of standard decision tree models, particularly with respect to discounting. This paper gives a comprehensive description of Markov modelling for economic evaluation, including a discussion of the assumptions on which the type of model is based, most notably the memoryless quality of Markov models often termed the 'Markovian assumption'. A hypothetical example of a drug intervention to slow the progression of a chronic disease is employed to demonstrate the modelling technique and the possible methods of analysing Markov models are explored. Analysts should be aware of the limitations of Markov models, particularly the Markovian assumption, although the adept modeller will often find ways around this problem.
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The economic evaluation of health care technologies has a key role within the new National Health Service health technology assessment process. There has, however, been little discussion of the best way of combining economic and clinical research. Economic evaluation should be iterative, generating progressively firmer estimates of cost-effectiveness and helping to maximise the efficiency of health care R&D. Here, four stages of economic analysis are suggested, starting with stage I when the basic clinical science is complete, and finishing with stage IV analysis to generalise the results of earlier studies to routine clinical practice.
Prospective economic assessments of new pharmaceutical therapies are increasingly being incorporated into phase III clinical trials. We report on the design of an economic evaluation integrated into the Flolan International Randomized Survival Trial (FIRST). Economic evaluation was considered a critical component of the assessment of this therapy given the resources required to administer epoprostenol (Flolan), a therapy that would require lifelong continuous intravenous infusion. Economic secondary endpoints were incorporated in the clinical trial. The economic evaluation of the treatment was integrated into all aspects of study development, including study design, implementation, and monitoring. Since this was a multinational trial, special care was required to ensure that the protocol design was appropriate for all study countries. The economic assessment required the development of several methodologic components: a set of background economic concepts to guide protocol development, a set of resource items to be recorded when required for study participants; a set of data collection instruments for assessment of health-related quality of life for study patients; and a protocol for a resource costing exercise for the study. We report the data elements included in the study design, as well as a discussion of some of the issues faced in developing the economic evaluation for this trial.
Despite the perception of many people that lasers represent the cutting edge of high-technology medicine, this form of medical technology has been subject to relatively little rigorous evaluation. This dearth of research relates particularly to economic evaluation, where there have been few attempts to justify the high cost of laser equipment. This paper details an economic evaluation of the use of laser technology as a secondary adjunct to angioplasty to treat peripheral arterial occlusions. Using data from a range of sources, including a published randomized trial, a cost-utility model is developed to estimate the costs and benefits of the laser, relative to standard angioplasty. The best available data indicate a cost-effective role for the laser, but important areas of uncertainty exist, including the laser's secondary recanalization rate, which has been estimated on the basis of limited numbers of patients. This uncertainty suggests that further research is required before widespread diffusion of the laser for use in this clinical context.
We present the prospective economic evaluation that served as a secondary endpoint for the FIRST study, a randomized international multicenter trial of patients with severe congestive heart failure. Although the clinical results of this study were disappointing, we demonstrated the feasibility of incorporating prospective economic evaluation in phase III clinical trials.
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Given the increased use of economic evaluation to inform decision making in the health service, it is particularly important that the research methods used are critically assessed and, where possible, improved. The systematic handling of uncertainty in economic evaluation is an important area that remains methodologically underdeveloped. With the increased use of the clinical trial as a vehicle for economic evaluation, there has been recent interest in how the statistical methods routinely employed to handle uncertainty in clinical research might be applied to economic evaluation. This paper reviews the types of uncertainty that exist in economic evaluation and argues that some forms of uncertainty are not amenable to statistical methods. Sensitivity analysis is not a single approach but can take a number of different forms. The different types of sensitivity analysis are reviewed, with an indication of their strengths and weaknesses in relation to the different types of uncertainty in economic evaluation.
A structured methodological review of journal articles published in 1992 was undertaken to determine whether recently published economic evaluation studies deal systematically and comprehensively with uncertainty. Ninety three journal articles were identified from a range of searches including a computerised search of the MEDLINE CD-Rom database. Articles were reviewed to determine how they had handled uncertainty in: a) data sources; b) generalisability; c) extrapolation; and d) analytic method. Articles were subsequently assessed to determine how they had represented this uncertainty in terms of the overall results of their analysis. Finally, studies were rated on the basis of their overall performance with respect to dealing systematically and comprehensively with uncertainty. Despite the numerous books and articles devoted to the appropriate methods to be employed by analysts conducting economic evaluation, 22 (24%) studies failed to consider uncertainty at all and 35 (38%) studies employed sensitivity analysis in a manner judged as inadequate. In all, 36 (39%) studies were judged to have given at least an adequate account of uncertainty with 13 (14%) of those judged to have provided a good account of uncertainty. Such disappointing results may reflect a general lack of detail in much of the methods literature concerning how sensitivity analysis should be applied and how results should be presented. Journal editors and readers of economic evaluation articles should acquaint themselves with the methods for handling uncertainty in order that they can critically evaluate the extent to which authors have allowed for uncertainties inherent in their analysis.