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COST-EFFECTIVENESS IMPACTS CANCER CARE FUNDING DECISIONS IN BRITISH COLUMBIA, CANADA, EVIDENCE FROM 1998 TO 2008

Published online by Cambridge University Press:  05 September 2017

Zahra Ismail
Affiliation:
Canadian Centre for Applied Research in Cancer Control Cancer Care Ontario
Stuart J. Peacock
Affiliation:
Canadian Centre for Applied Research in Cancer Control British Columbia Cancer Agency Simon Fraser University
Laurel Kovacic
Affiliation:
British Columbia Cancer Agency
Jeffrey S. Hoch
Affiliation:
University of California at Davis St. Michael's Hospital University of [email protected]

Abstract

Objectives: The Priorities and Evaluation Committee (PEC) funding recommendations for new cancer drugs in British Columbia, Canada have been based on both clinical and economic evidence. The British Columbia Ministry of Health makes funding decisions. We assessed the association between cost-effectiveness of cancer drugs considered from 1998 to 2008 and the subsequent funding decisions.

Methods: All proposals submitted to the PEC between 1998 and 2008 were reviewed, and the association between cost-effectiveness and funding decisions was examined by (i) using logistic regression to test the hypothesis that interventions with higher incremental cost-effectiveness ratios (ICERs) have a lower probability of receiving a positive funding decision and (ii) using parametric and nonparametric tests to determine if a statistically significant difference exists between the mean cost-effectiveness of funded versus not funded proposals. A sub-analysis was conducted to determine if the findings varied across different outcome measures.

Results: Of the 149 proposals reviewed, 78 reported cost-effectiveness using various outcome measures. In the proposals that used life-years gained as the outcome (n = 22), a statistically significant difference of nearly $115,000 was observed between the mean ICERs for funded proposals ($42,006) and for unfunded proposals ($156,967). An odds ratio indicating higher ICERs have a lower probability of being funded was also found to be statistically significant (p < .05).

Conclusions: Economic evidence appears to play a role in British Columbia cancer funding decisions from 1998 to 2008; other decision-making criteria may also have an important role in recommendations and subsequent funding decisions.

