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Patterns in PARTNERing across Public Health Collaboratives

Author

Listed:
  • Christine A. Bevc

    (North Carolina Institute for Public Health, University of North Carolina, Chapel Hill, Campus Box # 8165, Chapel Hill, NC 27599, USA)

  • Jessica H. Retrum

    (Department of Social Work, Metropolitan State University of Denver, Campus Box 70, P.O. Box 173362, Denver, CO 80217-3362, USA)

  • Danielle M. Varda

    (School of Public Affairs, University of Colorado-Denver, 1380 Lawrence St., Ste. 500, Denver, CO 80204, USA)

Abstract

Inter-organizational networks represent one of the most promising practice-based approaches in public health as a way to attain resources, share knowledge, and, in turn, improve population health outcomes. However, the interdependencies and effectiveness related to the structure, management, and costs of these networks represents a critical item to be addressed. The objective of this research is to identify and determine the extent to which potential partnering patterns influence the structure of collaborative networks. This study examines data collected by PARTNER, specifically public health networks ( n = 162), to better understand the structured relationships and interactions among public health organizations and their partners, in relation to collaborative activities. Combined with descriptive analysis, we focus on the composition of public health collaboratives in a series of Exponential Random Graph (ERG) models to examine the partnerships between different organization types to identify the attribute-based effects promoting the formation of network ties within and across collaboratives. We found high variation within and between these collaboratives including composition, diversity, and interactions. The findings of this research suggest common and frequent types of partnerships, as well as opportunities to develop new collaborations. The result of this analysis offer additional evidence to inform and strengthen public health practice partnerships.

Suggested Citation

  • Christine A. Bevc & Jessica H. Retrum & Danielle M. Varda, 2015. "Patterns in PARTNERing across Public Health Collaboratives," IJERPH, MDPI, vol. 12(10), pages 1-14, October.
    • Handle: RePEc:gam:jijerp:v:12:y:2015:i:10:p:12412-12425:d:56760
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    References listed on IDEAS

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    1. Bevc, C.A. & Retrum, J.H. & Varda, D.M., 2015. "New perspectives on the "silo effect": Initial comparisons of network structures across public health collaboratives," American Journal of Public Health, American Public Health Association, vol. 105, pages 230-235.
    2. Morris, Martina & Handcock, Mark S. & Hunter, David R., 2008. "Specification of Exponential-Family Random Graph Models: Terms and Computational Aspects," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i04).
    3. Handcock, Mark S. & Hunter, David R. & Butts, Carter T. & Goodreau, Steven M. & Morris, Martina, 2008. "statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i01).
    4. Schoen, Martin W. & Moreland-Russell, Sarah & Prewitt, Kim & Carothers, Bobbi J., 2014. "Social network analysis of public health programs to measure partnership," Social Science & Medicine, Elsevier, vol. 123(C), pages 90-95.
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