Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
BMC Public Health
Published in: BMC Public Health 1/2016

Open Access 01-12-2016 | Research article

Partnership capacity for community health improvement plan implementation: findings from a social network analysis

Authors: J. Mac McCullough, Eileen Eisen-Cohen, S. Bianca Salas

Published in: BMC Public Health | Issue 1/2016

Login to get access

Abstract

Background

Many health departments collaborate with community organizations on community health improvement processes. While a number of resources exist to plan and implement a community health improvement plan (CHIP), little empirical evidence exists on how to leverage and expand partnerships when implementing a CHIP. The purpose of this study was to identify characteristics of the network involved in implementing the CHIP in one large community. The aims of this analysis are to: 1) identify essential network partners (and thereby highlight potential network gaps), 2) gauge current levels of partner involvement, 3) understand and effectively leverage network resources, and 4) enable a data-driven approach for future collaborative network improvements.

Methods

We collected primary data via survey from n = 41 organizations involved in the Health Improvement Partnership of Maricopa County (HIPMC), in Arizona. Using the previously validated Program to Analyze, Record, and Track Networks to Enhance Relationships (PARTNER) tool, organizations provided information on existing ties with other coalition members, including frequency and depth of partnership and eight categories of perceived value/trust of each current partner organization.

Results

The coalition’s overall network had a density score of 30 %, degree centralization score of 73 %, and trust score of 81 %. Network maps are presented to identify existing relationships between HIPMC members according to partnership frequency and intensity, duration of involvement in the coalition, and self-reported contributions to the coalition. Overall, number of ties and other partnership measures were positively correlated with an organization’s perceived value and trustworthiness as rated by other coalition members.

Conclusions

Our study presents a novel use of social network analysis methods to evaluate the coalition of organizations involved in implementing a CHIP in an urban community. The large coalition had relatively low network density but high degree centralization—meaning key organizations link organizations otherwise not tightly partnering. Coalition members rated each other highly on trust, a positive sign for future partnership development efforts. Examination of network maps reveal key organizations that can be targeted for future partnership facilitation and expansion. Future network data collection will enable exploration of longitudinal trends and exploration of network characteristics versus health behavior, status, and outcome changes.
Literature
1.
Institute of Medicine. The Future of Public Health. Washington, DC: National Academy Press; 1988.
2.
3.
Cheadle A, Hsu C, Schwartz PM, Pearson D, Greenwald HP, Beery WL, Flores G, Casey MC. Involving Local Health Departments in Community Health Partnerships: Evaluation Results from the Partnership for the Public’s Health Initiative. J Urban Health. 2008;85(2):162–77.CrossRefPubMedPubMedCentral
4.
5.
National Association of County and City Health Officials. 2013 National Profile of Local Health Departments. Washington, DC: NACCHO; 2014.
6.
Abarca C, Grigg CM, Steele JA, Osgood L, Keating H. Building and measuring infrastructure and capacity for community health assessment and health improvement planning in Florida. J Public Health Manag Pract. 2009;15(1):54–8.CrossRefPubMed
7.
Wetta RE, Dong F, LaClair B, Pezzino G, Orr SA. Factors Affecting the Progress of Community Health Assessment and Improvement Activities in Kansas. J Public Health Manage Practice. 2015;21(4):E1–9.CrossRef
8.
Institute of Medicine. Improving health in the community: a role for performance monitoring. Washington, DC: National Academies Press; 1997.
9.
Zahner SJ, Kaiser B, Kapelke-Dale J. Local partnerships for community assessment and planning. J Public Health Manag Pract. 2005;11(5):460–4.CrossRefPubMed
10.
11.
Spice C, Snyder K. Reviewing Self‐Reported Impacts of Community Health Assessment in Local Health Jurisdictions. J Public Health Manage Practice. 2009;15(1):18–23.CrossRef
12.
Erwin PC, Hamilton CB, Welch S, Hinds B. The Local Public Health System Assessment of MAPP/The National Public Health Performance Standards Local Tool: a community-based, public health practice and academic collaborative approach to implementation. J Public Health Manage Practice JPHMP. 2006;12(6):528–32.CrossRef
13.
Lenihan P. MAPP and the evolution of planning in public health practice. J Public Health Manage Practice. 2005;11(5):381–6.CrossRef
14.
Kalos A, Kent L, Gates D. Integrating MAPP, APEXPH, PACE-EH, and other planning initiatives in Northern Kentucky. J Public Health Manag Pract. 2005;11(5):401–6.CrossRefPubMed
15.
Stoto MA, Straus SG, Bohn C, Irani P. A Web-based tool for assessing and improving the usefulness of community health assessments. J Public Health Manag Pract. 2009;15(1):10–7.CrossRefPubMed
16.
Chudgar RB, Shirey LA, Sznycer-Taub M, Read R, Pearson RL, Erwin PC. Local health department and academic institution linkages for community health assessment and improvement processes: a national overview and local case study. J Public Health Manage Practice. 2014;20(3):349–55.CrossRef
17.
Roussos ST, Fawcett SB. A review of collaborative partnerships as a strategy for improving community health. Annu Rev Public Health. 2000;21:369–402.CrossRefPubMed
18.
Kuehnert P, Graber J, Stone D. Using a Web-based tool to evaluate a collaborative community health needs assessment. J Public Health Manage Practice. 2014;20(2):175–87.CrossRef
19.
Rodriguez HP, McCullough JM, Hsuan C. Local Health Department Collaborative Capacity to Improve Population Health. Frontiers Public Health Services Syst Res. 2014;3(4):7.
20.
Hogg RA. Examining the Relationship Between Public Health Delivery System Structures and Local Health Department Efficiency [Doctoral Capstone]. Lexington, KY: College of Public Health, University of Kentucky; 2014.
21.
Luke DA, Harris JK. Network analysis in public health: history, methods, and applications. Annu Rev Public Health. 2007;28:69–93.CrossRefPubMed
22.
Klovdahl AS. Social networks and the spread of infectious diseases: the AIDS example. Soc Sci Med. 1985;21(11):1203–16.CrossRefPubMed
23.
Klovdahl A, Graviss E, Yaganehdoost A, Ross M, Wanger A, Adams G, Musser J. Networks and tuberculosis: an undetected community outbreak involving public places. Soc Sci Med. 2001;52(5):681–94.CrossRefPubMed
24.
Harris JK, Clements B. Using social network analysis to understand Missouri’s system of public health emergency planners. Public Health Rep. 2007;122(4):488.PubMedPubMedCentral
25.
Merrill J, Keeling JW, Carley KM. A Comparative study of 11 Local health department organizational networks. J Public Health Manage Practice JPHMP. 2010;16(6):564.CrossRef
26.
27.
Varda DM, Chandra A, Stern SA, Lurie N. Core dimensions of connectivity in public health collaboratives. J Public Health Manage Practice. 2008;14(5):E1–7.CrossRef
28.
29.
Luke DA, Wald LM, Carothers BJ, Bach LE, Harris JK. Network influences on dissemination of evidence-based guidelines in state tobacco control programs. