Health Technology Assessment (HTA) is increasingly used to support evidence-based decision-making in health care internationally. This empirical study aims at collecting data on the relative importance of selected barriers and facilitators of the uptake of HTA studies in Austria by surveying relevant national stakeholders. Best-worst scaling modelling technique will be applied in the analysis.
Different methods are used in practice to analyse Best-Worst Scaling (BWS) data in health services research and yet, it is unknown to what extent the different methods yield different conclusions. Hence, to deepen the understanding of conducting and interpreting BWS studies, this study aims to empirically test the comparability of different methods of analysis (i.e. count analysis; multinomial logit, mixed logit and rank-ordered logistic regression models; latent class analysis; Hierarchical Bayes estimation), using data from a BWS that quantifies the importance of barriers and facilitators to the usage of HTA in several European countries.
Dates: 2017
Collaborator(s):
Department of Health Services Research, Maastricht University, NL
Information:
Susanne Mayer, Judit Simon, Chiara Feig, Kei Long Cheung
Publication(s):