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Governing through Evidence

A Study of Technological Innovation in Health Care

Bibliographic Data

ID6294157
AuthorsValentina Mele (0000-0001-9304-2266, Bocconi University), Amelia Compagni (0000-0003-1744-3134, Bocconi University), Marianna Cavazza (0000-0001-5609-6804, Bocconi University)
Year2014
Volume24
Issue4
Pages843-877
Publication date2014-10-01
Open AccessYes
TypeARTICLE
VenueJournal of Public Administration Research and Theory (JOURNAL)
Journal identifiersISSN: 1053-1858 • E-ISSN: 1477-9803
PublisherOxford University Press (OUP) (PUBLISHER)
DOI10.1093/jopart/mut016
OpenAlexW2327745339
LanguageEN
Citations received7
References cited52

The evidence-based paradigm is increasingly permeating the spheres of policymaking and management in health care, as it has in most other public domains. An emerging stream of research has investigated how different institutional arrangements are more (or less) conducive to an effective evidence-based policy. We contribute to this stream through a multiple-case design on governing technological innovation. In particular, the study examines the dynamics through which policymakers have governed the adoption of the Da Vinci robot within the Italian health care system. The analysis leads to the elaboration of four archetypes for governing through evidence, the common mechanisms of which are systematized in an emerging theory. The framework developed here suggests that governing through evidence entails selecting or combining a variety of evidentiary bases, structuring a new relational arrangement among the actors involved, and standardizing decisional criteria and procedures. Combining these elements with the specific governing output sought by policymakers explains the different steering capabilities of institutional arrangements in practice

Archetype · Business · Economics · Health care · Knowledge management · Management science · Political science · Structuring · Variety (cybernetics · Computer Science · Health Systems, Economic Evaluations, Quality of Life · Management and Organizational Studies · Occupational and Professional Licensing Regulation · Artificial Intelligence · Law

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Citations per year0.64
Citation span2015 - 2026 (12)
Highly citedNo

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