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HEALTH TECHNOLOGY ASSESSMENT AND PERSONALIZED MEDICINE: ARE ECONOMIC EVALUATION GUIDELINES SUFFICIENT TO SUPPORT DECISION MAKING?

Part of: Special Collection - Methods

Published online by Cambridge University Press:  07 May 2014

Don Husereau ,
Deborah A. Marshall ,
Adrian R. Levy ,
Stuart Peacock  and
Jeffrey S. Hoch
Don Husereau
Affiliation:
Institute of Health Economics, Department of Epidemiology and Community Medicine. University of Ottawa, University for Health Sciences, Medical Informatics and Technology
Deborah A. Marshall
Affiliation:
Faculty of Medicine, Department of Community Health Sciences, University of Calgary
Adrian R. Levy
Affiliation:
Department of Community Health and Epidemiology, Dalhousie University Faculty of Medicine
Stuart Peacock
Affiliation:
Canadian Centre for Applied Research in Cancer Control, British Columbia Cancer Research Centre, School of Population and Public Health, University of British Columbia
Jeffrey S. Hoch
Affiliation:
Pharmacoeconomics Research Unit, Cancer Care Ontario, Canadian Centre for Applied Research in Cancer Control
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Abstract

Background: Many jurisdictions delivering health care, including Canada, have developed guidance for conducting economic evaluation, often in the service of larger health technology assessment (HTA) and reimbursement processes. Like any health intervention, personalized medical (PM) interventions have costs and consequences that must be considered by reimbursement authorities with limited resources. However, current approaches to economic evaluation to support decision making have been largely developed from population-based approaches to therapy—that is, evaluating the costs and consequences of single interventions across single populations. This raises the issue as to whether these methods, as they are or more refined, are adequate to address more targeted approaches to therapy, or whether a new paradigm for assessing value in PM is required.

Objectives: We describe specific issues relevant to the economic evaluation of diagnostics-based PM and assess whether current guidance for economic evaluation is sufficient to support decision making for PM interventions.

Methods: Issues were identified through literature review and informal interviews with national and international experts (n = 10) in these analyses. This article elaborates on findings and discussion at a workshop held in Ottawa, Canada, in January 2012.

Results: Specific issues related to better guiding economic evaluation of personalized medicine interventions include: how study questions are developed, populations are characterized, comparators are defined, effectiveness is evaluated, outcomes are valued and how resources are measured. Diagnostics-based PM also highlights the need for analyses outside of economic evaluation to support decision making.

Conclusions: The consensus of this group of experts is that the economic evaluation of diagnostics-based PM may not require a new paradigm. However, greater complexity means that existing approaches and tools may require improvement to undertake these more analyses.

Keywords

Costs and cost analysisBiomedical research/methodsBiomedical research/standardsDecision support techniquesDelivery of health careDiagnostic techniques and proceduresHealth policyHumansIndividualized medicine/methodsTechnology assessmentBiomedical
Type
Methods
Information
International Journal of Technology Assessment in Health Care , Volume 30 , Issue 2 , April 2014 , pp. 179 - 187
Copyright
Copyright © Cambridge University Press 2014 

