Objective. To determine and describe the features of Indigenous participation in an informal national Indigenous health policy network.
Design. A questionnaire was administered during 2003–04. Through a snowball nomination process a total of 227 influential persons were identified. Of these, 173 received surveys of which 44 were returned, a return rate of 25%.
Outcome measures. These data were analysed to detect the existence of network groups; measure the degree of group interconnectivity; and measure the characteristics of bonds between influential persons. Demographic information was used to characterise the network and its groups.
Results. Indigenous people were integral to the network due to their high representation, their distribution throughout the 16 groups, and the interconnections between the groups. The network was demographically diverse and multiple relational variables were needed to characterise it. Indigenous and non-Indigenous people had strong ties in this network.
Conclusion. Social network methods made visible an informal network where Indigenous and non-Indigenous people relate in a complex socio-political environment to influence national Indigenous health policy.
What is known about the topic? The participation of Indigenous people is acknowledged as important in health, but there is criticism of the lack of real opportunities for Indigenous people to participate in national Indigenous health policy processes.
What does this paper add? This research reveals the presence of an informal network of influential persons. It demonstrates a way to investigate the concept of participation through social network analytic techniques. It reveals that Indigenous people are fundamental to an informal network that influences national health policy processes.
What are the implications for practitioners? Practitioners can become more aware of their place in informal networks of influence and of their capacity to exercise personal influence in national policy decisions based on advice drawn from their informal networks.