EQ-5D-5L:
development of the first national tariffs
ISPOR Symposium
The EuroQol Group
May 2015, Philadelphia, USA
Disclosure
• This symposium is sponsored by The EuroQol
Research Foundation, a not-for-profit organization
The EuroQol Group
Overview of Presenters
• EQ-5D-5L: an international approach to valuing health
Speaker: Simon Pickard
• An EQ-5D-5L value set for England
Speaker: Ben van Hout
Overview of Presenters
• A user’s perspective on the EQ-5D-5L
– considerations for users
Speaker: Kristina S. Boye
• Future directions
– Initiatives
– applications beyond economic evaluations
Speaker: Jan van Busschbach
An international approach to valuing health
A. Simon Pickard, PhD
Professor, University of Illinois at Chicago
Chair of Executive Committee, EuroQol Group
Overview
• EuroQol Group
• Overview of EQ instruments
• EQ-5D-5L: status
– Descriptive system
– Value sets
• EQ-VT valuation protocol
Vision
The EuroQol Group aims to improve
decisions about health and health care
throughout the world by developing,
promoting and supporting the use of
instruments with the widest possible
applicability for the measurement and
valuation of health.
EQ-5D Instruments: 2015 Status
EQ-5D-3L Translations
•
>170 languages in self-complete
paper format
EQ-5D-5L Translations
•
>120 languages in self-complete
paper format
EQ-5D-Y Translations
•
•
> 30 languages
Youth between 8-11 years
Available versions
•
•
•
Electronic (Web, PDA, Tablet)
Telephone, IVRS
Proxy, Face-to-face
Translated
EQ-5D-3L
• Brief, concise
• Defines 243 health
states
• We wanted to
improve descriptive
richness and
discriminatory power
EQ-5D-5L
• Added 2 levels per
dimension
• Development of EQ5D-5L descriptive
system
– Herdman M, Gudex C, Lloyd
A, et al. Development and
preliminary testing of the new
five-level version of EQ-5D
(EQ-5D-5L). Qual Life Res.
2011;20(10):1727-1736.
EQ-5D-5L: Measurement properties
• A multi-country, cross-sectional study was conducted
in 8 patient groups that compared the performance of
the EQ-5D-3L and EQ-5D-5L.
• In general, EQ-5D-5L improved discriminative ability
and reduced ceiling effects
–
Janssen MF, Pickard AS, Golicki D, et al. Measurement properties of the EQ-5D-5L compared to the
EQ-5D-3L across eight patient groups: a multi-country study. Qual Life Res. 2013;22(7):1717-1727.
• Since 2013, 10 more studies in various countries and
disease groups have reported similar results
EuroQol valuation research aims
• Take advantage of advances in technology –
computer based methods (valuation task and data
collection)
– The EuroQol Valuation Technology or “EQ-VT”
• Provide a fully documented, standardized protocol to
enhance consistency between valuation studies by
investigators around the world
• Refine the valuation methods and protocol as we
learn
EuroQol Group’s Valuation Technology:
The EQ-VT
• Data collection
–
–
–
–
computer assisted personal interviews (CAPI) approach
Visually displays tasks
automates the iterative procedures in TTO
captures and time stamps participant responses
• Uses underlying block design to present health states
• Facilitates protocol compliance + data quality monitoring
 QC Tool
• Accompanying EQ-VT: interview script; interviewer
training resources; guidance on modelling.
