Quantifying the impact of clinical-academic collaborations
Mohamad Zeina, Nick McNally, Karl S. Peggs, Parashkev Nachev
Abstract
Academic collaboration is of self-evident value but requires a quantitative representation to be optimally guided by policy. No established methodological approach to such representation exists. Here we introduce a general framework of graphical and bibliometric analysis of open data for the task of quantifying the impact of academic networks, with NIHR Biomedical Research Centre (BRC) clinical-academic partnerships in England as the prototype. We define publication-level identities for the 20 English BRCs based on the conjunction of authors from each BRC's partner institutions. Drawing on bibliometric and administrative records, we characterise the graphical properties of each network, estimate what the university adds to the hospital's papers, what the partnership adds to the papers of relatively infrastructure-poor collaborating institutions, and how that gain depends on existing infrastructure. We apply our framework to the NIHR UCLH/UCL BRC as an exemplar. UCLH/UCL authored 20,985 network papers from April 2007, in collaboration with 9,868 distinct external partners over the whole record, forming the most central node of the graph of networks across England. University co-authored papers exhibited 1.6 times the field-weighted citation impact (FWCI) of hospital-only papers, and were 2.1 times as likely to be cited by a patent. Across 60 of the exemplar's most partnered with UK healthcare organisations, the benefit rose from 1.8 times where local NIHR infrastructure activity was densest to 3.4 times where it was sparsest, while impact without the exemplar varied little. Academic networks can be robustly identified from open data, enabling comparative analysis of collaborative impact. Applied to NIHR BRCs, the approach enables quantification of the impact across networks and reveals that benefit is most pronounced where infrastructure is least developed.
Create a lesson
Related papers
Shifting Research Funding Priorities under Geopolitical Pressure: Evidence from Estonia
Yunfeng Gao, Yang Ding
Geospatial Metadata Improves Discoverability by Connecting Datasets Across Scientific Disciplines
Daniel Ebanks, Devika Jain
Testing Our Foundations: Citation Trends, Errors, and Emerging Hallucinations in the Computing Education Literature
Paul Denny, Gweneth Barbre, Musa Blake et al.
Toward non-textual representation of social anthropology: Modeling cultures as knowledge graphs
Manolis Peponakis, Sarantos Kapidakis, Martin Doerr et al.
Geometric Signatures of Conceptual Reorganization: A Counterfactual Embedding Framework for Detecting Scientific Revolutions
Dimitris Ntounis, Ariel Schwartzman, Chris Chafe et al.
Ending the NIH embargo accelerated public access to funded research, but substantial delays remain
Haining Wang