What works better for preference elicitation among older people? Cognitive burden of discrete choice experiment and case 2 best-worst scaling in an online setting

To appropriately weight dimensions of quality of life instruments for health economic evaluations, population and patient preferences need to be elicited. Two commonly used elicitation methods for this purpose are discrete choice experiments (DCE) and case 2 best-worst scaling (BWS). These methods differ in terms of their cognitive burden, which is especially relevant when eliciting preferences among older people. Using a randomised experiment with respondents from an online panel, this paper examines the cognitive burden associated with colour-coded and level overlapped DCE, colour-coded BWS, and ‘standard’ BWS choice tasks in a complex health state valuation setting. Our sample included 469 individuals aged 65 and above. Based on both revealed and stated cognitive burden, we found that the DCE tasks were less cognitively burdensome than case 2 BWS. Colour coding case 2 BWS cannot be recommended as its effect on cognitive burden was less clear and the colour coding lead to undesired choice heuristics. Our results have implications for future health state valuations of complex quality of life instruments and at least serve as an example of assessing cognitive burden associated with different types of choice experiments

Methods for exploring and eliciting patient preferences in the medical product lifecycle: a literature review.

Objectives: Patient preference information (PPI) is gaining recognition among the pharmaceutical industry, regulatory authorities, and health technology assessment (HTA) bodies/payers for use in assessments and decision-making along the medical product lifecycle (MPLC). This study

Case 2 best-worst scaling: For good or for bad but not for both

This paper studies the performance of case 2 best-worst scaling (BWS) when it is applied to a mix of positive and negative attributes, for example in studying treatments characterized by both benefits and harms. Intuitively, such a mix of positive and negative attributes leads to dominance. We analytically show that dominance leads to infinitely large differences between the parameter estimates for the positive versus negative attributes. The results from a simulation study confirm our analytical results: parameter values of the attributes could not be accurately recovered. When only a single positive attribute was used, even the relative ordering of the attribute level preferences was not identified. As a result, case 2 BWS can be used to elicit preferences if only good (positive) or only bad (negative) attributes are included in the choice tasks, but not for both since dominance will impact parameter estimation and therefore decision-making

Neuropsychiatrische verschijnselen bij patiënten met COVID-19 op de ic

Het is duidelijk geworden dat COVID-19 kan leiden tot neuropsychiatrische complicaties. In dit artikel beschrijven wij drie casussen die illustreren hoe dergelijke complicaties zich kunnen manifesteren binnen het COVID-19-ziekteverloop. Patiënten lopen het risico op een ernstig, hyperactief delier, dat vaak gepaard gaat met angst en soms met neurologische symptomen. Bij de behandeling van de neuropsychiatrische complicaties zijn ongebruikelijk hoge doses antipsychotica en sedativa nodig. Wij adviseren tijdige psychiatrische consultatie voor adequate herkenning en effectieve behandeling van delier en andere neuropsychiatrische symptomen

Methods for exploring and eliciting patient preferences in the medical product lifecycle: a literature review

Objectives: Patient preference information (PPI) is gaining recognition among the pharmaceutical industry, regulatory authorities, and health technology assessment (HTA) bodies/payers for use in assessments and decision-making along the medical product lifecycle (MPLC). This study