EQ-VT valuation protocol
Introduction
•
Self reported health on the EQ-5D-5L
descriptive system
• Self reported health on the EQ-VAS
• Background questions
Composite Time Trade-Off
•
•
•
Instructions and example of TTO task
TTO valuation of 10 EQ-5D-5L states
TTO debriefing/structured feedback
Discrete Choice
•
•
Instructions and example of DC task
DC valuation of 10 pairs of EQ-5D-5L
states
• DC debriefing/structured feedback
TTO task: better than dead (values>0)
U(hi) = (x/t)
where x is time in
full health and
t is time in health
state hi at the
respondent’s point
of indifference
Example shown:
U(hi) = 5/10
= 0.5
TTO task: states worse than dead
t= 20 years
lead time(LT)= 10 yrs
U(hi)= (x-LT)/(t-LT)
= (x-10)/10
Min value= -1
Example shown:
U(hi) = (5-10)/10
= -0.5
Discrete choice tasks
Conducting an EQ-5D-5L valuation study:
Required resources
The EQ-VT protocol
EQ-VT Software, including QC Tool
Interviewer training resources
Translation services
Technical support & advice
Guidance on reporting
An EQ-5D-5L value set for England
Ben van Hout, HEDS, ScHARR , University of
Sheffield, United Kingdom
Project team
•
Project team from OHE & University of Sheffield: Nancy Devlin and
Ben van Hout (PIs); Koonal Shah (project manager); Brendan Mulhern
and Yan Feng
•
In collaboration with:
–
–
–
–
Sub-contractor (data collection): Ipsos MORI
The EuroQol Group (copyright holder of EQ-5D-5L and EQ-VT)
Aki Tsuchiya (Pret-AS data)
Ethics approval granted by the research ethics committee of the University
of Sheffield’s School of Health and Related Research
Study design
• Research protocol developed by the EuroQol Research Foundation
• Stated preference data collected in face-to-face computer-assisted
personal interviews
• n = 1000 members of the adult general public of England, selected at
random from residential postcodes
• Sample recruitment sub-contracted to Ipsos MORI
• Each respondent valued 10 health states using TTO, randomly assigned
from 86 health states in an underlying design; and seven DCE tasks,
randomly assigned from 196 pairs of states
• ‘Composite’ TTO approach: conventional TTO for values > 0 and ‘lead
time’ TTO for values < 0
• The EuroQol Valuation Technology software (EQ-VT) was used to
present the tasks and to capture respondents’ responses
Data
• Interviews conducted between Nov 2012 and May 2013
• 996 completed the valuation questionnaire (response rate approx. 40%)
• Close attention paid to data quality: daily monitoring of uploaded data
and follow-up with interviewers
• Sample broadly representative of English adult general public, although
a somewhat larger proportion of retired individuals and a smaller
proportion of younger individuals
DCE data
%A
dif in misery
90%
80%
-5
70%
0
5
100%
delta sum of scores
%B
10
Proportions choosing A and B based on
relative severities of A and B
60%
-10
50%
40%
0
30%
20%
10%
-10
-8
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
7
8
9
0%
Misery index of state A minus misery index of
state B
1
TTO data
• Fewer values < 0 (worse than dead) compared to Dolan (1997) value set –
as expected.
• Clusters of values at -1, 0, 0.5 and 1
• Logical inconsistencies (e.g. 55555 > than other states)
• ‘Unusual’ valuations e.g. mild states being valued < 0
• Interviewer effects apparent
Distributions, by state
40
0
20
density
20
10
0.0 0.5 1.0
-1.0
0.0 0.5 1.0
-1.0
0.0 0.5 1.0
12111 mean= 0.868
21111 mean= 0.83
11122 mean= 0.806
0.0 0.5 1.0
-1.0
0 5
density
20
0
density
-1.0
15
value
40
value
20 40
value
0
0.0 0.5 1.0
-1.0
0.0 0.5 1.0
11211 mean= 0.866
12121 mean= 0.823
11212 mean= 0.801
0.0 0.5 1.0
value
-1.0
0.0 0.5 1.0
value
0 5
density
density
20
0
-1.0
15
value
15
value
40
value
0 5
density
-1.0
density
