Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-25T07:04:13.571Z Has data issue: false hasContentIssue false
  • English
  • Français

Key principles for the improved conduct of health technology assessments for resource allocation decisions

Published online by Cambridge University Press:  04 July 2008

Michael F. Drummond ,
J. Sanford Schwartz ,
Bengt Jönsson ,
Bryan R. Luce ,
Peter J. Neumann ,
Uwe Siebert  and
Sean D. Sullivan
Michael F. Drummond
Affiliation:
University of York
J. Sanford Schwartz
Affiliation:
University of Pennsylvania
Bengt Jönsson
Affiliation:
Stockholm School of Economics
Bryan R. Luce
Affiliation:
United BioSource Corporation
Peter J. Neumann
Affiliation:
Tufts University
Uwe Siebert
Affiliation:
UMIT—University for Health Sciences, Medical Informatics and Technology
Sean D. Sullivan
Affiliation:
University of Washington
Get access Rights & Permissions [Opens in a new window]

Abstract

Health technology assessment (HTA) is a dynamic, rapidly evolving process, embracing different types of assessments that inform real-world decisions about the value (i.e., benefits, risks, and costs) of new and existing technologies. Historically, most HTA agencies have focused on producing high quality assessment reports that can be used by a range of decision makers. However, increasingly organizations are undertaking or commissioning HTAs to inform a particular resource allocation decision, such as listing a drug on a national or local formulary, defining the range of coverage under insurance plans, or issuing mandatory guidance on the use of health technologies in a particular healthcare system. A set of fifteen principles that can be used in assessing existing or establishing new HTA activities is proposed, providing examples from existing HTA programs. The principal focus is on those HTA activities that are linked to, or include, a particular resource allocation decision. In these HTAs, the consideration of both costs and benefits, in an economic evaluation, is critical. It is also important to consider the link between the HTA and the decision that will follow. The principles are organized into four sections: (i) “Structure” of HTA programs; (ii) “Methods” of HTA; (iii) “Processes for Conduct” of HTA; and (iv) “Use of HTAs in Decision Making.”

