Table 1.

Network Metrics Used in the Study With Their Definitions.

Network Metric	Definition
Node size	The number of nodes (in this case, individual staff) in the network.
Density	The percentage of actual to possible connections between nodes.
Weighted density	Density weighted by frequency of communication.
Total degree centrality	How many neighbors a node is connected to—includes both incoming (in-degree) and outgoing (out-degree) communication.
Betweenness centrality	Measures the number of times that connections must pass through a single individual to be connected (i.e., which person is most central to the network as a whole and likely to be the most influential with the most group knowledge). Higher scores describe organizations in whom many people play this central role.
Eigenvector centrality	Measure of node connections to highly connected people. A person well connected to well-connected people can spread information quickly and could be critical when rapid communication is needed.
Clustering coefficient	Extent to which there are small clusters (cliques). A higher clustering coefficient supports local information diffusion as well as a decentralized infrastructure because employees are likely to share information and know what is happening in their work group.
Average distance	The average number of connections along the shortest paths for all possible pairs of network nodes. Average distance provides a measure of information efficiency.
Diffusion	The speed with which information can travel through the network.