11112 mean= 0.815
0
20
density
40
11221 mean= 0.862
0
density
11121 mean= 0.876
-1.0
0.0 0.5 1.0
value
Distributions, by state
15
0
5
density
8 12
4
0.0 0.5 1.0
-1.0
0.0 0.5 1.0
-1.0
0.0 0.5 1.0
33253 mean= 0.465
43514 mean= 0.443
31525 mean= 0.428
density
0.0 0.5 1.0
0
0
4
density
-1.0
5 10
value
8
value
15
value
0 5
-1.0
0.0 0.5 1.0
-1.0
0.0 0.5 1.0
12334 mean= 0.463
15151 mean= 0.436
31524 mean= 0.423
density
density
0
4
0
-1.0
0.0 0.5 1.0
value
-1.0
0.0 0.5 1.0
value
0 2 4 6 8
value
10 15
value
8
value
5
density
-1.0
density
23152 mean= 0.435
0
4
density
8 12
23514 mean= 0.46
0
density
54231 mean= 0.473
-1.0
0.0 0.5 1.0
value
Distributions, by state
-0.5
0.0
0.5
10 15
1.0
-1.0
-0.5
0.0
0.5
value
53244 mean= 0.148
55555 mean= 0.016
density
0
0 5
1.0
100
value
15
-1.0
density
5
0
10
density
20
43555 mean= 0.119
0
density
21444 mean= 0.148
-0.5
0.0
0.5
1.0
-1.0
-0.5
0.0
0.5
value
value
52455 mean= 0.12
NA mean= NA
1.0
-1.0
0.0
density
10
5
0
density
1.0
-1.0
-1.0
-0.5
0.0
value
0.5
1.0
-1.0
-0.5
0.0
value
0.5
1.0
Descriptive statistics
standard deviation of values
100
0
-0.5
0.0
0.5
0.0 0.2 0.4 0.6 0.8 1.0
1.0
minv
(varv^0.5)
maximum value
range of values used
0
100
50
0
200
Frequency
400
150
-1.0
Frequency
50
Frequency
100
50
0
Frequency
150
150
minimum value
0.0
0.2
0.4
0.6
maxv
0.8
1.0
0.0
0.5
1.0
range
1.5
2.0
Interpretation of the data
• Our process for examining the individual-level data:
–
–
–
–
Let’s look at all our respondents
Put expected value according to DCE on x axis
Put values on Y axis
And stare at 1,000 graphs
Examination of individual-level
data
Decisions regarding the data
• Excluded 23 respondents who gave all 10 health states the same value;
and 61 respondents who valued 55555 (misery score = 25) no lower
than the value they gave to the mildest health state included in their
block (misery score = 6)
• The core modelling dataset includes 912 respondents, with 10 TTO
observations for each
• Censored 105 individuals/477 zeros with >2 states at zero (that is out of
1,315 zeros)
• Censored 68 individuals/142 data points with inconsistent negative data
Modelling
•
The main specifications included models with 5, 9, 10 and 20
parameters (four parameters for each of the five dimensions reflecting a
utility decrement for each severity level)
•
All models were estimated for both TTO and DCE data, and ‘hybrids’ of
these
•
Values at -1 treated as censored
•
Values at +1 are treated as censored
•
The variance decreases with an increasing value of the value
(heteroskedasticity)
•
Heterogeneity explored via random coefficient models, which estimate
value functions for every individual member of the sample
The relatively low value of the good health
states
Heterogeneity
• The coefficients beta which reflect weights for dimensions
and levels are normally distributed over the population
• The shape of the value as a function of x’beta follows a:
Normal distribution
Lognomal distribution
Multinomial distribution
– (3 latent classes)
1
0.5
0
value
•
•
•
-0.5
-1
-1.5
x'beta
EQ-5D-5L value set for England
constant
Mobility
The final
EQ-5D-5L
value set
model
Self care
Usual activities
Pain/discomfort
Anxiety/depression
1.003
slight
0.057
moderate
0.074
severe
0.207
unable
0.255
slight
0.059
moderate
0.083
severe
0.176
unable
0.208
slight
0.048
moderate
0.067
severe
0.165
unable
0.165
slight
0.059
moderate
0.079
severe
0.244
extreme
0.298
slight
0.072
moderate
0.099
severe
0.282
extreme
0.282
Comparison with 3L and crosswalk
5L value set
Crosswalk value set
3L value set
% health states
worse than dead
3.2% (100 out of
3,125)
26.66% (833 out of
3,125)
34.57% (84 out of
243)
Preferences
regarding
dimensions (from
the most important
to the least
