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Systematic reviews and economic evaluations conducted for the National Institute for Health and Clinical Excellence in the United Kingdom: A game of two halves?

Published online by Cambridge University Press:  09 April 2008

Michael F. Drummond
Affiliation:
University of York
Cynthia P. Iglesias
Affiliation:
University of York
Nicola J. Cooper
Affiliation:
University of Leicester

Abstract

Background: Decision analytic models, as used in economic evaluations, require data on several clinical parameters. The gold standard approach is to conduct a systematic review of the relevant clinical literature, although reviews of economic evaluations indicate that this is rarely done. Technology appraisals for the National Institute for Health and Clinical Excellence (NICE), which are fully funded, represent the best case scenario for the close integration of economic evaluations and systematic reviews. The objective of this study was to assess the extent to which the systematic review of the clinical literature informs the economic evaluation in NICE technology appraisals.

Methods: All NICE technology assessment reports (TARs) published between January 2003 and July 2006 were considered. Data were abstracted on the TAR topics, the primary measure of clinical effectiveness, the approach to pooling in the clinical review, the measure of economic benefit and the use, or non-use, of the systematic review in the economic evaluation.

Results: Forty-one TARs were published in the period studied, all of which contained a systematic review. Most of the economic evaluations (85 percent) were cost-utility analyses, reflecting NICE's guidelines for economic evaluation. In seventeen cases, the clinical data were not pooled in the review, owing to heterogeneity in the clinical data or the limited number of studies. In these cases, the economists used alternative approaches for estimating the key effectiveness parameter in the model. The results of the review (when pooled) were always used when the primary clinical effectiveness measure corresponded with the measure of economic benefit (e.g., survival). However, because preference-based quality of life measures are rarely included in clinical trials, the results of the systematic review were never directly used in the cost-utility analyses. Nevertheless, the outputs of the systematic review were used when the data were useful in estimating components of the quality-adjusted life-year (QALY) (e.g., the life-years gained, or the frequencies of health states to which QALYs could be assigned). Problems occurred mainly when the clinical data were not pooled, or when the measure of clinical benefit could not be converted into health states to which QALYs could be assigned.

Conclusions: Economic evaluations can benefit from systematic reviews of the clinical literature. However, such reviews are not a panacea for conducting a good economic evaluation. Much of the relevant data for estimating QALYs are not contained in such reviews and the chosen method for summarizing the clinical data may inhibit the assessment of economic benefit. Problems would be reduced if those undertaking the technology assessments discussed the data requirements for the economic model at an early stage.

Type
GENERAL ESSAYS
Copyright
Copyright © Cambridge University Press 2008

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References

REFERENCES

1. Barbieri, M, Drummond, MF, Puig Junoy, J, Casado Gomez, MA, Blasco Segura, PB, Poveda Andres, JL. A critical appraisal of pharmacoeconomic studies comparing TNF alpha antagonists for the rheumatoid arthritis treatment. Expert Rev Pharmacoecon Outcomes Res. 2007; 7:613626.Google Scholar
2. Brazier, J, Roberts, J, Deverill, M. The estimation of a preference-based measure of health from the SF-36. J Health Econ. 2002; 21:271292.Google Scholar
3. Bryant, J, Loveman, E, Chase, D, et al. Clinical effectiveness and cost-effectiveness of growth hormone in adults in relation to impact on quality of life: A systematic review and economic evaluation. Health Technol Assess. 2002;6:1106.Google ScholarPubMed
4. Cooper, N, Coyle, D, Abrams, K, Mugford, M, Sutton, A. Use of evidence in decision models: An appraisal of health technology assessments in the UK since 1997. J Health Serv Res Policy. 2005;10:245250.CrossRefGoogle ScholarPubMed
5. EuroQol Group. EuroQol – a new facility for the measurement of health-related quality of life. Health Policy. 1990;16:199208.Google Scholar
6. Feeny, D, Furlong, W, Torrance, GW, et al. Multiattribute and single attribute functions for the Health Utilities Index Mark 3 System. Med Care. 2002;40:113128.CrossRefGoogle ScholarPubMed
7. Hanratty, B, Craig, D, Nixon, J, Rice, S, Christie, J, Drummond, MF. Are the best available clinical effectiveness data used in economic evaluations of drug therapies? J Health Serv Res Policy. 2007;12:138141.Google Scholar
8. King, S, Griffin, S, Hodges, Z, et al. A systematic review and economic model of the effectiveness and cost-effectiveness of methylphenidate, clexamfetamine and amoxetine for the treatment of attention deficit hyperactivity disorder in children and adolescents. Health Technol Assess. 2006;10:162.Google Scholar
9. National Institute for Clinical Excellence. Guide to the methods of technology appraisal. London: NICE; 2004.Google Scholar
10. Turner, D, Wailoo, A, Nicholson, K, Cooper, N, Sutton, A, Abrams, K. Systematic review and economic decision modelling for the prevention and treatment of influenza A and B. Health Technol Assess. 2003;7:1182.Google Scholar