Transcript Tony O Hagan

CHEBS Activities and Plans
Tony O’Hagan
Director
17/12/2002
CHEBS Launch Seminar
What is CHEBS?
• An official interdisciplinary research centre of
the University of Sheffield
• A collaboration that builds on a unique
combination of strengths
› Bayesian Statistics – Department of Probability and
Statistics
› Health Economics – ScHARR
› Operational Research – ScHARR
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CHEBS Launch Seminar
CHEBS’ Mission
• To engage in innovative research, developing
methodology based on Bayesian statistics for
solution of problems in health economics
• To set standards for statistical analysis of health
economic data and models
• To promote dialogue with the pharmaceutical
industry, including consultancy and training
• To influence best practice in presentation of
health economic information to regulators and
health care providers
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CHEBS Activities
• Primary research
› CHEBS Research Fellow
• Focus Fortnights
› Invited visiting experts
› Dissemination workshop
› Strategic research themes
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Evidence Synthesis
Value of Information
Elicitation
Costs …
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CHEBS Activities
• Short courses
• Research contracts, participating in:
› Department of Health – Multiple Sclerosis
› NICE – Decision Support Unit
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CHEBS Base Funding
• Base funding from sponsors
› pays for Research Fellows, Focus Fortnights,
administrative costs, etc.
• Ensures academic freedom
› informed by needs of sponsors and other
stakeholders
• Sponsors benefit from
› briefings and seminars,
› access to a unique blend of expertise
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Bayesian Statistics in Health
Economics
Some research areas:
• Trial design and analysis
• Modelling costs
• Quantifying uncertainty & evidence synthesis
• Outcomes – QoL estimation and uncertainty
• Sensitivity and VoI analysis of economic models
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Trial design and analysis
• Design
› Must use prior information!
› More rational design criteria
› Sequential design
• Analysis
› Can use prior information
› More accurate modelling
› More interpretable inferences
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CHEBS Launch Seminar
Modelling costs
• Cost distributions are highly skew
• Sample sizes are often small
• Conventional robust methods …
› Normal distributions
› Bootstrapping
• … are criterion robust but not inference robust
› Sample means are inefficient and sensitive to outliers
• Tails matter
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Quantifying uncertainty &
evidence synthesis
• Uncertainty has many sources
• Only Bayesian methods can quantify and
account for all kinds of uncertainty
› Randomness
› Lack of knowledge
• Synthesising evidence from diverse sources
requires careful consideration of uncertainties
› Bayesian analysis of primary data feeds into
economic models
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Outcomes
• Utilities
› Bayesian methods can better estimate utility
functions from raw preference data
› Uncertainty in the estimated utilities can be
quantified
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Sensitivity & VoI analyses
• Sensitivity analysis
› Parameter distributions intrinsically Bayesian
» Evidence synthesis
› Efficient propagation of uncertainty through models
› Detailed analysis of sensitivity to individual
parameters or groups of parameters
› Value of information analysis
» EVPI
» EVSI
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CHEBS Launch Seminar
The future is Bayesian
• Demand for Bayesian methods is increasing at a
spectacular rate
• Driven by … conceptual advantages
› Bayesian inferences answer the question
• … practical advantages
› Able to use all available information
• … computational advantages
› Able to tackle more complex models and data
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CHEBS Launch Seminar
The future is Bayesian
• This is happening in many fields
› Specially in younger disciplines like health economics
• Barriers to acceptance are crumbling
› Regulators increasingly open to Bayesian methods
› Bayes has achieved academic respectability
• Inertia is still a problem!
• Remaining barriers are being addressed
› Lack of software is a damper on take-up
› Clearer guidelines are needed on priors
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The future is multidisciplinary
• Many skills must come together
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Statistics
Economics
Modelling/OR
Decision analysis
Clinical/pharmaceutical/…
Sociology/psychology
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CHEBS Launch Seminar
The future is multidisciplinary
• Many stakeholders’ interests must be recognised
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Patients
Industry
Practitioners
Taxpayers
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