important)
Pain/Discomfort
Pain/Discomfort
Pain/Discomfort
Anxiety/Depression
Mobility
Mobility
Mobility
Anxiety/Depression
Anxiety/Depression
Self-care
Self-care
Self-care
Usual Activities
Usual Activities
Usual Activities
Value of 55555
(33333)
-0.208
-0.49
-0.594
Value of 11112*
0.928
0.879
0.848
Value of 11121*
0.941
0.837
0.796
Value of 11211*
0.952
0.906
0.883
Value of 12111*
0.941
0.846
0.815
Value of 21111*
0.943
0.877
0.850
Range of values
[-0.208, 1]
[-0.490, 1]
[-0.594, 1]
Implications of the results
•
The 5L Value set for England has a lower range of values than the
current UK EQ-5D value set
•
Higher minimum value for 55555 (5L) (-0.208) than 33333 (3L) (-0.56):
as expected, given known issues with the Dolan (1997) value set
•
The proportion of health states with negative values is considerably
lower
•
No ‘N3’ term – it did not improve the model
•
Implies treatments for very severe conditions may have lower QALY
gains than at present
•
The greater descriptive sensitivity of the EQ-5D-5L will be somewhat
counteracted by the nature of the 5L value set compared to the
previous 3L value set
A User’s Perspective on the EQ-5D-5L
Kristina S. Boye, RPh, MS, MPH, PhD
Senior Research Advisor, Eli Lilly and Company
Deputy Chair, EuroQol Executive Committee
May 2015
Overview
•
•
•
•
•
•
•
•
•
EQ-5D-3L vs EQ-5D-5L versions
Should I use the 3L or 5L version in my study?
Availability of EQ-5D-5L formats and translations
Availability of EQ-5D-5L value sets
Which value set or scoring algorithm should I use?
Country specific considerations
How to obtain the EQ-5D
Do I need a license to use EQ-5D?
Need more information?
Example:
EQ-5D-3L vs EQ-5D-5L versions: Mobility
EQ-5D-3L
EQ-5D-5L*
 I have no problems in walking
about
 I have some problems in walking
about
 I am confined to bed
 No problems in walking about
 Slight problems in walking about
 Moderate problems in walking
about
 Severe problems in walking
about
 Unable to walk about
*Instructions for the 5L version: By placing a tick in one box in each group below,
please indicate which statements best describe your own health state TODAY.
EQ-5D-3L vs EQ-5D-5L versions
EQ-5D-3L VAS
EQ-5D-5L VAS
Should I use the
3L or 5L version in my study?
•
•
•
•
•
•
•
•
Timing
Comparability
Desire for a new value set or scoring algorithm
Sensitivity
Translations
Mode of data collection
Use of both instruments
Cost
Availability of EQ-5D-5L
Formats and Translations
Available Format
Number of translations currently
available
Paper
132
Tablet
102
Personal Digital Assistant (PDA)
93
Web
54
Interactive voice response (IVR)
30
Telephone
14
Proxy Paper version 11
5
Proxy Paper version 22
8
Face to Face
1
1Asking
the proxy to rate how he/she (the proxy would rate the patient's HRQoL).
Asking the proxy to rate how he/she (the proxy) thinks the patient would rate his/her own HRQoL if he/she (the
patient) was able to communicate it.
The number of available translations is still growing and new translations will be produced, if needed.
2
State of play EQ-VT studies
In preparation
France
Italy
USA
Portugal
Ongoing
Completed
Available
State of play EQ-VT studies
In preparation
Ongoing
France
Hong Kong
Italy
Singapore
USA
Indonesia
Portugal
Ireland
Completed
Available
State of play EQ-VT studies
In preparation
Ongoing
Completed
France
Hong Kong
UK
Italy
Singapore
Spain
USA
Indonesia
The Netherlands
Portugal
Ireland
Canada
China
Korea
Thailand
Uruguay
Germany
Available
State of play EQ-VT studies
In preparation
Ongoing
Completed
Available
France
Hong Kong
UK
England
Italy
Singapore
Spain
Japan
USA
Indonesia
The Netherlands
Portugal
Ireland
Canada
China
Korea
Thailand
Uruguay
Germany
Which value set or scoring
algorithm should I use?
