cadth 2015 a4 regier cadth bias(1)
TRANSCRIPT
Advancing Health Economics, Services, Policy and Ethics
2015 CADTH Symposium
Saskatoon, Saskatchewan
Dean A Regier, PhD
Cancer Control Research, BC Cancer Agency
Assistant Professor, School of Population and
Public Health, University of British Columbia
Problem #1
• Input from the public is not routinely pursued in health-care decision-making
• Public values viewed as biased
Problem #2
• Public values are (probably) biased
• Leads to misallocation of scarce resources
Public Engagement & Value
2
Involving the public in policy-forming activities
• Public includes patient/lay public
Normative & pragmatic motivations
• Democratic ideals; economic theory
• Comparative-effectiveness
Why Public Engagement?
3
4*Regier DA, Bentley C, Mitton C, et al. Public Engagement in Priority-Setting: Results from a pan-Canadian Survey of Decision-Makers in Cancer
Control. Social Science & Medicine; 2014: 122:130-139.
Relative to clinical effectiveness and cost
• Input from the public is rarely pursued
Barriers
• Implies public input is biased
Stated preference elicitation of utility
• Non-market valuation of goods
Hypothetical bias
• Benefit over-valuation leads to investing in goods that cost too much in terms of available alternatives
Mitigating hypothetical bias
• Rationality tests; cheap-talk; oath
Public Engagement & Bias
5
Communication theory
The medium is the message - McLuhan, 1964
• The medium delivers change separate from content
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Hypothesis: a video introduction to a stated preference study will differently engage respondents and mitigate hypothetical bias
Next generation genomic sequencing
• Predictive therapy, prognostic therapy, hereditary cause of disease
Potential of incidental findings
• Information on diseases not related to current diagnosis
Background
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Published list of incidental findings (Green et al, 2013)
• High-penetrance & clinical utility
• List of 56 genes, 24 disorders
• Labs look for mutations, IF’s returned to patient, through managing physician
Controversial
• Patients not offered a choice
• (Public not consulted)
ACMG Recommendations
8
Objective
• Personal utility for the return incidental findings
• Discrete choice experiment (two choice + opt-out)
Respondent Sample
• General public in Canada (N=1200)
• English and French language versions
Objective & Sample
9
Define Attributes/levels
• Cognitive interviews (n=6)/ 2 focus groups (n=12)
Experimental design
• D-efficient design with informative priors
Statistical Analysis
• Mixed Logit Model (preference heterogeneity)
Welfare analysis
• Willingness to pay (compensating variation)
Methods Approach
10
Evaluate difference
in welfare estimates
D1
D2
D3Text Introduction
Only
Study design
Video Introduction
& Text Intro
English-speaking
Respondents
D4
randomized randomized
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Choice task example
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Option A
Option B
No information
Diseases with a 80% lifetime risk or higher
Diseases with a 5% lifetime risk or higher
No information
Recommended effective medical treatment and lifestyle change
Recommended effective medical treatment
only
No information
Mild health consequences
Moderate health consequences
No information
Does not provide information on carrier status
Information on if your family members could
be affected
No information
$425
$1500
$ 0
Option A
Option B
No Information
Disease Risk More disease will be identified if the lifetime risk is lower
Disease Treatability
Disease Severity Health consequences of the diseases you may develop You m
Carrier Status Disease risk not affecting you but can affect your family Cost to you
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Video+TextVersion
Text Version
Scenario 1Medical treatment , 80% or greater risk, severe QOL
$42095% CI 191-528
$515 95% CI 417-778
Scenario 2 (vs Scenario 1)Medical & No treatment , 80% or greater risk, severe QOL
$235 95% CI 195-275
$32095% CI 225-371
*t-test (unequal variances)=-1.66, p-val=0.11
• Lower WTP values in video version
• Potential to mitigate hypothetical bias
Welfare Analysis
1. Is it necessary for decision-makers to consult the public for each health care investment/disinvestment decisions?
2. Willingness to pay (and utility) is often biased, is there a role for this metric in decision-making?
• Focus on naturalistic units?
3. Do researchers need do more with how the public is engaged?
Questions
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A d v a n c i n g H e a l t h E c o n o m i c s , S e r v i c e s , P o l i c y a n d E t h i c s
Thank-you
• Acknowledgements: Stuart Peacock, Reka Pataky, Kimberly van der Hoek, Gail Jarvik, Jeffrey Hoch, David Veenstra
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• Funding for this research obtained from the Canadian Centre for Applied Research in Cancer Control (ARCC); ARCC is funded by the Canadian Cancer Society Research Institute grant #019789, #703549