An EQ-5D-5L Value Set for England- Nancy Devlin and Ben Van Hout

Nancy Devlin & Ben van Houton behalf of the OHE & ScHARR research team

OHE seminarLondon • October 30th 2014

An EQ-5D-5L value set for England


October 30th 2014

This report is independent research commissioned and funded by the NIHR/ Department of Health Policy Research Programme (‘EQ-5D-5L Value Set for England’ - 070/0073). The views expressed in this publication are those of the author(s) and not necessarily those of the Department of Health.

Additional data have been used from the PRET study, funded by the MRC-NIHR Research Methodology Programme, and the PRET-AS study, funded by the EuroQol Group.

Views expressed in the paper are those of the authors, and not the funding bodies.

Disclaimer


October 30th 2014

Content

1. Background

2. Aims

3. Study design

4. Data

5. Modelling

6. Key results and implications

7. Remaining research questions


October 30th 2014

Background

• EQ-5D-5L: 3,125 states cf. 243 in the EQ-5D

• Requests for 5L use now supersedes 3L: an important instrument

• Interim utilities available by mapping 5L states to 3L states, and using existing 3L value sets

• But ultimately, ‘bespoke’ value sets required for 5L states

• Values are generally required to be based on preferences of the general public (e.g. NICE 2013)

• Using ‘stated preferences’ research methods


October 30th 2014

3L 5L Would we expect underlying values to be the same?

11111 11111 Yes

33333 55555 Not necessarily –mobility ‘extreme’ vs. ‘confined to bed’

22222 33333 Not necessarily –‘some’ vs. ‘moderate’


October 30th 2014

Aims

Aim: To produce a set of values for the EQ-5D-5L health state descriptive system, based on the preferences of the general public in England, for use in decisions based on EQ-5D-5L data

We investigated the following questions:

• What is the best method to generate an EQ-5D-5L Value Set which reflects the stated preferences of the English general public?

• How can conceptually different types of preference data – Time Trade Off (TTO) and Discrete Choice Experiment (DCE) – be combined in modelling health state values?

• How are extreme negative opinions about health states best handled?

• How do people differ in their stated preferences for quality of life; and life and death?


October 30th 2014

Study design

• Research protocol developed by the EuroQol Group: EQ-VT

• 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 participant 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 Group’s Valuation Technology software (EQ-VT) was used to present the tasks and to capture participants’ responses


October 30th 2014


October 30th 2014

TTO for values > 0 (states better than dead)

Example shown:U(Hi) = 0.5

U(Hi) = (x/t)where t = 10 years


October 30th 2014

Example shown:U(Hi) = -0.5

Where t = 10 years, and lead time = 10 years,U(Hi) = (x-10)/20-10) and min value = -1

TTO for values < 0 (states worse than dead)


October 30th 2014

DCE task


October 30th 2014

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

• In modelling, we also incorporated DCE data from a methodological study (‘PRET’)


