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Common Drug Review Recommendations

Author

Listed:
  • Angela Rocchi
  • Elizabeth Miller
  • Robert Hopkins
  • Ron Goeree

Abstract

Background: The Common Drug Review (CDR) was created to provide a single process to review the comparative clinical efficacy and cost effectiveness of new drugs, and then to make formulary listing recommendations to Canadian publicly funded drug benefit plans. Objective: The objective was to conduct an in-depth analysis of Canadian Expert Drug Advisory Committee (CEDAC) recommendations to date, to explore predictors and possible explanatory factors associated with negative recommendations. Methods: Final recommendations were identified from inception (September 2003) to 31 December 2009. Using only publicly available information, recommendations were analysed under the following categories: submission specifics, drug characteristics, clinical factors and economic factors. Descriptive analyses were conducted, followed by statistical analyses, to determine which factors independently predicted a ‘do not list’ (DNL) recommendation. Results: The database consisted of 138 unique final recommendations. The overall DNL rate was 48%. Significant differences in DNL rates were observed between therapeutic areas, ranging from 0% for HIV antivirals up to 88% for analgesic drugs. In the univariate analysis, several factors were significantly associated with a DNL recommendation, including first-in-class drugs and use of clinical scales as an outcome. In the multivariate regression, four factors were significantly predictive of a DNL recommendation: clinical uncertainty (odds ratio [OR] 14), price higher than comparators (OR 9), request for reconsideration (OR 10) and price as the only economic evidence used (OR 18). Incremental cost-effectiveness thresholds were not predictive of recommendations. The hypothesis that economic factors did not impact recommendations when clinical factors were included first was supported by the analysis. Conclusions: This analysis documented an evidence-driven process that simultaneously weighted multiple factors. Clinical uncertainty and price considerations, but not economic results, had a strong impact on the recommendations. Insufficiency of clinical evidence may have resulted from the gap in evidence available at the time of product launch and the absence of demonstrated benefits to support innovative drugs. Copyright Springer International Publishing AG 2012

Suggested Citation

  • Angela Rocchi & Elizabeth Miller & Robert Hopkins & Ron Goeree, 2012. "Common Drug Review Recommendations," PharmacoEconomics, Springer, vol. 30(3), pages 229-246, March.
  • Handle: RePEc:spr:pharme:v:30:y:2012:i:3:p:229-246
    DOI: 10.2165/11593030-000000000-00000
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    References listed on IDEAS

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    1. Helen Dakin & Nancy Devlin & Yan Feng & Nigel Rice & Phill O'Neill & David Parkin, 2015. "The Influence of Cost‐Effectiveness and Other Factors on Nice Decisions," Health Economics, John Wiley & Sons, Ltd., vol. 24(10), pages 1256-1271, October.
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    3. Lesley Chim & Patrick Kelly & Glenn Salkeld & Martin Stockler, 2010. "Are Cancer Drugs Less Likely to be Recommended for Listing by the Pharmaceutical Benefits Advisory Committee in Australia?," PharmacoEconomics, Springer, vol. 28(6), pages 463-475, June.
    4. Anthony H. Harris & Suzanne R. Hill & Geoffrey Chin & Jing Jing Li & Emily Walkom, 2008. "The Role of Value for Money in Public Insurance Coverage Decisions for Drugs in Australia: A Retrospective Analysis 1994-2004," Medical Decision Making, , vol. 28(5), pages 713-722, September.
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    Cited by:

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    2. Karin Cerri & Martin Knapp & Jose-Luis Fernandez, 2014. "Public funding of pharmaceuticals in the Netherlands: investigating the effect of evidence, process and context on CVZ decision-making," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(7), pages 681-695, September.
    3. Fischer, Katharina E. & Rogowski, Wolf H. & Leidl, Reiner & Stollenwerk, Björn, 2013. "Transparency vs. closed-door policy: Do process characteristics have an impact on the outcomes of coverage decisions? A statistical analysis," Health Policy, Elsevier, vol. 112(3), pages 187-196.
    4. Katharina Fischer & Reiner Leidl, 2014. "Analysing coverage decision-making: opening Pandora’s box?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(9), pages 899-906, December.
    5. Rosenberg-Yunger, Zahava R.S. & Bayoumi, Ahmed M., 2014. "Transparency in Canadian public drug advisory committees," Health Policy, Elsevier, vol. 118(2), pages 255-263.
    6. Wranik, Wiesława Dominika & Gambold, Liesl & Peacock, Stuart, 2021. "Uncertainty tolerance among experts involved in drug reimbursement recommendations: Qualitative evidence from HTA committees in Canada and Poland," Health Policy, Elsevier, vol. 125(3), pages 307-319.
    7. Wranik, Wiesława Dominika & Zielińska, Dorota Anna & Gambold, Liesl & Sevgur, Serperi, 2019. "Threats to the value of Health Technology Assessment: Qualitative evidence from Canada and Poland," Health Policy, Elsevier, vol. 123(2), pages 191-202.

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