New indicators and indexes for benchmarking university-industry-government innovation in medical and life science clusters: results from the European FP7 Regions of Knowledge HealthTIES project.

European Union Regional innovation cluster Regions of Knowledge biotechnology innovation index life sciences medical sciences public policy triple helix university–industry–government innovation

Journal

Health research policy and systems
ISSN: 1478-4505
Titre abrégé: Health Res Policy Syst
Pays: England
ID NLM: 101170481

Informations de publication

Date de publication:
28 Jan 2019
Historique:
received: 25 07 2018
accepted: 07 01 2019
entrez: 30 1 2019
pubmed: 30 1 2019
medline: 14 5 2019
Statut: epublish

Résumé

While the European Union is striving to become the 'Innovation Union', there remains a lack of quantifiable indicators to compare and benchmark regional innovation clusters. To address this issue, a HealthTIES (Healthcare, Technology and Innovation for Economic Success) consortium was funded by the European Union's Regions of Knowledge initiative, research and innovation funding programme FP7. HealthTIES examined whether the health technology innovation cycle was functioning differently in five European regional innovation clusters and proposed regional and joint actions to improve their performance. The clusters included BioCat (Barcelona, Catalonia, Spain), Medical Delta (Leiden, Rotterdam and Delft, South Holland, Netherlands), Oxford and Thames Valley (United Kingdom), Life Science Zürich (Switzerland), and Innova Észak-Alföld (Debrecen, Hungary). Appreciation of the 'triple helix' of university-industry-government innovation provided the impetus for the development of two quantifiable innovation indexes and related indicators. The HealthTIES H-index is calculated for disease and technology platforms based on the h-index proposed by Hirsch. The HealthTIES Innovation Index is calculated for regions based on 32 relevant quantitative and discriminative indicators grouped into 12 categories and 3 innovation phases, namely 'Input' (n = 12), 'Innovation System' (n = 9) and 'Output' (n = 11). The HealthTIES regions had developed relatively similar disease and technology platform profiles, yet with distinctive strengths and weaknesses. The regional profiles of the innovation cycle in each of the three phases were surprisingly divergent. Comparative assessments based on the indicators and indexes helped identify and share best practice and inform regional and joint action plans to strengthen the competitiveness of the HealthTIES regions. The HealthTIES indicators and indexes provide useful practical tools for the measurement and benchmarking of university-industry-government innovation in European medical and life science clusters. They are validated internally within the HealthTIES consortium and appear to have a degree of external prima facie validity. Potentially, the tools and accompanying analyses can be used beyond the HealthTIES consortium to inform other regional governments, researchers and, possibly, large companies searching for their next location, analyse and benchmark 'triple helix' dynamics within their own networks over time, and to develop integrated public-private and cross-regional research and innovation strategies in Europe and beyond.

Sections du résumé

BACKGROUND BACKGROUND
While the European Union is striving to become the 'Innovation Union', there remains a lack of quantifiable indicators to compare and benchmark regional innovation clusters. To address this issue, a HealthTIES (Healthcare, Technology and Innovation for Economic Success) consortium was funded by the European Union's Regions of Knowledge initiative, research and innovation funding programme FP7. HealthTIES examined whether the health technology innovation cycle was functioning differently in five European regional innovation clusters and proposed regional and joint actions to improve their performance. The clusters included BioCat (Barcelona, Catalonia, Spain), Medical Delta (Leiden, Rotterdam and Delft, South Holland, Netherlands), Oxford and Thames Valley (United Kingdom), Life Science Zürich (Switzerland), and Innova Észak-Alföld (Debrecen, Hungary).
METHODS METHODS
Appreciation of the 'triple helix' of university-industry-government innovation provided the impetus for the development of two quantifiable innovation indexes and related indicators. The HealthTIES H-index is calculated for disease and technology platforms based on the h-index proposed by Hirsch. The HealthTIES Innovation Index is calculated for regions based on 32 relevant quantitative and discriminative indicators grouped into 12 categories and 3 innovation phases, namely 'Input' (n = 12), 'Innovation System' (n = 9) and 'Output' (n = 11).
RESULTS RESULTS
The HealthTIES regions had developed relatively similar disease and technology platform profiles, yet with distinctive strengths and weaknesses. The regional profiles of the innovation cycle in each of the three phases were surprisingly divergent. Comparative assessments based on the indicators and indexes helped identify and share best practice and inform regional and joint action plans to strengthen the competitiveness of the HealthTIES regions.
CONCLUSION CONCLUSIONS
The HealthTIES indicators and indexes provide useful practical tools for the measurement and benchmarking of university-industry-government innovation in European medical and life science clusters. They are validated internally within the HealthTIES consortium and appear to have a degree of external prima facie validity. Potentially, the tools and accompanying analyses can be used beyond the HealthTIES consortium to inform other regional governments, researchers and, possibly, large companies searching for their next location, analyse and benchmark 'triple helix' dynamics within their own networks over time, and to develop integrated public-private and cross-regional research and innovation strategies in Europe and beyond.

Identifiants

pubmed: 30691504
doi: 10.1186/s12961-019-0414-5
pii: 10.1186/s12961-019-0414-5
pmc: PMC6350323
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

10

Subventions

Organisme : Seventh Framework Programme
ID : 265550
Organisme : European Institute of Innovation and Technology
ID : EIT Health-Rare Cancer KIC Stage 1
Organisme : Health Services Research Programme
ID : Oxford Biomedical Research Centre

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Auteurs

Laurel D Edmunds (LD)

Sir William Dunn School, University of Oxford, Oxford, United Kingdom.

Silvia Gluderer (S)

Astellas Pharma, Zürich, Switzerland.

Pavel V Ovseiko (PV)

Sir William Dunn School, University of Oxford, Oxford, United Kingdom.

Roel Kamerling (R)

Medical Delta, Delft University of Technology, Delft, The Netherlands.

Jacqueline Ton (J)

Leiden University Medical Center, Leiden, The Netherlands.

Laura Vis (L)

Province of South Holland, The Hague, The Netherlands.

Mario Jenni (M)

Bio-Technopark Schlieren-Zürich, Zurich,, Switzerland.

Gregory Tutton (G)

Cloverton Holdings, Basel, Switzerland.

Helen Lawton-Smith (H)

Department of Management, Birkbeck, University of London, London, United Kingdom.

Márta Völgyiné Nadabán (MV)

Independent Consultant, Debrecen, Hungary.

Máté Rab (M)

Innonic Group, Debrecen, Hungary.

Jon Rees (J)

Jon Rees Associates Ltd, Oxford, United Kingdom.

John Anson (J)

Oxford Gene Technology, Oxford, United Kingdom.

Alexander D Rushforth (AD)

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.

Maxine Allen (M)

Business Development Team, Medical Sciences Division, University of Oxford, Oxford, United Kingdom.

Alastair M Buchan (AM)

Sir William Dunn School, University of Oxford, Oxford, United Kingdom.

Montserrat Vendrell (M)

BioCat, Bioregion of Catalonia, Barcelona, Spain.

Alex Casta (A)

Business Development Team, Medical Sciences Division, University of Oxford, Oxford, United Kingdom.

Gábor Mehes (G)

Faculty of Public Health, University of Debrecen, Debrecen, Hungary.

Pancras C W Hogendoorn (PCW)

Leiden University Medical Center, Leiden, The Netherlands.

Ernst Hafen (E)

Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland.

A Bassim Hassan (AB)

Sir William Dunn School, University of Oxford, Oxford, United Kingdom. bass.hassan@path.ox.ac.uk.

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Classifications MeSH