Best-Worst Scaling (BWS) survey of barriers and facilitators of the uptake of Health Technology Assessment (HTA) in Austria and Europe
Date: 2017
Collaborator(s): Department of Health Services Research, Maastricht University, NL
Information: Susanne Mayer, Judit Simon, Chiara Feig, Kei Long Cheung
Health Technology Assessment (HTA) is increasingly used to support evidence-based decision-making in health care internationally. This empirical study aimed at collecting data on the relative importance of selected barriers and facilitators of the uptake of HTA studies in Austria and Europe by surveying relevant national stakeholders. Best-worst scaling modelling technique was applied in the analysis. Research was done in collaboration with Maastricht University as part of a visiting MSc research stay.
Furthermore, 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 aimed 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. Research was done in collaboration with Maastricht University as part of visiting PhD research stay.
Result(s):
- Wranik DW, Szekely RR, Mayer S, Hiligsmann M, Cheung KL. The most important facilitators and barriers to the use of Health Technology Assessment in Canada: A best-worst scaling approach. J Med Econ. 2021 Jan-Dec;24(1):846-856. DOI: 10.1080/13696998.2021.194632
- Feig C, Cheung KL, Hiligsmann M, Evers S, Simon J, Mayer S (2018): Best-worst scaling to assess the most important barriers and facilitators for the use of Health Technology Assessment in Austria. Expert Review of Pharmacoeconomics & Outcomes Research. 18(2), 223-232.
- Cheung KL, Mayer S, Simon J, de Vries H, Evers S, Kremer I, Hiligsmann M (2018): Comparison of statistical analysis methods for object case best-worst scaling. Journal of Medical Economics. doi.org/10.1080/13696998.2018.1553781.
- Cheung KL, Evers S, de Vries H, Levy P, Pokhrel S, Jones T, Danner M, Wentlandt J, Knufinke L, Mayer S, Hiligsmann M (2018): Most important barriers and facilitators of HTA usage in decision-making in Europe. Expert Review of Pharmacoeconomics & Outcomes Research, 8(3), 297-304, DOI:10.1080/14737167.2018.1421459.