• When analyzing a multi-country clinical trial, should I analyze
each country by its country specific data set or just use one
value set for all the data?
– Several schools of thought
• When should I use the available ‘crosswalk’ scoring
methodology?
– This depends on the study objectives, timing and overall needs
– It back-translates the 5L system into the 3L and gives you 3L
values which therefore do not take advantage of the 5L system
Country specific considerations
• Which version –the 3L or 5L- is preferred in each
country?
– Look to regional HTA guidance
– Consider the study needs
• What are the differences in the 5L value sets by country?
– Research in progress
How to obtain EQ-5D
• Go to our website euroqol.org and register your study
Do I need a license to use EQ-5D?
• Answer is Yes
Our licensing policy will determine if a fee is required
• Commercial user  fee
• Non commercial user:
– Use for scientific research, resulting in a publication
 no fee
– Internal (clinical) use, benchmarking, routine outcome
measurement etc.  modest fee
Future directions
Jan Busschbach
Chair of the Board of the EuroQol Research Foundation
Erasmus Medical Center, Rotterdam
Routine Outcome Monitoring: ROM
Individual feedback
Management information
Benchmarking
Many names
• UK
– The PROMs initiative
• USA
– International Consortium
for Health Outcomes
Measurement
– PROMIS
• Netherlands
– Benchmark Mental health
Many different applications
• Part of quality control
– Benchmark
• Can be basis for science
– Effectiveness (big) data: applied in daily practice
• Can be used for clinical feedback
– Individual data interpreted by patient and doctor
The PROMs initiative UK
• NHS
• > 100.000 patients/year
PROMs: benchmarking
Hip replacement: variations in ∆ QALYs
Appleby et al. Using patient-reported outcome measures to estimate cost-effectiveness of hip
replacements in English hospitals. Journal of the Royal Society of Medicine 2013;106(8):323-31
Ordered hospitals
137
133
129
125
121
117
113
109
105
101
97
93
89
85
81
77
73
69
65
61
57
53
49
45
41
37
33
29
25
21
17
13
9
5
1
Cost/QALY (£000)
NHS hospitals: Cost per QALY
9
8
7
6
5
4
3
2
1
0
Daily reports EQ-VAS in multiple sclerosis
Parkin et al. Use of a VAS in a daily patient diary. Soc Sci Med 2004;59:351-360.
ROM brings EuroQol back to its roots
• EQ-5D developed in the late ’80
– Many different (national) QoL questionnaires existed
– Make data comparable: “benchmark”
– Should have low administrative burden
• “The EuroQol Common Core Questionnaire”
– “The raison d’être of the EuroQol Instrument is to provide a simple
“abstracting” device, for use alongside other more detailed
measures of […HRQoL], to serve as a basis for comparing health
care outcomes using a basic “common core” of QoL characteristics
which most people are known to value highly.”
– Alan Williams
Improving the interface
• In ROM the interface becomes more important
• EuroQol ‘App’ technology
Walking
No problems
Slight problems
Moderate
Severe
Unable to walk
Further development of the youth version
• There is a youth version: The EQ-5D-Y
• Whose values to be used?
– Values from the children themselves
– Values from the parents
– Values from the general public
• Expect:
– Fundamental research
– Policy papers
Fundamental research: other than QALY
values
• Values for applications without QALY aspirations
– Germany (IQWiG)
– USA
• Next to TTO as used in QALY-analysis:
– Item Response Modeling (Rasch)
– Discrete Choice Modeling
– VAS
Fundamental research: increasing
sensitivity
• Experiments to ‘bolt-on’ an additional dimension
– Moving into diseases-specific measures
• Changing the wording of the descriptive system
• Is it an improvement?
