TY - JOUR
T1 - Multilevel integrated healthcare :
T2 - The evaluation of Project ECHO® networks to integrate children's healthcare in Australia
AU - Broccatelli, Chiara
AU - Nixon, Phil
AU - Moss, Perrin
AU - Baggio, Sarah
AU - Young, Angela
AU - Newcomb, Dana
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2025/1
Y1 - 2025/1
N2 - The present empirical study aims to explore medical knowledge sharing in the Australian healthcare context, aiming to broadly evaluate the potential impact of Project ECHO®, an online mentoring and networking health program. We focus on health-related knowledge sharing practices among the network of professionals through formal and informal channels, and across different health and non-health sectors and organisational systems. Studying knowledge transmission among professional networks is essential for optimizing healthcare delivery, promoting innovation, and providing insights on improvement of patient experiences within the healthcare system. We utilize a multilevel approach to shape our data collection strategy. Employing network measures and Multilevel Exponential Random Graph Models, we aim to explore how advice and knowledge sharing behaviours among healthcare professionals and their institutions are interdependently connected. Then, we incorporate network generated results within an evaluation framework for establishing some aspects of the efficiency of the ECHO program along four pillars: Acceptability, Capability, Reachability, and Integration. Our investigation found that among ECHO members, hierarchy is less pronounced compared to across levels and organizations, with certain individuals emerging as central in advice-sharing. The multilevel network perspective showed complex, informal patterns of knowledge and information sharing, including inter-organizational hierarchy, role and sector homophily, brokerage roles with popularity across health organizations, and connectivity through knowledge-sharing in cross-level small group clusters.
AB - The present empirical study aims to explore medical knowledge sharing in the Australian healthcare context, aiming to broadly evaluate the potential impact of Project ECHO®, an online mentoring and networking health program. We focus on health-related knowledge sharing practices among the network of professionals through formal and informal channels, and across different health and non-health sectors and organisational systems. Studying knowledge transmission among professional networks is essential for optimizing healthcare delivery, promoting innovation, and providing insights on improvement of patient experiences within the healthcare system. We utilize a multilevel approach to shape our data collection strategy. Employing network measures and Multilevel Exponential Random Graph Models, we aim to explore how advice and knowledge sharing behaviours among healthcare professionals and their institutions are interdependently connected. Then, we incorporate network generated results within an evaluation framework for establishing some aspects of the efficiency of the ECHO program along four pillars: Acceptability, Capability, Reachability, and Integration. Our investigation found that among ECHO members, hierarchy is less pronounced compared to across levels and organizations, with certain individuals emerging as central in advice-sharing. The multilevel network perspective showed complex, informal patterns of knowledge and information sharing, including inter-organizational hierarchy, role and sector homophily, brokerage roles with popularity across health organizations, and connectivity through knowledge-sharing in cross-level small group clusters.
KW - Integrated healthcare
KW - Multilevel exponential random graph models
KW - Advice-seeking networks
KW - Interorganisational networking
UR - https://www.scopus.com/pages/publications/85203412033
UR - https://www.mendeley.com/catalogue/0f661bc1-00a4-397d-a0b5-4ddcf085e21f/
U2 - 10.1016/j.socnet.2024.08.007
DO - 10.1016/j.socnet.2024.08.007
M3 - Article
SN - 1879-2111
VL - 80
SP - 44
EP - 58
JO - Social networks
JF - Social networks
ER -