Directly eliciting personal utility functions: a new way to value health-related quality of life

(Poster PRM156)

Koonal Shah, Nancy Devlin (Office of Health Economics, UK) Brendan Mulhern (CHERE, University of Technology Sydney, Australia)

Ben van Hout (ScHARR, University of Sheffield, UK) For further information, contact kshah@ohe.org

BACKGROUND

• The end product of EQ-5D valuation studies is an algorithm describing, on average, the utility decrements associated with each dimension and level of problems within the EQ-5D descriptive system

• Standard methods for eliciting health state preference data (e.g. TTO, DCE) vary considerably in approach, but have in common an aim to ‘uncover’ these preferences by asking survey respondents to evaluate a sub-set of health states, and then using their responses to infer the relative importance of the specific dimensions and levels to them

• An alternative (and novel) approach is to directly ask respondents about their own personal utility functions • Instead of inferring respondents’ utility functions from their responses to abstract choice tasks, we propose directly

asking people about the relative importance of the health dimensions and levels, and the interactions between them

This study was funded by the EuroQol Research Foundation. The views expressed do not necessarily reflect the views of the EuroQol Research Foundation.

METHOD / KEY INNOVATIONS

• Paper- and computer-based tasks administered via F2F interviews • Focus is on reflection and open discussion of responses • Based on premise that respondents are constructing their preferences • Some elements draw on swing weighting approach (MCDA literature)

A. WARM-UP TASKS

• Self-reported health using EQ-5D and EQ-VAS • Ranking exercise: ranking of level-free

descriptions of the five EQ-5D dimensions

B. DIMENSION WEIGHTING TASK

• Five cards: each describes an improvement from extreme problems to no problems in one of the EQ-5D dimensions • 0 to 100 scale: 100 refers to the most important improvement in health and 0 refers to an improvement that respondent

does not feel is important or valuable at all • Respondent assigns a rating of 100 to the improvement (card) that is most important or valuable to them • Respondent then rates the other improvements using the same scale and in relation to the most important improvement • Responses generate a set of dimension weights, which will be presented diagrammatically to respondents (Fig 1)

C. LEVEL WEIGHTING TASK

• Three cards (for each dimension): no improvement (from extreme problems); intermediate improvement (from extreme problems to moderate problems) and largest possible improvement (from extreme problems to no problems)

• 0 to 100 scale: 100 refers to the largest possible improvement and 0 refer to no improvement • Respondent rates the intermediate improvement using the 0 to 100 scale • Rating of 50 implies that respondent considers the improvement from extreme problems to moderate problems to be

about as important as the improvement from moderate problems to no problems – may not always be the case • Responses generate a set of level weights, which will be combined with the dimension weights and presented

diagrammatically to respondents (Fig 2) – opportunity for respondents to reflect and amend their answers

D. VALIDATION EXERCISE

• The information collected in C and D will be validated using a series of pairwise choice tasks • Purpose of the exercise is to validate our understanding of the responses and to identify any potential inconsistencies

E. POSITIONING OF DEAD

• Position of dead will be estimated by asking respondents to complete simple trade-off tasks where the unit of trade is dimension-specific levels (as opposed to time or risk, as in TTO and standard gamble, respectively)

• Example: start with following pairwise choice: (X) 11113 for 10 years followed by death vs. (Y) ‘die immediately’ • If respondent prefers X, then X is worsened: (X) 31113 for 10 years followed by death vs. (Y) ‘die immediately’ • Continue until respondent switches to preferring Y, at which point the approximate location of dead can be identified • Exact selection of health states presented in option X will follow directly from responses to dimension weighting task

Fig 1. Output from B

Fig 2. Output from B & C

Diagrams will be used to check whether

respondents agree with our interpretation of their

responses; changes to earlier answers permitted

F. EXAMINATION OF INTERACTIONS

• Systematic approach will be used to examine interactions

G. DEBRIEFING

• Views about feasibility of the approach and suggestions for improving questionnaire will be sought from both respondents and interviewers

CURRENT STATUS

• Draft questionnaire has been developed • Accompanying computer-based tool is in development • Pilot interviews to be conducted in Q2 2015 using

convenience samples in Australia, Netherlands, UK • Revised questionnaire will be tested in Q3/Q4 2015