October 30th 2014

DCE data

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

-10 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9

Misery index of state A minus misery index of state B

Proportions choosing A and B based on relative severities of A and B

% B

% A

0 1

-10

-50

51

0

delta sum of scores

dif in

mis

ery


October 30th 2014

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


October 30th 2014

1 3 4 5 6 7 8

-0.1

0-0

.05

0.0

0

misery coefficient

group

TTO groups

group N

all at 1 18

0<all<1 217

-1<all<1 113

-1=<all<1 53

0<all<=1 194

-1<all<=1 55

-1=<all<=1 52


October 30th 2014

11121 mean= 0.876

value

density

-1.0 0.0 0.5 1.00

20

40

12111 mean= 0.868

value

density

-1.0 0.0 0.5 1.0

020

40

11211 mean= 0.866

value

density

-1.0 0.0 0.5 1.0

020

40

11221 mean= 0.862

value

density

-1.0 0.0 0.5 1.0

010

20

21111 mean= 0.83

value

density

-1.0 0.0 0.5 1.00

20

40

12121 mean= 0.823

value

density

-1.0 0.0 0.5 1.0

05

15

11112 mean= 0.815

value

density

-1.0 0.0 0.5 1.0

020

40

11122 mean= 0.806

value

density

-1.0 0.0 0.5 1.0

05

15

11212 mean= 0.801

value

density

-1.0 0.0 0.5 1.00

515

Distributions, by state


October 30th 2014

54231 mean= 0.473

value

density

-1.0 0.0 0.5 1.00

48

12

33253 mean= 0.465

value

density

-1.0 0.0 0.5 1.0

05

15

12334 mean= 0.463

value

density

-1.0 0.0 0.5 1.0

04

8

23514 mean= 0.46

value

density

-1.0 0.0 0.5 1.0

04

812

43514 mean= 0.443

value

density

-1.0 0.0 0.5 1.00

48

15151 mean= 0.436

value

density

-1.0 0.0 0.5 1.0

05

10

15

23152 mean= 0.435

value

density

-1.0 0.0 0.5 1.0

05

15

31525 mean= 0.428

value

density

-1.0 0.0 0.5 1.0

05

10

31524 mean= 0.423

value

density

-1.0 0.0 0.5 1.00

24

68



October 30th 2014

21444 mean= 0.148

value

density

-1.0 -0.5 0.0 0.5 1.0

010

20

53244 mean= 0.148

value

density

-1.0 -0.5 0.0 0.5 1.0

05

15

52455 mean= 0.12

value

density

-1.0 -0.5 0.0 0.5 1.0

05

10

43555 mean= 0.119

value

density

-1.0 -0.5 0.0 0.5 1.0

05

10

15

55555 mean= 0.016

value

density

-1.0 -0.5 0.0 0.5 1.0

0100

NA mean= NA

value

density

-1.0 -0.5 0.0 0.5 1.0

-1.0

0.0

1.0



October 30th 2014

minimum value

minv

Fre

quency

-1.0 -0.5 0.0 0.5 1.0

050

100

150

maximum value

maxv

Fre

quency

0.0 0.2 0.4 0.6 0.8 1.0

0200

400

standard deviation of values

(varv̂ 0.5)

Fre

quency

0.0 0.2 0.4 0.6 0.8 1.0

050

100

150

range of values used

range

Fre

quency

0.0 0.5 1.0 1.5 2.0

050

100

150

Descriptive statistics


October 30th 2014

• Overall, English 5L valuation data have acceptable ‘face validity’: the worse the health state, the lower the mean and median value

Face validity of the data


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Interpretation of the data

• Evidence from this study suggests that it is harder to imagine, differentiate between, and value health states described in terms of 5L rather than 3L

• More subtle differences between states

• Cognitive burden

• Initial model results suggested respondents did not differentiate between ‘severe’ (level 4) and ‘extreme’ (level 5) problems on the dimension anxiety/depression


October 30th 2014

• 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

Interpretation of the data


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Examination of individual-level data


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Real or censored???


October 30th 2014

Interviewer effects

InterviewerCompleted interviews

Exhaust lead time (value = -1)

State worse than dead (value < 0)

State equal to dead (value = 0)

Non-trade(value = 1)

UK15354 33 6% 14% 15% 15%UK12790 30 1% 5% 22% 3%UK05524 29 0% 1% 6% 8%UK03958 28 3% 10% 25% 10%UK04526 28 1% 16% 8% 2%UK04512 26 6% 20% 10% 3%UK13185 25 0% 3% 24% 8%UK14661 25 4% 12% 14% 36%UK04523 24 2% 10% 9% 20%UK02515 22 1% 7% 6% 5%UK15247 20 5% 12% 27% 13%UK12648 19 5% 14% 17% 27%UK15835 19 12% 19% 2% 42%UK02957 18 3% 6% 12% 2%UK03921 16 0% 0% 4% 20%UK04405 16 13% 33% 13% 4%UK06347 16 6% 11% 27% 19%UK12499 16 0% 2% 6% 17%UK04587 15 2% 5% 7% 13%


October 30th 2014

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


October 30th 2014

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 the these

• Heterogeneity explored via random coefficient models, which estimate value functions for every individual member of the sample