Type
Assessments
Copyright
Copyright © Cambridge University Press 2017 

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References

REFERENCES

1. Canadian Cancer Society/National Cancer Institute of Canada. Canadian cancer statistics 2008. Toronto: National Cancer Institute of Canada; April 2008 ISSN 08352976.Google Scholar
2. Canadian Strategy for Cancer Control. Establishing the strategic framework for the Canadian strategy for cancer control 2005. http://www.partnershipagainstcancer.ca/wp-content/uploads/2015/03/The-Canadian-Strategy-for-Cancer-Control-A-Cancer-Plan-for-Canada_accessible.pdf (accessed June 22, 2017).Google Scholar
3. Steinbrook, R. Saying no isn't NICE: The travails of Britain's National Institute for Health and Clinical Excellence. N Engl J Med. 2008;28:713722.Google Scholar
4. Drummond, MF, Sculpher, MJ, Torrance, GW, O'Brien, BJ, Stoddart, GL. Methods for the economic evaluation of health care programmes, 3rd ed. New York: Oxford University Press, 2005.CrossRefGoogle Scholar
5. Gold, MR, Seigel, JE, Russell, LB, Weinstein, MC. Cost-effectiveness in health and medicine. New York: Oxford University Press; 1996.CrossRefGoogle ScholarPubMed
6. Anell, A. Priority setting for pharmaceuticals. Eur J Health Econ. 2004;5:2835.Google Scholar
7. Rocchi, A, Menon, D, Verma, S, Miller, E. The role of economic evidence in Canadian oncology reimbursement decision-making: To lambda and beyond. Value Health. 2007;11:771783.Google Scholar
8. Morgan, SG, McMahon, M, Mitton, C, et al. Centralized drug review processes in Australia, Canada, New Zealand, and the United Kingdom. Health Aff (Millwood). 2006;25:337347.Google Scholar
9. Clement, F, Harris, A, Li, JJ, et al. Using effectiveness and cost-effectiveness to make drug coverage decisions: A comparison of Britain, Australia and Canada. JAMA. 2009;302:14371443.Google Scholar
10. 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;13:437452.Google Scholar
11. George, B, Harris, A, Mitchell, A. Cost-effectiveness analysis and the consistency of decision-making. Pharmacoeconomics. 2001;19:11031109.CrossRefGoogle ScholarPubMed
12. Collier, J. Parliamentary review asks NICE to do better still. Br Med J. 2008;336:5657.Google Scholar
13. Miners, AH, Garau, M, Fidan, D, Fischer, AJ. Comparing estimates of cost effectiveness submitted to the National Institute for Clinical Excellence (NICE) by different organizations: Retrospective study. Br Med J. 2005;330:65.Google Scholar
14. Williams, I, Bryan, S, McIver, S. How should cost-effectiveness analysis be used in health technology coverage decisions? Evidence from the National Institute for Health and Clinical Excellence approach. J Health Serv Res Policy. 2007;12:7379.Google Scholar
15. Harris, AH, Hill, SR, Chin, G, Li, JJ, Walkom, E. The role of value for money in public insurance coverage decisions for drugs in Australia: A retrospective analysis 1994–2004. Med Decis Making. 2008;28:713722.Google Scholar
16. Henry, DA, Hill, SR, Harris, A. Drug prices and value for money: The Australian Pharmaceutical Benefits Scheme. JAMA. 2005;294:26302632.Google Scholar
17. Hill, SR, Mitchell, AS, Henry, DA. Problems with the interpretation of pharmacoeconomic analyses: A review of submissions to the Australian Pharmaceutical Benefits Scheme. JAMA. 2000;283:21162121.Google Scholar
18. Tierney, M, Manns, B, Members of the Canadian Expert Drug Advisory Committee. Optimizing the use of prescription drugs in Canada through the Common Drug Review. Can Med Assoc J. 2008;178:432435.Google Scholar
19. McMahon, M, Morgan, S, Mitton, C. The common Drug Review: A NICE start for Canada? Health Policy. 2006;77:339-51.CrossRefGoogle ScholarPubMed
20. Canadian Agency for Drugs and Technologies in Health (CADTH). Common drug review submission guidelines for manufacturers. Ottawa: CADTH 2010.Google Scholar
21. Mason, J. Cost per QALY league tables: Their role in pharmacoeconomic analysis. Pharmacoeconomics. 1994;5:472481.Google Scholar
22. Statistics Canada [Internet]. Consumer price index, historical summary. From Statistics Canada. http://www40.statcan.ca/l01/cst01/econ46a.htm (accessed August 2008).Google Scholar
23. Eichler, HG, Kong, S, Gerth, W, et al. Use of cost-effectiveness analysis in health-care resource allocation decision-making: How are cost-effectiveness thresholds expected to emerge? Value Health. 2004;7:518528.Google Scholar
24. Chambers, JD, Neumann, PJ, Buxton, MJ. Does Medicare have an implicit cost-effectiveness threshold? Med Decis Making. 2010;30:E14-E27.Google Scholar
25. Hoch, JS, Sabharwal, M. Informing Canada's cancer drug funding decisions with scientific evidence and patient perspectives: The Pan-Canadian Oncology Drug Review. Curr Oncol. 2013;20:121124.CrossRefGoogle ScholarPubMed
26. Hoch, JS, Brown, MB, McMahon, C, Nanson, J, Rozmovits, L. Meaningful patient representation informing Canada's cancer drug funding decisions: Views of patient representatives on the Pan-Canadian Oncology Drug Review. Curr Oncol. 2014;21:263266.Google Scholar
27. Hoch, JS, Beca, J, Sabharwal, M, Livingstone, SW, Fields, AL. Does it matter whether Canada's separate health technology assessment process for cancer drugs has an economic rationale? Pharmacoeconomics. 2015;33:879882.CrossRefGoogle ScholarPubMed
28. Yong, JH, Beca, J, Hoch, JS. The evaluation and use of economic evidence to inform cancer drug reimbursement decisions in Canada. Pharmacoeconomics. 2013;31:229236.Google Scholar
29. Cramer, JS. Logit models from economics and other fields. New York: Cambridge University Press; 2003.Google Scholar
30. Masucci, L, Beca, J, Sabharwal, M, Hoch, J. Methodological issues in economic evaluations submitted to the pan-Canadian Oncology Drug Review. PharmacoEconomics Open, 2017. doi:10.1007/s41669-017-0018-3.Google Scholar
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