NEWS

Choice modeling for healthcare: methodological issues in best-worst scaling and discrete choice experiments

University of Twente

August 14th

Place: building Ravelijn, room RA 1501 (first floor/Atrium)

13.00 – 13.25

Coffee / Tea

13.25 – 13.30

INTRODUCTION

Karin Groothuis-Oudshoorn, University of Twente

13.30 – 14.00

COMPARISON OF THE VALUATION OF TREATMENT ALTERNATIVES IN PARKINSON'S DISEASE WITH BEST-WORST SCALING, TIME TRADE-OFF AND VISUAL ANALOGUE SCALES
Marieke Weernink, University of Twente

14.00 – 14.30

CALIBRATING THE POSITION OF ‘DEAD’ AMONG HEALTH STATUS IN THE CHOICE MODELLING FRAMEWORK

Sander Arons, Arons Consultancy

14.30 – 15.00

Coffee / Tea

15.00 – 15.30

PRESENTING DCE CHOICE TASKS: ISSUES THAT CALL FOR ATTENTION

Jorien Veldwijk, RIVM

15.30 – 16.00

AUGMENTING BEST-WORST SCALING ATTITUDINAL DATA WITH RESPONSE TIME DATA - IDENTIFYING 'FAST' AND 'SLOW' DECISION MAKING TO AID ELICITATION OF ADVANCE CARE PLANS

Terry Flynn, University of Western Sydney

16.00 – 17.00

Drinks

For further questions please send an email to Karin Groothuis-Oudshoorn (c.g.m.oudshoorn@utwente.nl). Although registration for the meeting is not necessary, please confirm your participation by email, so we can get an idea how many people will attend.

Abstracts

COMPARISON OF THE VALUATION OF TREATMENT ALTERNATIVES IN PARKINSON'S DISEASE WITH BEST-WORST SCALING, TIME TRADE-OFF AND VISUAL ANALOGUE SCALES

Marieke Weernink, University of Twente

Standard utility assessment techniques (time trade-off, visual analogue scales) are limited in their ability to measure influence of multiple characteristics of drug use on the value of drugs. Best-Worst Scaling, a relative new preference elicitation technique, has the same ability as discrete choice experiments to measure relative value of multiple aspects of care but allows for more efficient data collection. This study objective was to compare the ability of BWS to differentiate between different treatment alternatives to that of TTO and VAS.

PRESENTING DCE CHOICE TASKS: ISSUES THAT CALL FOR ATTENTION

Jorien Veldwijk, RIVM

For every DCE that is conducted researchers have to make decisions concerning various choice task presentation options. They can partly rely on guidelines that describe in detail how attributes and levels should be selected, and how choice tasks should be designed in order to measure preferences as accurate (and efficient) as possible. However, these guidelines do not include detailed descriptions on how to present choice tasks to participants. Will we include an opt-out option? How will we depict our attribute levels? Will we use a positive or a negative frame to describe our attribute levels? Until now, there is very limited empirical evidence concerning the effects of such presentation decisions on the outcomes of the DCE that is conducted, while from social sciences it is known that human behavior (among which decision behavior) is influenced to a large extent based on how information is presented. To ensure the validity of the outcomes of DCEs, the effects of choice task presentation decisions should be unraveled.

CALIBRATING THE POSITION OF ‘DEAD’ AMONG HEALTH STATUS IN THE CHOICE MODELLING FRAMEWORK

Sander Arons, Arons Consultancy

The scientific community is devoting more attention to ordinal choice task as a means to obtain data that can be used to model health-state values. Such values are often used for the estimation of quality-adjusted life years. Most health-state values derived from ordinal response tasks use the assumptions of random utility theory (RUT) to shape the model used to estimate them. However, some models violate the assumptions underlying RUT, especially with regards to the health state 'dead' which causes problems with correctly anchoring the health-state continuum on the dead-full health range. Our objective is to introduce a novel 'dead'-calibration method and investigate its theoretical en empirical advantages and limitations.

AUGMENTING BEST-WORST SCALING ATTITUDINAL DATA WITH RESPONSE TIME DATA - IDENTIFYING 'FAST' AND 'SLOW' DECISION MAKING TO AID ELICITATION OF ADVANCE CARE PLANS

Terry Flynn, University of Western Sydney

Case 1 Best-worst scaling (BWS) is increasingly used outside health to quantify attitudes but health researchers largely seem unaware of this use. Results of a large study to quantify attitudes towards end of life care and segmentation results will be presented. The effects of supplementing these data with response time data seemed to allow better differentiation of “fast, gut” responses such as “all life is sacred” from "slow, considered" responses of the types hypothesised by Daniel Kahneman. This ground-breaking work offers enormous potential to replace more complex discrete choice experiments that many people find too confronting.