• Values at -1 treated as censored


October 30th 2014

The hybrid likelihood

General

• You have a statistical model that generates the data, holding unknown parameters

• You have the data

• You calculate for every set of parameters the probability that the data occur

• The likelihood is the product of all probabilities

• You calculate the parameters at which this product of probabilities (likelihood) is highest

Specific

• There is a likelihood for the DCE-data

– Assuming normal errors

• There is a likelihood for the TTO-data

– Assuming normal errors

• The combined likelihood is the product of both likelihoods


October 30th 2014

Initial model results, DCE only

mobility 0.337 (0.306 - 0.369) 1.574 (0.884 - 2.334) 0.278 (0.185 - 0.398) slight 0.349 (0.235 - 0.460)

self-care 0.241 (0.214 - 0.268) 1.222 (0.689 - 1.805) 0.217 (0.144 - 0.315) moderate 0.441 (0.310 - 0.577)

usual activities 0.203 (0.175 - 0.232) 0.994 (0.555 - 1.474) 0.176 (0.117 - 0.257) severe 1.132 (1.002 - 1.269)

pain/discomfort 0.406 (0.377 - 0.436) 1.793 (1.017 - 2.655) 0.312 (0.208 - 0.446) unable 1.441 (1.298 - 1.590)

anxiety/depression 0.394 (0.364 - 0.424) 1.777 (1.002 - 2.619) 0.309 (0.205 - 0.442) slight 0.268 (0.145 - 0.388)

slight 0.214 (0.132 - 0.358) 1.187 (0.758 - 1.753) moderate 0.406 (0.272 - 0.541)

moderate 0.256 (0.159 - 0.426) 1.425 (0.929 - 2.106) severe 1.007 (0.874 - 1.145)

severe 0.788 (0.503 - 1.294) 4.385 (2.961 - 6.234) unable 1.049 (0.920 - 1.180)

unable/extreme 0.912 (0.583 - 1.496) 5.006 (3.357 - 7.127) slight 0.213 (0.102 - 0.326)

extreme 5.134 (3.450 - 7.351) moderate 0.216 (0.096 - 0.335)

severe 0.796 (0.672 - 0.923)

unable 0.816 (0.689 - 0.949)

slight 0.328 (0.212 - 0.446)

moderate 0.376 (0.248 - 0.499)

severe 1.198 (1.065 - 1.331)

extreme 1.587 (1.449 - 1.731)

slight 0.331 (0.205 - 0.454)

moderate 0.376 (0.252 - 0.506)

severe 1.355 (1.220 - 1.494)

extreme 1.470 (1.329 - 1.611)

Deviance 7750 (7745 - 7757) 7516 (7510 - 7525) 7516 (7510 - 7527) Deviance 7502 (7492 - 7516)

DIC 7755 7517 7523 DIC 7522

5 parameters 9 parameters 10 parameters 20 parameters

self-care

usual activities

pain/discomfort

anxiety/

depression

mobility


October 30th 2014

Initial model results, TTO only

• DIC lowest for 10-parameter model• Unexpected coefficient for level 5 on anxiety/depression

constant 1.109 (1.086 - 1.131) 0.874 (0.858 - 0.889) 0.884 (0.870 - 0.899) constant 0.832 (0.816 - 0.837)

mobility 0.037 (0.030 - 0.045) 0.266 (0.215 - 0.323) 0.209 (0.176 - 0.257) slight -0.021 -(0.039 - -0.015)

self-care 0.035 (0.028 - 0.042) 0.273 (0.222 - 0.337) 0.208 (0.175 - 0.255) moderate 0.008 -(0.018 - 0.017)

usual activities 0.040 (0.033 - 0.048) 0.252 (0.208 - 0.308) 0.194 (0.162 - 0.241) severe 0.141 (0.108 - 0.153)

pain/discomfort 0.072 (0.063 - 0.081) 0.401 (0.334 - 0.485) 0.323 (0.275 - 0.392) unable 0.210 (0.175 - 0.221)

