The delivery of population health services is a cross-sector effort that involves many different organizations in the community. While research has shown the collaborative nature of population health, very little has examined differences in system composition based on the size of the jurisdiction served. This study examines how the composition of local public health systems differs based on the size of the population served. The National Longitudinal Survey of Public Health Systems (NLSPHS) contains a stratified random sample of the nation's local public health officials (n=397) who were surveyed in 1998, 2006, 2012, and 2014 (70% response) to measure the availability of 20 core public health activities within their jurisdictions and the range of organizations that deliver each activity. The initial sample included departments serving populations of 100,000 or more and was expanded in 2014 to include smaller jurisdictions. We analyzed the networks for four key Social Network Analysis measures. Degree centralization measures the connectedness of organizations in the network, density measures the proportion of total possible relationships that exist between organizations in the network, degree centrality captures the number of relationships that an organization maintains with others in the network, and betweenness centrality measures the degree an organization lies between others in the network. We then used multivariate regression to determine if significant differences exist between small and large jurisdictions. Large systems are 20% more central (p<0.01), indicating that less organizations are providing the bulk of activities, while smaller systems have more organizations participating in population health. Regression results indicated that differences in systems based on size exist when controlling for the likelihood that there are more partners available in large jurisdictions because of scale effects.

Details

Project: A Network View of Population Health Delivery Systems
Resource: View Event
Authors: Hogg RA, Timsina L, Mays GP