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References

REFERENCES

1. Tarn, T, Smith, MD. Pharmacoeconomic guidelines around the world. ISPOR Connect. 2004;10:5–15.Google Scholar
2. Eldessouki, R, Dix Smith, M. Health care system information sharing: A step toward better health globally. Value Health Regional Issues. 2012;1:118–120.CrossRefGoogle ScholarPubMed
3. Mittmann, N, Evans, WK, Rocchi, A, et al. Guidelines for health technologies: Specific guidance for oncology products in Canada. Value Health. 2012;15:580–585.Google Scholar
4. Drummond, MF, Sculpher, MJ, Torrance, G, O'Brien, B, Stoddart, G. Methods for the Economic Evaluation of Health Care Programmes, 3rd ed. Cambridge: Oxford University Press; 2005.CrossRefGoogle Scholar
5. Faulkner, E, Annemans, L, Garrison, L, et al. Challenges in the development and reimbursement of personalized medicine-payer and manufacturer perspectives and implications for health economics and outcomes research: A report of the ISPOR personalized medicine special interest group. Value Health. 2012;15:1162–1171.CrossRefGoogle ScholarPubMed
6. Stallings, SC, Huse, D, Finkelstein, SN, et al. A framework to evaluate the economic impact of pharmacogenomics. Pharmacogenomics. 2006;7:853–862.Google Scholar
7. Repa, R. The power of innovation. Ontario: Hamilton; 2010.Google Scholar
8. The Lewin Group. Under the microscope: Trends in laboratory medicine [Internet]. Oakland: California Healthcare Foundation; 2009. www.chcf.org (accessed December 25, 2013).Google Scholar
9. Becla, L, Lunshof, JE, Gurwitz, D, et al. Health technology assessment in the era of personalized health care. Int J Technol Assess Health Care. 2011;27:118–126.Google Scholar
10. Bossuyt, PM, Reitsma, JB, Bruns, DE, et al. The STARD statement for reporting studies of diagnostic accuracy: Explanation and elaboration. Clin Chem. 2003;49:7–18.Google Scholar
11. Teutsch, SM, Bradley, LA, Palomaki, GE, et al. The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) initiative: Methods of the EGAPP working group. Genet Med. 2009;11:3–14.Google Scholar
12. Fang, C, Otero, HJ, Greenberg, D, Neumann, PJ. Cost-utility analyses of diagnostic laboratory tests: A systematic review. Value Health. 2011;14:1010–1018.Google Scholar
13. CADTH. Guidelines for the economic evaluation of health technologies. Canada: Canadian Agency for Drugs and Technologies in Health; 2006. 46 p.Google Scholar
14. Beaulieu, M, de Denus, S, Lachaine, J. Systematic review of pharmacoeconomic studies of pharmacogenomic tests. Pharmacogenomics. 2010;11:1573–1590.Google Scholar
15. Wong, WB, Carlson, JJ, Thariani, R, Veenstra, DL. Cost Effectiveness of Pharmacogenomics. Pharmacoeconomics. 2010;28:1001–1013.Google Scholar
16. Paci, D, Ibarreta, D. Economic and cost-effectiveness considerations for pharmacogenetics tests: An integral part of translational research and innovation uptake in personalized medicine. Curr Pharmacogenomics Person Med. 2009;7:284–96.Google Scholar
17. Mittmann, N, Au, H-J, Tu, D, et al. Prospective cost-effectiveness analysis of cetuximab in metastatic colorectal cancer: Evaluation of National Cancer Institute of Canada Clinical Trials Group CO.17 trial. J Natl Cancer Inst. 2009;101:1182–1192.Google Scholar
18. Health Quality Ontario. KRAS Testing for anti-EGFR therapy in advanced colorectal cancer: An evidence-based and economic analysis. Ont Health Technol Assess Ser. 2010;10:1–49.Google Scholar
19. Dranitsaris, G, Norris, B, Hanna, W, O'Malley, F, Gelmon, K. Identifying the optimal timing of HER2/neu testing in patients with breast cancer: A Canadian cost minimization analysis. Breast Cancer Res Treat. 2002;76:S135–135.Google Scholar
20. Dendukuri, N, Khetani, K, McIsaac, M, Brophy, J. Testing for HER2-positive breast cancer: A systematic review and cost-effectiveness analysis. CMAJ. 2007;176:1429–1434.Google Scholar
