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WHO SHOULD CONDUCT MODELING AND COST-EFFECTIVENESS ANALYSIS?

Published online by Cambridge University Press:  06 February 2014

Måns Rosén*
Affiliation:
Swedish Council on Health Technology Assessment (SBU) Karolinska Institutet, Department of Learning, Informatics, Management and Ethics
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Extract

In some countries, reimbursement of drugs is based on cost-effectiveness analysis (CEA), in others not. In times of ageing populations, increasing number of possible interventions, and limited resources, it seems likely that CEA will be more and more important as a basis for decision making.

Type
Letters to the Editor
Copyright
Copyright © Cambridge University Press 2014 

Dear Dr. Mäkelä,

In some countries, reimbursement of drugs is based on cost-effectiveness analysis (CEA), in others not. In times of ageing populations, increasing number of possible interventions, and limited resources, it seems likely that CEA will be more and more important as a basis for decision making.

SBU has conducted systematic reviews for more than 25 years, and our experience is that it is very difficult to draw any conclusions from the literature on cost-effectiveness due to the variability in organizations, contexts, and costs between countries. According to CHEERS (Reference Husereau, Drummond and Petrou1), economic evaluations have no widespread mechanisms for warehousing data to allow for independent interrogation and thereby creating transparency.

In most countries where CEA plays a role in drug reimbursements, industry delivers the CEA which then are scrutinized by regulatory bodies. These public agencies can ask for complementary information within a short time period. However, models are usually not transparent for others or available for public use. The problem is that CEA studies funded by industry are more likely to report lower ratios than nonsponsored studies (Reference Bell, Urbach and Ray2Reference Garattini, Koleva and Casadei5), that is, they are biased. Approximately 70 percent of all CEA were sponsored, and those studies were much more likely to report favorable conclusions and showed more favorable incremental cost-effectiveness ratios than nonsponsored studies (Reference Bell, Urbach and Ray2;Reference Garattini, Koleva and Casadei5). To minimize this bias, actions have been taken, for example, developing methodological guidelines (Reference Husereau, Drummond and Petrou1), improving the peer review process and clarifying relationships between sponsors and analysts (Reference Drummond6). Still, the problem persists and is well in line with standard economic theory, which postulates that the behavior of private firms is driven by the objective of profit maximization (Reference Morgan, Barer and Evans7).

With the present decision-making process, society will not optimize health within limited resources. An alternative approach is thereby to let public organizations or independent university departments conduct CEA financed by fees from industry. The benefit is more unbiased CEA without increasing costs for involved parties. There would be a parallel to the legislation where industry pays a fee to the European Medicines Agency (EMA) for their services.

To deal with the problem of biased CEA, Barbieri and Drummond suggested increased public funding for economic evaluation of medicines (Reference Barbieri and Drummond8). Garattini et al. took one step further and concluded that the best way of limiting confounding factors is by clearly distinguishing assessors from manufacturers and marketers of any new technologies (Reference Garattini, Koleva and Casadei5). However, no actions have been taken so far and the reasons could be discussed. Hampering factors are that economic modeling is a demanding and time consuming task and that strong stakeholders like industry would oppose. It may even not be in the interest of health economists depending on assignments from industry. For drugs, decisions on reimbursement must usually be made with limited resources and within a limited time period. Most health technology assessment (HTA) organizations or reimbursement bodies, except NICE, lack the economic resources to conduct modeling on their own. Open and transparent economic modeling where each country can put their own data on incidence and costs is a more appealing approach.

Because economic modeling is a demanding task, international collaboration would be needed and cost-effective. How such a system would be organized is a later question. Maybe member states interested could join in a consortium. The models should be transparent with open-access and possibilities to adjust according to local conditions. For example, organization, costs, and incidence vary between countries. Each regulatory body could then incorporate relevant figures for their own country. Initiatives within Europe and the HTA society would be very welcome.

References

REFERENCES

1. Husereau, D, Drummond, M, Petrou, S, et al. Consolidated health economic evaluation reporting standards (CHEERS) statement. Int J Technol Assess in Health Care. 2013;29:117122.Google Scholar
2. Bell, CM, Urbach, DR, Ray, JG, et al. Bias in published cost-effectiveness studies: Systematic review. BMJ. 2006;332:699703.CrossRefGoogle ScholarPubMed
3. Peura, PK, Martikainen, JA, Purmonen, TT, Turunen, JH. Sponsorship-related outcome selection bias in published economic studies of triptans: Systematic review. Med Decis Making. 2012;32:237245.Google Scholar
4. Lexchin, J, Bero, LA, Djulbegovic, B, Clark, O. Pharmaceutical industry sponsorship and research outcome and quality: Systematic review. BMJ. 2003;326:11671170.Google Scholar
5. Garattini, L, Koleva, D, Casadei, G. Modeling in pharmacoeconomic studies: Funding sources and outcomes. Int J Technol Assess in Health Care. 2010;26:330333.Google Scholar
6. Drummond, MF. A reappraisal of economic evaluation of pharmaceuticals. Science or marketing? Pharmacoeconomics. 1988;14:19.CrossRefGoogle Scholar
7. Morgan, S, Barer, M, Evans, R. Health economists meet the fourth tempter: Drug dependency and scientific discourse. Health Econ. 2000;9:659667.3.0.CO;2-0>CrossRefGoogle ScholarPubMed
8. Barbieri, M, Drummond, MF. Conflict of interest in industry-sponsored economic evaluations: Real or imagined? Curr Oncol Rep. 2001;3:410413.Google Scholar