Most important barriers and facilitators of HTA usage in decision-making in Europe

ABSTRACT

Background: To enhance usage of health technology assessment (HTA) in decision-making, it is important to prioritise important barriers and facilitators to the uptake of HTA. This study aims to quantify and compare the relative importance of barriers and facilitators regarding the use of HTA in several European countries.

Methods: A survey containing two best-worst scaling (BWS) object case studies (i.e. barriers and facilitators) were conducted among 136 policy makers and HTA researchers from the Netherlands, Germany, France, and United Kingdom. Hierarchical Bayes analysis generated the mean relative importance score (RIS) for each factor and subgroup analyses assessed differences between countries.

Results: Six barriers (RIS≥5) and five facilitators (RIS≥6) were deemed highly important. Eleven barriers and ten facilitators differed in their importance between countries. Policy characteristics, research & researcher characteristics, and organisation & resources were particularly important to facilitate uptake of HTA, such as an explicit framework for decision-making and research of sufficient quality.

Conclusion: The most paramount barriers and facilitators to HTA usage were quantified. For all countries it is crucial to create an explicit framework for the decision-making context to include HTA evidence. Country differences in the quality of research emphasize the need for enhanced international collaboration in HTA.

KEYWORDS:

• Europe
• health technology assessment
• barriers
• facilitators
• best-worst

Acknowledgments

We thank the participants for their input. We are indebted to Manuela Joore and Maria Jansen for their valuable inputs regarding the master lists of barriers and facilitators. The views expressed and any errors in this article are those of the authors and not of the funding agency or the institutions the authors belong to.

Author contribution statement

KLC planned and managed the work, analysed and interpreted results and produced the first draft of the manuscript with support from HDV, SE, MH, and SM. Different versions of the manuscript have been reviewed and conceptualised by all co-authors. Data was collected by KLC (Netherlands), TJ (UK), PL (France), and JW and LK (Germany). KLC produced the final manuscript and is the corresponding author. All authors have read and approved the final manuscript.

Declaration of interest

KL Cheung received financial support for his research stay at the Department of Health Economics, Center for Public Health, Medical University of Vienna through the Erasmus+ staff mobility grant. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

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Funding

This paper was not funded.