PhD defence V.R. (Vikash) Soekhai

On 4 November 2021, V.R. Soekhai will defend his PhD dissertation, entitled: ‘Choice Modelling in Health: Challenges and Opportunities’.
Promotor

Prof.dr. E.W. de Bekker-Grob

Promotor

Prof.dr. B. Donkers

Date
Thursday 4 Nov 2021, 10:30 - 12:00
Type
PhD defence
Space
Senate Hall
Building
Erasmus Building
Location
Campus Woudestein
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On 4 November 2021, V.R. Soekhai will defend his PhD dissertation, entitled: ‘Choice Modelling in Health: Challenges and Opportunities’.

The choice modelling field is concerned with understanding how individuals make choices by quantifying the underlying preferences. More specifically, the aim of choice modelling is to characterize choices individuals make and to predict choices among the choice alternatives considered. Choice modelers assume that choices from individuals are based on preferences determining the amount of satisfaction (utility) they derive from goods and services. In choice modelling, individual’s choices are related to their preferences by focusing on the utilities of choice alternatives. Choice modelling (i.e., specifically discrete choice experiments) was introduced in health in the early 1990s, especially to capture outcomes beyond health for health benefit assessments. Before the introduction of choice modelling in health, methods from other fields were used to gain insights into health preferences. Since choice modelling provided a new way to gain insights into health preferences the application of choice modelling in health continued to grow after the 1990s, especially with regard to stated-preferences. There are several stated-preference methods to gain insights into health preferences, but discrete choice experiments (DCE) are increasingly advocated. A DCE is a survey-based preference elicitation method in which individuals are asked to select their preferred alternative from a set of alternatives. DCE data analysis has its origin in mathematical psychology, with wide applications in marketing, transport and environmental economics and its theoretical foundation in random utility theory (RUT). Best-worst scaling (BWS) is another statedpreference method that has become an increasingly popular method to elicit health preferences. The introduction of BWS came from the intent to obtain more preference information than from a DCE by asking individuals to select their “best” and “worst” option, without increasing the cognitive burden. There are several types of BWS, but case 2 BWS (BWS-2) received much attention in the literature since this method can uncover attribute level importance, reduce cognitive burden of the choice task by focusing on one profile at a time and experiments are relatively easy to design. More detailed information about these methods can be found in chapter 1 of this dissertation. DCE and BWS-2 gained popularity in health to elicit preferences, although there are several methodological challenges to overcome inhibiting these methods to become more valuable for actual decision-making. Therefore, gaining insights into methodological challenges and providing opportunities to overcome them, contributes to academic literature as well as practice to inform decision-making. This dissertation has three main objectives (chapter 1):

1. Providing insights into preference methods used in health

2. Providing insights into DCE and BWS-2 challenges and opportunities regarding design and analysis

3. Empirically comparing outcomes between DCE and BWS-2

The public defence will take place at the Senate Hall, 1st floor Erasmus Building, location campus Woudestein. The ceremony will begin exactly at 10.30 AM. In light of the solemn nature of the ceremony, we recommend that you do not take children under the age of 6 to the first part of the ceremony.

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