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Classification of evidence in decision-analytic models of cost-effectiveness: A content analysis of published reports

Published online by Cambridge University Press:  06 October 2010

Suzy Paisley
Suzy Paisley*
Affiliation:
University of Sheffield
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Abstract

Objectives: The aim of this study was to assess systematically the scope of evidence and purposes for which evidence is used in decision-analytic models of cost-effectiveness and to assess the implications for search methods.

Methods: A content analysis of published reports of models was undertaken. Details of cited sources were extracted and categorized according to three dimensions; type of information provided by the evidence, type of source from which the evidence was drawn and type of modeling activity supported by the evidence. The analysis was used to generate a classification of evidence. Relationships within and between the categories within the classification were sought and the implications for searching considered.

Results: The classification generated fourteen types of information, seven types of sources of evidence and five modeling activities supported by evidence. A broad range of evidence was identified drawn from a diverse range of sources including both research-based and non–research-based sources. The use of evidence was not restricted to the population of model parameters but was used to inform the development of the modeling framework and to justify the analytical and methodological approach.

Conclusions: Decision-analytic models use evidence to support all aspects of model development. The classification of evidence defines in depth the role of evidence in modeling. It can be used to inform the systematic identification of evidence.

Keywords

Cost-benefit analysisModelsEconomicInformation storage and retrieval
Type
THEME SECTION: INFORMATION RETRIEVAL FOR HTA
Information
International Journal of Technology Assessment in Health Care , Volume 26 , Issue 4 , October 2010 , pp. 458 - 462
Copyright
Copyright © Cambridge University Press 2010

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References

REFERENCES

1. Ara, R, Tumur, I, Pandor, A, et al. Ezetimibe for the treatment of hypercholesterolaemia: A systematic review and economic evaluation. Health Technol Assess (Winch Eng). 2008;12:iii-212.Google Scholar
2. Brennan, A, Akehurst, R. Modelling in health economic evaluation – What is its place? What is its value? Pharmacoeconomics. 2000;17:445–459.CrossRefGoogle ScholarPubMed
3. Buxton, MJ, Drummond, MF, VanHout, BA, et al. Modelling in economic evaluation: An unavoidable fact of life. Health Econ. 1997;6:217–227.3.0.CO;2-W>CrossRefGoogle ScholarPubMed
4. Chilcott, J, Tappenden, P, Rawdin, A, et al. Avoiding and identifying errors in health technology assessment models: Qualitative study and methodological review. Health Technol Assess (Winch Eng). 2010;14:III-135.Google Scholar
5. Cooper, NJ, Sutton, AJ, Ades, AE, Paisley, S, Jones, DR. Use of evidence in economic decision models: Practical issues and methodological challenges. Health Econ. 2007;16:1277–1286.CrossRefGoogle ScholarPubMed
6. 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;10:245–250.Google Scholar
7. Coyle, D, Lee, KM. Evidence-based economic evaluation: How the use of different data sources can impact results. In: Donaldson, C, Mugford, M, Vale, L, eds. Evidence-based health economics: From effectiveness to efficiency in systematic review. London: BMJ; 2002:55–66.Google Scholar
8. Eddy, D. Technology assessment: The role of mathematical modelling. In: Committe for Evaluating Medical Technologies in Clinical Use, ed. Assessing medical technologies. Washington, DC: National Academy Press; 1985:144–160.Google Scholar
9. Garrison, LP, Neumann, PJ, Erickson, P, Marshall, D, Mullins, D. Using real-world data for coverage and payment decisions: The ISPOR Real-World Data Task Force report. Value Health. 2007;10:326–335.CrossRefGoogle ScholarPubMed
10. Glanville, J, Paisley, S. Searching for evidence for cost-effectiveness decisions. In: Shemilt, I, Mugford, M, Vale, L, Marsh, K, Donaldson, C, eds. Evidence-based decisions and economics: Health care, social welfare, education and criminal justice. 2nd ed. New York: Wiley-Blackwell; 2010:79–92.Google Scholar
11. Golder, S, Glanville, J, Ginnelly, L. Populating decision-analytic models: The feasibility and efficiency of database searching for individual parameters. Int J Technol Assess Health Care. 2005;21:305–311.CrossRefGoogle ScholarPubMed
12. National Institute for Health and Clinical Excellence (NICE). Guide to the methods of technology appraisal. London: NICE; 2008.Google Scholar
13. Paisley, S. Use of evidence in decision-analytic models (thesis in preparation). [University of Sheffield; 2010].Google Scholar
14. Pandor, A, Eggington, S, Paisley, S, Tappenden, P, Sutcliffe, P. The clinical and cost-effectiveness of oxaliplatin and capecitabine for the adjuvant treatment of colon cancer: Systematic review and economic evaluation. Health Technol Assess (Winch Eng). 2006;10:iii-xiv,1–201.Google ScholarPubMed
15. Weinstein, MC, O'Brien, B, Hornberger, J, et al. Principles of good practice for decision analytic modeling in health-care evaluation: Report of the ISPOR Task Force on Good Research Practices – modeling studies. Value Health. 2003;6:9–17.Google Scholar