CADTH 2015 Symposium

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
Michelle.Driedger@umanitoba.ca
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 / bradveley.com

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
- Patient
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 evidence pCODR
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 and/or
private insurers
 “pay-for-performance” agreements with
manufacturers (company rebates $ for patients
that don’t benefit)

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. © Mischa Richter / The New Yorker Collection

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 Comm.
 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 ScienceCartoonsPlus.com

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: Michelle.Driedger@umanitoba.ca