– Backwards-compatibility is the rule in the Group
– Test versus standard EQ-5D
Value sets for EQ-5D-5L
• Many ongoing studies use the protocol and EQ-VT
• Opportunity for international comparisons
• Also possible to examine other research questions by
adding to protocol
• Opportunity to engage in EuroQol Group meetings
References for EQ-5D-5L studies
•
•
•
•
•
•
•
•
•
•
•
•
Janssen MF, Pickard AS, Golicki D, et al. Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight
patient groups: a multi-country study. Qual Life Res. 2013;22(7):1717-1727.
Kim T, Jo M-W, Lee S-i, Kim S, Chung S. Psychometric properties of the EQ-5D-5L in the general population of South Korea.
Qual Life Res. 2013;22(8):2245-2253.
Hinz A, Kohlmann T, Stöbel-Richter Y, Zenger M, Brähler E. The quality of life questionnaire EQ-5D-5L: psychometric properties
and normative values for the general German population. Qual Life Res. 2014;23(2):443-447.
Agborsangaya CB, Lahtinen M, Cooke T, Johnson JA. Comparing the EQ-5D 3L and 5L: measurement properties and
association with chronic conditions and multimorbidity in the general population. Health Qual Life Outcomes. 2014;12:74.
Scalone L, Ciampichini R, Fagiuoli S, et al. Comparing the performance of the standard EQ-5D 3L with the new version EQ-5D 5L
in patients with chronic hepatic diseases. Qual Life Res. 2013;22(7):1707-1716.
Golicki D, Niewada M, Buczek J, et al. Validity of EQ-5D-5L in stroke. Qual Life Res. 2014:1-6.
Kim S, Kim H, Lee S-i, Jo M-W. Comparing the psychometric properties of the EQ-5D-3L and EQ-5D-5L in cancer patients in
Korea. Qual Life Res. 2012;21(6):1065-1073.
Tran B, Ohinmaa A, Nguyen L. Quality of life profile and psychometric properties of the EQ-5D-5L in HIV/AIDS patients. Health
and Quality of Life Outcomes. 2012;10(1):132.
Conner-Spady BL, Marshall DA, Bohm E, et al. Reliability and validity of the EQ-5D-5L compared to the EQ-5D-3L in patients with
osteoarthritis referred for hip and knee replacement. Qual Life Res. 2015.
Golicki D, Niewada M, Karlińska A, Buczek J, Kobayashi A, Janssen MF, Pickard AS. Comparing responsiveness of the EQ-5D5L, EQ-5D-3L and EQ VAS in stroke patients. Qual Life Res. 2014 Nov 26. [Epub ahead of print] PubMed PMID: 25425288.
Jia YX, Cui FQ, Li L, Zhang DL, Zhang GM, Wang FZ, Gong XH, Zheng H, Wu ZH, Miao N, Sun XJ, Zhang L, Lv JJ, Yang F.
Comparison between the EQ-5D-5L and the EQ-5D-3L in patients with hepatitis B. Qual Life Res. 2014 Oct;23(8):2355-63.
Lee CF, Luo N, Ng R, Wong NS, Yap YS, Lo SK, Chia WK, Yee A, Krishna L, Wong C, Goh C, Cheung YB. Comparison of the
measurement properties between a short and generic instrument, the 5-level EuroQoL Group's 5-dimension (EQ-5D-5L)
questionnaire, and a longer and disease-specific instrument, the Functional Assessment of Cancer Therapy-Breast (FACT-B), in
Asian breast cancer patients. Qual Life Res. 2013 Sep;22(7):1745-51. doi: 10.1007/s11136-012-0291-7. Epub 2012 Oct 11.
PubMed PMID: 23054499.
Acknowledgements
• Bernhard Slaap,
Executive Director,
EuroQol Research Foundation
• Mandy van Reenen,
Communication Officer
EuroQol Research Foundation
EuroQol Research Foundation, Booth #1108
www.euroqol.org;
email: userinformationservice@euroqol.org
Questions?