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Determinants of knowledge-sharing networks in primary care

Determinants of knowledge-sharing networks in primary care

Mascia, Daniele, Pallotti, Francesca and Dandi, Roberto (2016) Determinants of knowledge-sharing networks in primary care. Health Care Management Review, 43 (2). pp. 104-114. ISSN 0361-6274 (Print), 1550-5030 (Online) (doi:https://doi.org/10.1097/HMR.0000000000000139)

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Abstract

Background. Around the world, health reforms are increasingly fostering collaboration and integration among primary care physicians with the aim of facilitating knowledge sharing and evidence-informed decision making. Although extant research on this topic is abundant, the evidence and results regarding social and organizational factors affecting the formation of knowledge-sharing networks in this setting are inconclusive.

Purposes. The aim of this article is to explore multiple theoretical mechanisms explaining the formation of knowledge-sharing networks among primary care physicians across relevant clinical areas.

Methodology/Approach. The data are collected from two local health authorities (LHAs) in the Italian National Health Service that are responsible for delivering primary care in two Italian regions. Exponential random graph models are used to test the hypotheses.

Findings. Our findings indicate that knowledge-sharing networks are highly correlated across clinical areas. In addition, knowledge-sharing networks are highly reciprocal and clustered. We also observe that formal models adopted to foster collaboration have remarkably different effects on the formation of knowledge networks, depending upon the diverse knowledge management approaches adopted in the surveyed LHAs.

Practice Implications. Primary care organizations need to develop and implement knowledge management practices in order to help physicians in identifying knowledge domain experts as well as to support connections through formal groupings and incentives.

Item Type: Article
Uncontrolled Keywords: Knowledge sharing, Primary care, Social networks, Exponential Random Graph Models, organizational design.
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of International Business & Economics
Last Modified: 11 Jul 2018 13:07
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/16043

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