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Navigating uncertainty in policy decision making about new cancer drugs: A qualitative study of Canadian policymakers Presenter: Dr. S. Michelle Driedger,

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Presentation on theme: "Navigating uncertainty in policy decision making about new cancer drugs: A qualitative study of Canadian policymakers Presenter: Dr. S. Michelle Driedger,"— Presentation transcript:

1 Navigating uncertainty in policy decision making about new cancer drugs: A qualitative study of Canadian policymakers Presenter: Dr. S. Michelle Driedger, University of Manitoba Co-authors:Dr. Melissa C. Brouwers, McMaster University Gary Annable, University of Manitoba On behalf of the Uncertainty Project Research Team CADTH, April 14, 2015, Saskatoon

2 © Mischa Richter / The New Yorker Collection

3 © Bradford Veley /

4 The Study Mixed-methods study examining the navigation of uncertainty about policy decision making in four cancer control scenarios: Approval and funding of new drugs Mammography screening for women aged 40 to 49 years Prostate specific antigen (PSA) screening HPV vaccination programs 4

5 Methods Focus groups with  women about mammography screening (n = 46)  men about PSA screening (n = 47) Key informant interviews with policy makers (n = 29) Development of a policy decision making aid 5

6 Methods – Drug Scenario Qualitative interviews with officials (n = 16) who influence or make decisions about cancer drug policy in Canada: cancer agencies (n = 7) ministries of health (n = 4) organizations that evaluate and recommend drugs (n = 4) patient advocacy organizations (n = 1) Convergent interviewing technique 6

7 Sources of Uncertainty Evidence  Clinical  Economic Values  Political  Clinician  Patients Implementation Issues

8 Evidence – Clinical (RCTs) Priority reviews Approvals on Phase II data only Early trial closures Crossover designs Open-labeled (unblinded) trials Surrogate outcome measures (e.g., Progression- Free Survival, Quality of Life) Does clinical efficacy predict real-world effectiveness?

9 Evidence - Economic Analyses Uncertainty not quantified ICER thresholds are absent or not transparent Not subjected to same rigour or scrutiny as clinical evidence Economic models built by drug manufacturers Uncertainty in economic analyses are compounded when clinical evidence is weak/ uncertain

10 Values “Physicians give me the most trouble because they wear different hats and the hat they are most comfortable wearing is being their patient’s advocate. They tend have a hard time putting on the hat of ‘public funding for the societal overview.’ If we have restricted funds, do we try to do the best for everyone, or do we do exceptionally for one group and leave others out in the cold?”

11 Values “If it’s a mom who has a child who is going be starting kindergarten in three months, is that where you want to take her so she can see her child go to kindergarten for the first time? Most of us would say we’d spend however much money to do that, but then are we taking away that funding from somebody that you can extend their life by five years with a drug that has better survival benefits? It becomes really tricky because you have a confined funding envelope.”

12 Implementation - “Whipsaw Effect”

13 Diversity in Decision Making

14 Navigating Uncertainty – A Toolbox focus on the evidencepCODR pricing negotiations formulary management

15 Focus on the Evidence “ We fund based on the best evidence we have at a point in time.” “Our reimbursement criteria needs to align with what the evidence says.”

16 Evidence vs. Values “We want evidence to inform, but evidence doesn't make the decision. Any process like this has various people's values and perspectives, and we've tried to find systems that ensure fair and equitable decisions are made.” “We have a very strong evidence-based decision- making framework that takes into consideration the clinical and economic evidence, but it also takes into consideration some of the patient values as well.”

17 pCODR : Strengths Many provinces didn’t have the internal expertise to do their own evidence reviews All provinces get the same recommendation at the same time Governments and cancer agencies are working closer together Comparatively transparent process Provides clinician and patient input

18 pCODR: Some challenges Recommendations aren’t rank- ordered/prioritized ICER threshold is not transparent Provinces with internal expertise used to be able to implement new drugs sooner pre-pCODR

19 Pricing Negotiations Especially for drugs with poor cost-effectiveness (i.e., marginal benefits and high costs) pan-Canadian Pharmaceutical Alliance Risk sharing/pooling with manufacturers

20 Formulary Management Approval only for very specific indications Case-by-case approvals Conditional approvals to allow for collection of additional evidence to attempt to resolve residual uncertainty  e.g., Coverage with Evidence Development

21 So where does this leave us?

22 Any action is still a decision “When you don't have enough information to make a decision, it doesn’t mean you shouldn’t make a decision. Life goes on. It's almost better to make an educated decision—meaning you weigh the information you have and then decide to do something—than it is to sit and do nothing.”

23 Next steps Study limitations Uncertainty Assessment and Navigation (U-ANT) Multiple sclerosis (CCSVI/Liberation Therapy)

24 Conclusion: Managing Transparency Insights from Risk Communication: Transparency needs contextualization Need to be open about the nature and type of uncertainty People can accept evolving information Need to build a culture of flexible policy review

25 Acknowledgements & Questions Canadian Cancer Society Research Institute Uncertainty project team: Drs. Mita Giacomini (McMaster), Jeffrey Hoch (UToronto), Jeff Sisler (University of Manitoba), Donna Turner (CancerCare Manitoba), Ms Julie Makarski and Ms Samantha Craigie (McMaster University) Contact:

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