21. Paulden, M, Franek, J, Pham, B, Krahn, M. Gene expression profiling for guiding adjuvant chemotherapy decisions in women with early breast cancer: A Cost-effectiveness analysis of 1000 strategies for the provision of adjuvant! Online, Oncotype Dx and Chemotherapy. Value Health. 2011;14:A167–167.CrossRefGoogle Scholar
22. Hannouf, MB, Xie, B, Brackstone, M, Zaric, GS. Cost-effectiveness of a 21-gene recurrence score assay versus Canadian clinical practice in women with early-stage estrogen- or progesterone-receptor-positive, axillary lymph-node negative breast cancer. BMC Cancer. 2012;12:447.Google Scholar
23. Basu, A, Meltzer, D. Value of information on preference heterogeneity and individualized care. Med Decis Making. 2007;27:112–127.Google Scholar
24. Wong, WB, Carlson, JJ, Thariani, R, Veenstra, DL. Cost effectiveness of pharmacogenomics. Pharmacoeconomics. 2010;28:1001–1013.CrossRefGoogle ScholarPubMed
25. IOM (Institute of Medicine). The economics of genomic medicine: Workshop summary. Washington, DC: The National Academies Press; 2013.Google Scholar
26. Elkin, EB, Marshall, DA, Kulin, NA, et al. Economic evaluation of targeted cancer interventions: Critical review and recommendations. Genet Med. 2011;13:853–860.Google Scholar
27. Ferrusi, IL, Leighl, NB, Kulin, NA, Marshall, DA. Do economic evaluations of targeted therapy provide support for decision makers? J Oncol Pract. 2011;7:36s–45s.Google Scholar
28. Postma, MJ, Boersma, C, Vandijck, D, et al. Health technology assessments in personalized medicine: Illustrations for cost-effectiveness analysis. Expert Rev Pharmacoecon Outcomes Res. 2011;11:367–369.Google Scholar
29. Annemans, L, Redekop, K, Payne, K. Current methodological issues in the economic assessment of personalized medicine. Value Health. 2013;16:S20–26.Google Scholar
30. Personalized Medicine Coalition. The case for personalized medicine, 3rd ed [Internet]. Personalized Medicine Coalition. http://www.ageofpersonalizedmedicine.org/objects/pdfs/Case_for_PM_3rd_edition.pdf (accessed October 26, 2012).Google Scholar
31. Lee, DW, Neumann, PJ, Rizzo, JA. Understanding the medical and nonmedical value of diagnostic testing. Value Health. 2010;13:310–314.Google Scholar
32. Birch, S, Donaldson, C. Valuing the benefits and costs of health care programmes: Where's the “extra” in extra-welfarism? Soc Sci Med. 2003;56:1121–1133.Google Scholar
33. Basu, A, Meltzer, D. Implications of spillover effects within the family for medical cost-effectiveness analysis. J Health Econ. 2005;24:751–773.Google Scholar
34. Merlin, T, Farah, C, Schubert, C, et al. Assessing personalized medicines in Australia: A national framework for reviewing codependent technologies. Med Decis Making. 2013;33:333–342.Google Scholar
35. Australian Government Department of Health and Ageing. Section D: Economic evaluation for the main indication [Internet]. http://www.pbs.gov.au/info/industry/listing/elements/pbac-guidelines/b-part-2/Section_D (accessed October 26, 2012).Google Scholar
36. Elkin, EB, Marshall, DA, Kulin, NA, et al. Economic evaluation of targeted cancer interventions: Critical review and recommendations. Genet Med. 2011;13:853–860.Google Scholar
37. Basu, A. Economics of individualization in comparative effectiveness research and a basis for a patient-centered health care. J Health Econ. 2011;30:549–559.Google Scholar
38. Ferrusi, IL, Earle, CC, Trudeau, M, et al. Closing the personalized medicine information gap: HER2 test documentation practice. Am J Manag Care. 2013;19:838–844.Google ScholarPubMed
39. Basu, A, Heckman, JJ, Navarro-Lozano, S, Urzua, S. Use of instrumental variables in the presence of heterogeneity and self-selection: An application to treatments of breast cancer patients. Health Econ. 2007;16:1133–1157.Google Scholar
40. NICE. Diagnostics Assessment Programme manual [Internet]. NICE. [cited 2014 Jan 6]. http://www.nice.org.uk/ (accessed January 6, 2014).Google Scholar
41. Husereau, D, Drummond, M, Petrou, S, et al. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. Int J Technol Assess Health Care. 2013;29:117–122.Google Scholar
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