anxiety/depression 0.057 (0.049 - 0.065) 0.312 (0.253 - 0.382) 0.261 (0.223 - 0.317) slight -0.005 -(0.027 - 0.002)

slight 0.111 (0.080 - 0.150) 0.159 (0.120 - 0.202) moderate 0.031 (0.003 - 0.041)

moderate 0.225 (0.175 - 0.279) 0.282 (0.221 - 0.344) severe 0.102 (0.068 - 0.114)

severe 0.644 (0.539 - 0.756) 0.838 (0.678 - 0.953) unable 0.196 (0.166 - 0.207)

unable/extreme 0.802 (0.670 - 0.935) 1.094 (0.901 - 1.258) slight 0.000 -(0.019 - 0.007)

extreme 0.981 (0.789 - 1.125) moderate 0.020 -(0.006 - 0.029)

severe 0.123 (0.093 - 0.134)

unable 0.158 (0.124 - 0.170)

slight -0.004 -(0.022 - 0.002)

moderate 0.047 (0.022 - 0.056)

severe 0.269 (0.233 - 0.282)

extreme 0.304 (0.260 - 0.320)

slight 0.016 -(0.003 - 0.022)

moderate 0.060 (0.031 - 0.072)

severe 0.246 (0.211 - 0.259)

extreme 0.235 (0.202 - 0.247)

sigma 1.510 (1.235 - 1.775) 3.074 (2.659 - 3.567) 3.131 (2.664 - 3.650) sigma 0.931 (0.805 - 1.073)

Deviance 3153 (2914 - 3422) -3448 -(3967 - -2970) -4673 -(5200 - -4104) Deviance -11006 -(11860 - -10200)

DIC 4534 -989 -2704 DIC -4951

anxiety/

depression


mobility

self-care

usual activities

pain/discomfort


October 30th 2014

Initial results from the hybrid model

• Before addressing censoring at 1

constant 1.180 (1.150 -1.209) 0.890 (0.863 -0.913) 0.892 (0.866 -0.917) constant 0.881 (0.853 -0.912)

mobility -0.054 -(0.059 --0.050) 0.249 (0.154 -0.333) 0.157 (0.097 -0.271) slight -0.051 -(0.068 --0.035)

self-care -0.038 -(0.043 --0.032) 0.191 (0.117 -0.256) 0.118 (0.073 -0.205) moderate -0.065 -(0.085 --0.047)

usual activities -0.035 -(0.040 --0.029) 0.163 (0.100 -0.222) 0.101 (0.062 -0.175) severe -0.180 -(0.198 --0.162)

pain/discomfort -0.070 -(0.076 --0.065) 0.301 (0.186 -0.399) 0.198 (0.121 -0.338) unable -0.228 -(0.248 --0.210)

anxiety/depression -0.067 -(0.073 --0.063) 0.287 (0.177 -0.382) 0.188 (0.116 -0.326) slight -0.041 -(0.058 --0.025)

slight -0.201 -(0.310 --0.138) -0.323 -(0.504 --0.174) moderate -0.063 -(0.082 --0.045)

moderate -0.267 -(0.407 --0.188) -0.428 -(0.658 --0.234) severe -0.150 -(0.168 --0.131)

severe -0.800 -(1.216 --0.574) -1.276 -(1.932 --0.696) unable -0.169 -(0.187 --0.152)

unable/extreme -0.914 -(1.388 --0.658) -1.522 -(2.308 --0.822) slight -0.038 -(0.054 --0.021)

extreme -1.414 -(2.138 --0.775) moderate -0.039 -(0.058 --0.021)

severe -0.132 -(0.150 --0.114)

unable -0.136 -(0.154 --0.117)

slight -0.050 -(0.067 --0.032)

moderate -0.062 -(0.080 --0.044)

severe -0.206 -(0.225 --0.186)

extreme -0.258 -(0.279 --0.239)

slight -0.057 -(0.075 --0.039)

moderate -0.075 -(0.094 --0.056)

severe -0.230 -(0.252 --0.209)

extreme -0.238 -(0.259 --0.219)

constant DCE 0.023 -(0.077 -0.096) -0.119 -(0.174 --0.063) -0.120 -(0.170 --0.066) constant DCE -0.119 -(0.175 --0.064)

slope DCE 5.535 (4.223 -7.404) -5.936 -(6.325 --5.558) -5.935 -(6.324 --5.542) slope DCE -6.055 -(6.497 --5.632)

