ArticleFamily medicine and community health2020
Exploring the structure of social media application-based information-sharing clinical networks in a community in Japan using a social network analysis approach.
Article in Family medicine and community health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Observational
- Use of social media for the improvement of safety knowledge and awareness among Saudi Arabian phlebotomists.Frontiers in medicine · 2023Article
- Analyzing annual changes in network structures of a social media application-based information-sharing system in a Japanese community.BMC health services research · 2022Article
- Patterns of use and perceived value of social media for population health among population health stakeholders: a cross-sectional web-based survey.BMC public health · 2021Article
- What Types of Networks Do Professionals Build, and How Are They Affected by the Results of Network Evaluation?Frontiers in public health · 2021Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveCurrently, use of social networking services (SNSs) for interprofessional collaboration is increasing. However, few studies have reported on virtual interprofessional interactions in community healthcare services. Revealing such structural characteristics of the networks can provide insight into the functions of the interprofessional information-sharing network and lead to smoother collaboration. Thus, we aimed to explore the structure of SNS-based information-sharing clinical networks.
designSocial network analysis (SNA).
settingWe selected a community in City X in Japan. DATA COLLECTION: We analysed SNS-based information-sharing clinical network data linked to patients receiving home medical care or care services between January and December 2018. A network was created for each patient to allow healthcare professionals to post and view messages on the web platform. In the SNA, healthcare professions registered in a patient group were represented as nodes, and message posting/viewing relationships were represented as links in the patient network. We investigated the structural characteristics of the target networks using several measures for SNA, including indegree centrality and outdegree centrality, which reflect the number of incoming and outgoing links to/from a node, respectively. Additionally, the professions forming the most central nodes were investigated based on their ranking to identify those with a central role in the networks. Finally, to compare the networks of nursing care levels 1-3 (lighter care requirement) and those with nursing care levels 4-5 (heavier care requirement), we analysed the structural differences in the networks and investigated the roles of healthcare professionals using centrality measures of nodes.
resultsAmong 844 groups, 247 groups with any nursing care level data were available for analysis. Increasing nursing care level showed higher density, reciprocity and lower centralisation. Healthcare professions with high indegree centrality (physicians, care workers and physical therapists) differed from those with high outdegree centrality (home care workers, physical therapists, and registered dieticians). Visiting nurses and nurses in the clinic played a central role, but visiting nurses tended to have higher indegree and outdegree centrality, while nurses in the clinic had higher closeness and betweenness centrality in networks with heavier care requirement.
conclusionThe SNS-based information-sharing clinical network structure showed that different professions played some form of a central role. Associations between network structures and patient outcomes, cost effectiveness and other factors warrant further investigation.
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