Using DCEs to estimate utility weights
within the framework of QALYs
Professor Mandy Ryan
Health Economics Research Unit, University of Aberdeen
HERU is supported by the Chief Scientist Office of the Scottish Executive Health Department and the
University of Aberdeen.
The author accepts full responsibility for this talk.
Structure
• What DCEs are and background to their use in Health
Economics
• Application – developing a utility index in the area of
glaucoma
anchoring between 0 and 1 (John and Theresa)
distinguishing ‘weight’ from ‘scale’ (Terry)
assumption and analysis issues (Jorge, John +
Theresa)
Discrete choice experiments
• Attribute based hypothetical survey measure of value
• Origins in mathematical psychology
 Distinguish from conjoint analysis
 Also known as ‘Stated preference discrete choice modelling’
• Increasingly used in environmental, transport and health
economics
Can’t have the best of everything!
Check-in service
Ticket price
Entertainment
Food and drink
Legroom
Reclining chair
Example of binary - Yes/No response
Place of Screening Type of Screening
Cost to you of
Chlamydia
Screening
Chance of Pelvic
Inflammatory Disease
(PID) if not screened.
Type of Information
and Support when
you are given
Screening Results
Choice 1 Family Planning
Clinic
Full Pelvic
Examination
£5
10%
None
Choice 2 Family Planning
Clinic
Perineal Swab
£10
0%
None
Genito Urinary
Choice 3 Medicine (GUM)
Clinic
Urine Test
£10
10%
Support of Trained
Health Advisor
At Home
Perineal Swab
£5
5%
Support of Trained
Health Advisor
At Home
Urine Test
Free
0%
None
At GP Clinic
Full Pelvic
Examination
£20
0%
Support of Trained
Health Advisor
Choice 4
Choice 5
Choice 6
I would
have Test
I would
not have
Test
Example of generic multiple choice –
including a neither option
Question 4
Length of wait
Time with doctor
Pain Management
Service
Cost to you
Which Clinic
would you prefer
(tick one box
only)?
Clinic A
28 weeks
15 mins
No Specialist
Team
£60
Prefer Clinic A
Clinic B
6 weeks
45 mins
Specialist
Team
£60
Prefer Clinic B
Neither
Discrete choice experiments
• Attribute based hypothetical survey measure of value
• Origins in mathematical psychology
 Distinguish from conjoint analysis
 Also known as ‘Stated preference discrete choice modelling’
• Increasingly used in environmental, transport and health
economics
DCEs – their use in HE
• Pre 1970 - cost-benefit analysis
 human capital approach
 willingness to pay
• 1970s - cost-effectiveness analysis
 e.g. cost per life year
• 1980s - cost-utility analysis
 e.g. cost per Quality Adjusted Life Years (QALYs)
 Standard gamble and time trade-offs
• 1990s - cost-benefit analysis
 health, non-health and process attributes
 Contingent valuation method and discrete choice experiments
• 2000 forward
 the importance of factors beyond health outcomes
 NICE
• WTP for a QALY
• Estimation of utility weights
Eliciting a health state utility index using a
discrete choice experiment: an application
to Glaucoma
Funded by Ross Foundation
Jen Burr, Mary Kilonzo, Mandy Ryan,
Luke Vale
Health Economics Research Unit, University of Aberdeen
HERU is supported by the Chief Scientist Office of the Scottish Executive Health Department and the
University of Aberdeen.
The author accepts full responsibility for this talk.