Deviance 21241 (21230 -21250) 20934 (20930 -20950) 20932 (20920 -20940) Deviance 17806 (17790 -17820)

DIC 21249 20917 20877 DIC 17830

mobility

self-care

usual activities

pain/discomfort

anxiety/

depression



October 30th 2014

Issues with the TTO results

• Lower parameter for anxiety-depression level 5 than for anxiety/depression level 4

• Brute force

• Heterogeneity

• Latent distributions

• Low value of the intercept

• Error distributions


October 30th 2014

• 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’betafollows a:

– Normal distribution

– Lognomal distribution

– Multinomial distribution

– (3 latent classes)

Heterogeneity

-1.5

-1

-0.5

0

0.5

1

valu

e

x'beta


October 30th 2014

Parameter estimates

-0.0500.0000.0500.1000.1500.2000.2500.3000.350

slope ~ normal

slight moderate severe unable/extreme

-0.1000.0000.1000.2000.3000.4000.5000.600

slope ~ lognormal


-0.5000.0000.5001.0001.5002.0002.5003.0003.500

slope ~ multinomial


-0.0500.0000.0500.1000.1500.2000.2500.300

homogeneous TTO



October 30th 2014

The low value of the constant


October 30th 2014

• Variation is caused by:

• Differences of opinion

• Errors

• You can value at 0.5 or 0, but you can’t value at 1.5 or 2

• If it is errors, and not opinions, which are driving the lower values, the mean may not be the right measure to reflect ‘average’ opinion

• There is error-censoring at 1

Are (have) we (been) doing this correctly?


October 30th 2014

The low value of the constant


October 30th 2014

TTO value by number of moves

-1 -0.95 -0.9 -0.85 -0.8 -0.7 -0.65 -0.6 -0.55 -0.5 -0.5 -0.4 -0.4 -0.3 -0.3 -0.2 -0.2 -0.1 -0.1 0 0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.4 0.5 0.5 0.6 0.6 0.7 0.7 0.8 0.8 0.9 0.9 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 223

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 596 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 222 0 0 0 0 0 0 0 0 0 865 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 123 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 275 0 0 0 279 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 48 0 0 0 14 0 0 0 0 0 0 0 6 0 2 0 0 0 242 0 0 44 0 48 0 0 337 0 0 0 0 0 0

0 0 0 0 0 55 0 0 10 0 5 0 0 8 0 0 0 0 0 0 1 0 0 187 0 0 43 2 0 67 0 5 52 0 0 385 0 0 0 0

0 0 0 0 20 0 5 2 0 7 0 0 6 0 0 17 0 0 0 1 0 89 1 0 20 4 0 33 7 0 6 37 0 17 36 0 0 313 0 0

0 0 30 0 0 1 0 3 1 0 0 3 0 1 2 0 0 11 0 0 71 0 18 7 1 19 4 2 3 28 3 1 5 18 0 16 42 0 457 0

0 71 0 1 0 2 2 0 0 2 0 0 1 0 0 0 2 0 11 45 0 13 0 20 1 1 2 8 5 13 0 7 3 3 5 19 0 40 0 645

305 0 1 0 1 0 0 1 0 0 0 2 0 0 0 2 0 4 0 29 7 7 1 2 0 5 2 1 0 11 0 4 1 7 2 7 2 4 105 0

0 1 0 0 0 1 1 0 0 2 0 0 0 2 0 1 0 0 2 1 3 3 1 0 1 2 0 2 1 5 3 2 1 5 0 3 1 12 2 18