Keywords

Cost-effectiveness analysisHealth policy
Type
GENERAL ESSAYS
Information
International Journal of Technology Assessment in Health Care , Volume 24 , Issue 3 , July 2008 , pp. 244 - 258
Copyright
Copyright © Cambridge University Press 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Audit Commission. Managing the financial implications of NICE guidance. London: Audit Commission; 2005.Google Scholar
2. Birch, S, Gafni, A. Information created to evade reality (ICER): Things we should not look to for answers. Pharmacoeconomics. 2006;24:1121–1131.CrossRefGoogle Scholar
3. Brennan, A, Chick, SE, Davies, R. A taxonomy of model structures for economic evaluation of health technologies. Health Econ. 2006;15:1295–1310.CrossRefGoogle ScholarPubMed
4. Busse, FR, Orvain, J, Velasco, M, et al. Best practice in undertaking and reporting health technology assessments. Int J Technol Assess Health Care. 2002;18:361–422.CrossRefGoogle Scholar
5. Devlin, N, Parkin, D. Does NICE have a cost-effectiveness threshold and what other factors influence its decisions? A binary choice analysis. Health Econ. 2004;13:437–452.CrossRefGoogle ScholarPubMed
6. Drummond, MF, Sculpher, MJ, Torrance, GW, O'Brien, BJ, Stoddart, GL. Methods for the economic evaluation of health care programmes. 3rd ed. Oxford: Oxford University Press; 2005.CrossRefGoogle Scholar
7. Drummond, MF, Weatherly, H. Implementing the findings of health technology assessments. If the CAT got out of the bag, can the TAIL wag the dog? Int J Technol Assess Health Care. 2000;16:1–12.CrossRefGoogle ScholarPubMed
8. Eddy, DM. Investigational treatments: How strict should we be? JAMA. 1997;278:179–185.CrossRefGoogle Scholar
9. Eddy, DM. Evidence-based medicine: A unified approach. Health Aff (Millwood). 2005;24:9–17.CrossRefGoogle ScholarPubMed
10. Emanuel, EJ, Fuchs, VR, Garber, AM. Essential elements of a technology and outcomes assessment initiative. JAMA. 2007;298:1323–1325.CrossRefGoogle ScholarPubMed
11. EUnetHTA. Core HTA. Work package 4. http//www.eunethta.net. Accessed 16 March 2008.Google Scholar
12. European Federation of Pharmaceutical Industries and Associations. The use of health technology assessments (HTA) to evaluate medicines: EFPIA key principles. EFPIA Position Paper. http//www.efpia.org/Objects/2/Files/HTAprinciples-EPIApositionpaperfinal.pdf. 2005.Google Scholar
13. Garber, AM. Evidence-based coverage policy. Health Aff (Millwood). 2001;20:62–82.CrossRefGoogle ScholarPubMed
14. Garrison, LP, Neumann, P, Erickson, P, Marshall, D, Mullins, CD. Using real world data for coverage and payment decisions: The ISPOR real world task force report. Value Health. 2007;10:326–335.CrossRefGoogle ScholarPubMed
15. George, B, Harris, A, Mitchell, A. Cost-effectiveness analysis and the consistency of decision making: Evidence from pharmaceutical reimbursement in Australia (1991 to 1996). Pharmacoeconomics. 2001;19:1103–1109.CrossRefGoogle ScholarPubMed
16. Glasziou, PP. Support for trials of promising medications through the pharmaceutical benefits scheme: A proposal for a new authority category. Med J Aust. 1995;162:33–36.CrossRefGoogle ScholarPubMed
17. Goeree, R, Levin, L. Building bridges between academic research and policy formulation: The PRUFE framework-an integral part of Ontario's evidence-based HTPA process. Pharmacoeconomics. 2006;24:1143–1156.CrossRefGoogle ScholarPubMed
18. Gold, M, Siegel, J, Russell, LB, Weinstein, M. Cost-effectiveness in health and medicine. New York: Oxford University Press; 1996.CrossRefGoogle ScholarPubMed
19. Griffin, S, Claxton, K, Hawkins, N, Sculpher, MJ. Probabilistic analysis and computationally expensive models: Necessary and required? Value Health. 2006;9:244–252.CrossRefGoogle ScholarPubMed
20. IQWiG. [General methods]. Draft of version 3.0 of 15 November [German version]. Cologne: IQWiG; 2007: 1–137.Google Scholar
21. IQWiG. Methods for the assessment of the relation of benefits to costs in the German statutory health care system. Version 1.0. January 24, 2008. Cologne: IQWiG. http//www.iqwig.de. Accessed 31 March 2008.Google Scholar
22. Institute of Medicine of the National Academies. Roundtable on evidence-based medicine. http://www.iom.edu/CMS/28312/RT-EBM/41137/43388.aspx. Accessed 19 March 2007.Google Scholar
23. International Network of Agencies for Health Technology Assessment (INAHTA). http://www.inahta.org/HTA./ Accessed 31 March 2008.Google Scholar
24. Mason, A, Drummond, MF, Towse, A. Economic post-launch studies: Matching the desirable with the feasible. London: Office of Health Economics; 2006.Google Scholar
25. Mauskopf, J, Drummond, MF. Publication of pharmacoeconomic data submitted to reimbursement or clinical guidelines agencies (Editorial). Value Health. 2004;7:515–516.CrossRefGoogle Scholar
26. Medicare Payment Advisory Commission (MedPAC). Report to the Congress: Promoting greater efficiency in Medicare. June 2007. http://www.medpac.gov/documents/jun07_entirereport.pdf. Accessed 30 July 2007.Google Scholar
27. National Institute for Health and Clinical Excellence. Guide to the Technology Appraisal process. London: NICE; 2004.Google Scholar
28. National Institute for Health and Clinical Excellence. Evidence to the Health Select Committee Investigation of NICE. London: NICE; 2007.Google Scholar
29. Neumann, PJ, Sullivan, SD. Economic evaluation in the US: What is the missing link? Pharmacoeconomics. 2006;24:1163–8.CrossRefGoogle ScholarPubMed
30. Noorani, HZ, Husereau, D, Boudreau, R, Skidmore, B. Priority setting for health technology assessments: a systematic review of current practical approaches. Int J Technol Assess Health Care. 2007;23:310–315.CrossRefGoogle ScholarPubMed
31. Orszag, PR. Research on the comparative effectiveness of medical treatments: Options for an expanded Federal role. CBO Testimony, Subcommittee on Health, Committee on Ways and Means, US House of Representatives. Washington DC: Congressional Budget Office; 2007.Google Scholar
32. Rawlins, MD, Culyer, AJ. National Institute of Clinical Excellence and its value judgments. BMJ. 2004;329:224–227.CrossRefGoogle ScholarPubMed
33. Reiser, SJ. Criteria for standard versus experimental therapy. Health Aff (Millwood). 1994;113:127–136.CrossRefGoogle Scholar
34. Sackett, DL, Rosenberg, WM, Gray, JA, Haynes, RB, Richardson, WS. Evidence based medicine: What it is and what it isn't. BMJ. 1996;312:71–72.CrossRefGoogle ScholarPubMed
35. Sculpher, MJ, Drummond, MF. Analysis sans frontiers: Can we ever make economic evaluations generalisable across jurisdictions? Pharmacoeconomics. 2006;24:1087–1099.CrossRefGoogle Scholar
36. Sheldon, TA, Cullum, N, Dawson, D, et al. What's the evidence that NICE guidance has been implemented? Results from a national evaluation using time series analysis, audit of patients’ notes and interviews. BMJ. 2004;329:999.CrossRefGoogle ScholarPubMed
37. Siebert, U. When should decision-analytic modeling be used in economic evaluation of health care? Eur J Health Econ. 2003;4:143–150.CrossRefGoogle Scholar
38. Steinberg, EP, Tunis, S, Shapiro, D. Insurance coverage for experimental technologies. Health Aff (Millwood). 1995;14:143–158.CrossRefGoogle ScholarPubMed
39. Tarn, T, Smith, MD. Pharmacoeconomic guidelines around the world. ISPOR Connections. http://www.ispor.org/news/index_new.asp. Accessed 10 October 2006.Google Scholar
40. Tunis, SR. Reflections on science, judgment, and value in evidence-based decision making: A conversation with David Eddy. Health Aff (Millwood). 2007;26:w500–w515.CrossRefGoogle Scholar
41. Tunis, SR, Pearson, SD. Coverage options for promising technologies: Medicare's ‘Coverage with evidence development’. Health Aff (Millwood). 2006;25:1218–1230.CrossRefGoogle ScholarPubMed
42. Tunis, SR, Stryer, DB, Clancy, CM. Practical clinical trials: Increasing the value of clinical research for decision making in clinical and health policy. JAMA. 2003;290:1624–1632.CrossRefGoogle ScholarPubMed
43. Wilensky, GR. Developing a center for comparative effectiveness information. Health Aff (Millwood). 2006;25:w572–w585.CrossRefGoogle ScholarPubMed