MAPPING THE INVOLVEMENT OF EUNETHTA PARTICIPANTS IN EU RESEARCH PROJECTS

Author(s)

Kozák A, Hankó B, Lám J, Merész G
Semmelweis University, Budapest, Hungary

OBJECTIVES:

The 10-year anniversary of the first EUnetHTA project initiation offers a suitable occasion to evaluate the accumulated experience of participating entities through EU research projects. This research aims to describe the involvement of former EUnetHTA participants in research projects under Framework Programme 7 (FP7) and Horizon 2020 (H2020) funding programmes of the European Union. METHODS: An algorithm was created in R to carry out the data collection and analysis. FP7 and H2020 projects involving former EUnetHTA partner institutes were identified from the CORDIS datasets. Data was collected on major project characteristics, such as title, initiation date, description, participating members, and funding. Descriptive analysis techniques, such as network layouts and word clouds were used to provide an overview of the collected data. RESULTS: A total number of 31 institutes were identified as former EUnetHTA participants also involved in 734 different FP7/H2020 projects. These projects mainly concerned health or information and communication technology as primary topics. In approximately 10% of the projects, former EUnetHTA participants were listed as project coordinator, and with a few exceptions, all of them were universities. Network layouts showed universities dominating participation in community-funded projects, while also securing projects with higher EC contribution. CONCLUSIONS: Quantitative analysis of high-level data on FP7/H2020 projects can efficiently describe several attributes of participating entities. EUnetHTA participants are actively contributing to a noticeable number of community-funded projects of the European Union. Their involvement offers an opportunity to pursue research activities and potentially become centres of excellence through synergies, while also having significant influence on policy formulation.

Conference/Value in Health Info

2016-10, ISPOR Europe 2016, Vienna, Austria

Value in Health, Vol. 19, No. 7 (November 2016)

Code

PRM73

Topic

Methodological & Statistical Research, Real World Data & Information Systems

Topic Subcategory

Confounding, Selection Bias Correction, Causal Inference, Modeling and simulation, Reproducibility & Replicability

Disease

Multiple Diseases

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