Published online before print December 18, 2003, doi: 10.1161/01.STR.0000108267.46809.C4
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(Stroke. 2004;35:203.)
© 2004 American Heart Association, Inc.
Original Contributions |
Editorial Comment—Stroke Cost-Effectiveness Research: Are Acceptability Curves Acceptable?
Departments of Neurology and Community & Preventive Medicine, University of Rochester Medical Center, Rochester, New York
In this issue of Stroke, Patel et al examine the cost-effectiveness of 3 different care strategies for patients with moderately disabling stoke: stroke unit care, stroke team care, and domiciliary care.1 The results show that stroke unit care was more effective and more costly than the other 2 competing strategies, and based on the incremental comparison of stroke unit care compared with domiciliary care (stroke team care was dominated because it was less effective and more costly than stroke unit care), stroke unit care costs an additional £64 000 to £136 000 per quality-adjusted life year (QALY) gained. The authors rightly point out several limitations that need to be kept in mind, the most important of which is limited generalizability given the known differences in stroke care patterns across countries. Another important limitation not mentioned is that different methods of eliciting health state preferences yield different estimates of QALYs for equivalent health states, and such differences need to be kept in mind, considering the authors used only the EuroQol (EQ-5D) as a preference measure and imputed the baseline values.2 This article, however, is important for several reasons.
First, it demonstrates that cost and cost-effectiveness information can be collected, analyzed, and interpreted in the context of stroke treatment trials. To date, the majority of cost-effectiveness analyses for stroke-related interventions have been performed using decision-analytic modeling or have been methodologically limited economic evaluations piggy-backed onto cohort studies or clinical trials.3,4 Obtaining cost and effect data from the same population, as in this clinical-economic trial, has several advantages compared with obtaining cost and effects data from different sources as is often done in decision-analytic modeling, and one of the biggest advantages is that it allows one to understand the correlation between the costs and effects, including a measure of uncertainty in the cost-effectiveness estimates.
Second, it provides detailed descriptive information on the lengthy list of potential cost categories that should be considered in deriving a total cost estimate, and emphasizes the importance of initial hospital costs and informal care costs (ie, direct nonmedical costs) during the first year after a stroke. In fact, the initial hospital costs account for more than 50% of the first-year total direct medical costs, and the informal care costs ranged from approximately 30% to 151% of the total direct medical costs, depending on the methods used to estimate informal care inputs.
Third, it introduces a method of analysis that allows one to place cost-effectiveness results in a more meaningful perspective by plotting acceptability curves for multiple policy alternatives.5 The curves simultaneously compare the 3 treatment strategies and plot the probability that each strategy is the cost-effective alternative relative to all others. Rather than comparing each alternative to a single, perhaps arbitrarily chosen, policy, or prematurely eliminating a policy based on dominance or extended dominance, each policy is evaluated relative to all alternative policies simultaneously, and the level of uncertainty in each is appropriately addressed.
Fourth, because the curves plot the probability of cost-effectiveness for different valuations of a QALY, ranging from £0 to £100 000 for an additional QALY gained (analogous to a 1-tailed test probability value), decision makers can determine the probability that an intervention is cost-effective or welfare-enhancing based on their own specified threshold of cost-effectiveness (or ceiling ratio). Societal thresholds differ and current threshold values per QALY in the United Kingdom are estimated to be approximately £30 000 per additional QALY, whereas in the United States recent proposals have recommended that the societal threshold for considering a new technology to be cost-effective should be $200 000 per QALY.6,7
It should be kept in mind that domiciliary care is actually a strategy of care where initial care is provided in the home with hospital admission if clinically indicated. Because domiciliary care is the least costly alternative, it is the preferred policy when QALYs are not valued, as indicated by the probability points on the far left of Figure 1 in the article by Patel et al.1 As society’s value of a QALY increases, policies with larger QALY gains (ie, stroke unit) have larger net social welfare improvements and, consequently, increases in the probability of being the preferred policies. At the same time, however, the uncertainty in the net social welfare statistics increases rapidly, resulting in convergence of the probabilities (at 0.33 with 3 alternatives) as the value of a QALY becomes large. In this way, acceptability curves summarize important information about both the uncertainty in the estimates and the relative strength of the point estimates. Therefore, based on the information and the analysis presented, we would conclude that domiciliary care is the most cost-effective alternative, but there is not enough evidence to reject the alternative at any level of a QALY value.
This study moves us in the right direction, but more phase III and IV stroke trials should include an economic component. Stroke trialists should become familiar with study designs and methods to perform and appraise cost-effectiveness research, and collaborative partnerships should be strengthened with health economists, quality-of-life researchers, and health policy researchers. Only then will cost-effectiveness information regarding stroke treatments stand beside clinical information to help guide decisions to improve the quality and efficiency of stroke care.
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- Patel A, Knapp M, Perez I, Evans A, Kalra L. Alternative strategies for stroke care: cost-effectiveness and cost-utility analyses from a prospective randomized controlled trial. Stroke. 2004; 35: 196–204.
[Abstract/Free Full Text] - Kopec JA, Willison KD. A comparative review of four preference-weighted measures of health-related quality of life. J Clin Epidemiol. 2003; 56: 317–325.[CrossRef][Medline] [Order article via Infotrieve]
- Holloway RG, Benesch CG, Rahilly CR, Courtright CE. A systematic review of cost-effectiveness research for stroke evaluation and treatment. Stroke. 1999; 30: 1340–1349.
[Abstract/Free Full Text] - Evers SM, Ament AJ, Blaauw G. Economic evaluation in stroke research: a systematic review. Stroke. 2000; 31: 1046–1053.
[Abstract/Free Full Text] - Fenwick E, Claxton K, Sculpher M. Representing uncertainty: the role of cost-effectiveness acceptability curves. Health Econ. 2001; 10: 779–787.[CrossRef][Medline] [Order article via Infotrieve]
- Raftery J. NICE: faster access to modern treatments? Analysis of guidance on health technologies. BMJ. 2001; 323: 1300–1303.
[Free Full Text] - Ubel PA, Hirth RA, Chernew ME, Fendrick A. What is the price of life and why doesn’t it increase at the rate of inflation? Arch Intern Med. 2003; 163: 1637–1641.
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