Case Study - Glaucoma
• chronic eye disease - progressive damage to optic nerve
• does not reduce length of life but associated with impaired
quality of life
• outcomes - intraocular pressure reduction and measures of
visual function
• do not capture impact of condition or treatment on emotional
and physical functioning or lifestyle
• Standard gamble and time trade-off not appropriate
Conducting a DCE
• Stage 1 - Identifying attributes and levels
• Stage 2 - Experimental design to determine
choices
• Stage 3 - Collecting data
 Principles of a good survey design
• Stage 4 - Data analysis
 Discrete choice modelling
• Conditional logit model and developments
– nested logit, random parameter logit
Attributes and Levels
•
•
•
•
•
•
Attributes
Central and Near Vision
Lighting and glare
Mobility
Activities of daily living
Local eye discomfort
Other effects of glaucoma
and treatment
•
•
•
•
Levels
No difficulty
Some difficulty
Quite a bit of difficulty
Severe difficulty
Experimental design
• Fractional factorial design of 32 choices
 Main effects no interactions
• Properties
 Orthogonality
 Level balance
 Minimum overlap
Example of a DCE choice – respondents were
asked what they think is WORSE
SITUATION A
SITUATION B
No difficulty with:
Central and near vision
Lighting and glare
Mobility
Some difficulty with:
Activities of daily living
Eye discomfort
Other effects of glaucoma and its treatment
No difficulty with:
Central and near vision
Some difficulty with:
Lighting and glare
Quite a lot of difficulty with:
Activities of daily living
Other effects of glaucoma and its treatment
Severe difficulty with:
Mobility
Eye discomfort
(Tick one
box only)
Situation A
Situation B
Rationality tests
 Dominance tests too easy and may question credibility of
experiment
 Sen’s expansion and contraction rationality tests used
Data collection
• Subjects from 4 hospital-based clinics and 1 community-based
glaucoma clinic across two eye centres in the UK (Aberdeen and
Leeds) received questionnaire (n=225)
• Also recruited volunteers from the International Glaucoma
Association (IGA) (n=248)
Analysis of DCE
• QWij = ∑dlXdl + e + u
• where
QWij is the quality weight for outcome state i as valued by
individual j
 Xdl is a vector of dummy variables
• where d represents the attribute from the profile measure
• l the level of that attribute
Estimating utility weights
• summation of the coefficients associated with the best
level for each attribute
• Rescaled between zero (worse level of all attributes)
and 1 (best level of all attributes)
Response rates and rationality
• 289 subjects responded to DCE questionnaire
• 3 respondents failed both consistency tests
• Analysis performed on 286 respondents
• Analysed according to severity
Results of the DCE
Attributes and levels
Coefficient
Central and near vision tasks
No difficulty
1.254
Some difficulty
0.852
Quite a lot of difficulty
0.526
No, some and quite a lot of difficulty
0.272
No difficulty
0.921
Some difficulty
0.577
Quite a lot of difficulty
0.349
Lighting and glare
Mobility
Visual judgement for activities of daily living
No difficulty
0.999
Some difficulty
0.720
Quite a lot of difficulty
0.431
No difficulty
0.241
Some and quite a lot of difficulty
0.134
No difficulty
0.202
Some and quite a lot of difficulty
0.169
Eye discomfort
Other effects
Quality weights
Dimension
Index
Central and Near Vision
Dimension
Index
Activities of daily living
No difficulty
0.322
No difficulty
0.257
Some difficulty
0.219
Some difficulty
0.185
Quite a lot
0.135
Quite a lot
0.111
severe
0
severe
0
Eye discomfort
Lighting and glare
No difficulty
0.070
Some difficulty
0
Quite a lot
0
severe
0
Mobility
No difficulty
0.237
Some difficulty
0.148
Quite a lot
0.090
severe
0
No difficulty
0.062
Some difficulty
0.035
Quite a lot
0.035
severe
0
Other effects
No difficulty
0.052
Some difficulty
0.043
Quite a lot
0.043
severe
0
Utility score for BEST health state
Situation description
Quality
weights
Utility
Score
You have no difficulty with central and near vision
You have no difficulty with lighting and glare
0.322
0.070
1
You have no difficulty with mobility
0.237
You have no difficulty with activity of daily living
0.257
You have no difficulty with local eye discomfort
0.062
You have no difficulty with other effects of glaucoma 0.052
and its treatments
Utility score for WORSE health state
Situation description
Quality
weights
Utility
Score
You have severe difficulty with central and near
vision
0
0
You have severe difficulty with lighting and glare
0
You have severe difficulty with mobility
0
You have severe difficulty with activity of daily living 0
You have severe difficulty with local eye discomfort
0
You have severe difficulty with other effects of
glaucoma and its treatments
0
Utility score for intermediate health state
Situation description
Quality
weights
You have some difficulty with central and near vision 0.219
You have some difficulty with lighting and glare
0
You have some difficulty with mobility
0.148
You have no difficulty with activity of daily living
0.257
You have no difficulty with local eye discomfort
0.062
You have no difficulty with other effects of glaucoma 0.052
and its treatments
Utility
Score
0.737
Some general points
• One of few studies to estimates utility weights from DCEs
(though appears to be increasing)
• Programme specific!
• Response rate 62% good for DCE, though issues of
generalisability are important
• Preferences differed according to severity
Points for Discussion
• Weights for use in programme specific QALY
 What if want to generate generic QALY weights (anchored
between DEATH and PERFECT HEALTH)
• How value DEATH?
• Distinguishing weight (importance of attribute) from scale
(importance of attribute levels)
• Econometric analysis
 Assumptions of logit model
• Errors terms independent, irrelevance of alternatives and heterogeneity
 Decision making heuristics
• Do individuals trade across attributes