To determine how a health officials' advice network might contribute to a high-performing public health systems by facilitating diffusion of innovation and best practices.
A secondary analysis of cross-sectional data obtained from the National Association of County and City Health Officials 2010 Profile of local health departments (LHDs) using network analysis.
The Profile survey is distributed biannually to all 2565 LHDs in the United States. In 2010, it included a network question: “In thinking about your peers who lead other local health departments in the U.S., list the five LHDs whose leaders you communicate with most frequently about administrative, professional, and leadership issues in public health.”
The network question was answered only by the top executive. The subjects are 1522 health officials who answered the network question plus 477 named as contacts (n = 1999).
Measurements to assess network topology were density, centralization, transitivity, and reciprocity. At the node level, average centrality, clustering, effective network size, and clique count were measured. The convergence of iterated correlations algorithm was used to detect subgroups.
A sparsely connected core periphery network exhibited minimal evidence of unified communication. Mutually connected small groups tend to clump within state boundaries suggesting gaps in information flow. The pattern persisted at the regional level with an average health official having an effective network of only 2 others.
Communication between peers may not be the primary way professional information diffuses among local health officials. National groups involved in performance improvement may wish to consider strategies to increase the diffusion of best practices and innovations through this network.
This article discusses how a health officials' advice network might contribute to a high-performing public health systems by facilitating diffusion of innovation and best practices. Examination of regional networks and subgroup analysis showed a clumping communication pattern that largely follows state boundaries.
School of Nursing and Department of Biomedical Informatics (Dr Merrill), Department of Epidemiology, Mailman School of Public Health (Dr Orr), and School of Nursing (Jeon), Columbia University, New York; and Institute for Software Research, Carnegie Mellon University, Pittsburgh, Pennsylvania (Dr Carley and Mr Storrick).
Correspondence: Jacqueline Merrill, RN, MPH, DNSc, Columbia University, 630 West 168th St, Georgian 226, New York, NY 10032 (firstname.lastname@example.org).
The study was funded by the National Coordinating Center for Public Health Services and Systems Research at the University of Kentucky.
The authors declare no conflicts of interest.