4 0 2 0 0 0 0 1 0 1 0 1 0 0 0 1 0 0 2 6 0 2 1 3 1 3 0 1 1 3 0 3 0 0 0 7 0 4 12 8

2 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 5 0 2 0 0 0 1 1 2 1 2 0 0 0 1 0 0 0 5 6 4

0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 3 1 0 0 0 0 3 0 1 0 0 1 2 0 1 1 1 0 4 3 2

0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 1 1 1 1 1 0 1 0 6 0 2 0 2 0 0 0 0 2 15

0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 2 0 0 1 1 0 0 0 0 4 0

6 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 0 1 0 1 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1 0

0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1

1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 0 2 0 0 0 0 0 2 0 0 1 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1

0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0

1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0


October 30th 2014

The final EQ-5D-5L value set model

EQ-5D-5L value set for England

constant 1.003

Mobility slight 0.057

moderate 0.074

severe 0.207

unable 0.255

Self care slight 0.059

moderate 0.083

severe 0.176

unable 0.208

Usual activities slight 0.048

moderate 0.067

severe 0.165

unable 0.165

Pain/discomfort slight 0.059

moderate 0.079

severe 0.244

extreme 0.298

Anxiety/depression slight 0.072

moderate 0.099

severe 0.282

extreme 0.282


October 30th 2014

EQ-5D-5L value set for England Example: the value for health state 23245

constant 1.000 Constant =1.000

Mobility = 2 0.057 Minus MO level 2 -0.057

Mobility = 3 0.074

Mobility = 4 0.207

Mobility = 5 0.255

Self care = 2 0.059

Self care = 3 0.083 Minus SC level 3 -0.083

Self care = 4 0.176

Self care = 5 0.208

Usual activities = 2 0.048 Minus UA level 2 -0.048

Usual activities = 3 0.067



Pain/discomfort = 2 0.059


Pain/discomfort = 4 0.244 Minus PD level 4 -0.244


Anxiety/depression = 2 0.072



Anxiety/depression = 5 0.282 Minus AD level 5 -0.282

State 23245 =0.286

Calculating values:

a workedexample


October 30th 2014

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

Minimum value -0.208 -0.49 -0.594

Maximum value 1 1 1

Range of values [-0.208, 1] [-0.594, 1] [-0.594, 1]


October 30th 2014

Distributions of values0

.51

1.5

De

nsi

ty

-.5 0 .5 1value

0.5

11.5

2

De

nsity

-.5 0 .5 1value

0.5

11.5

2

De

nsity

-.5 0 .5 1value

3L crosswalk

5L


October 30th 2014

Values and ‘misery scores’-.

50

.51

5 10 15misery

eq5d3l Fitted values

-.5

0.5

1

5 10 15 20 25misery


-.5

0.5

1

5 10 15 20 25misery


3L crosswalk

5L


October 30th 2014

Comparing 3L and 5L data

3L value set 5L value set

% logical

inconsistencies

4.89%

(166 out of 3,395)

8.43%

(84 out of 996)

% who do not give

their lowest value to

the worst health state

29.19%

(991 out of 3,395)

28.92%

(288 out of 996)


October 30th 2014

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


October 30th 2014

Implications of the results

• For two dimensions, anxiety/depression and usual activities, the TTO results did not differentiate between levels 4 and 5

• e.g. interventions that reduce the level of anxiety/depression from extreme to severe will show few QALY gains

• Potential implications for other applications of the value set e.g. in the PROMs programme, where it is used to measure hospital performance


October 30th 2014

Remaining research questions

• This presentation has focussed on the value set for England – we have also collected data for Scotland, Wales and NI, and will be estimating a UK value set

• How do values compare with other countries? Over a dozen 5L value set studies underway internationally, using a consistent methodology

• Many remaining methodological issues…for example,

– the effect of valuation full health vs. 11111 in the TTO

– Describing health states ‘in context’ of the full health state descriptive system

– DCE with duration

– Remodelling the 3L value set with the new methods

An EQ-5D-5L Value Set for England- Nancy Devlin and Ben Van Hout

Healthcare

Transcript of An EQ-5D-5L Value Set for England- Nancy Devlin and Ben Van Hout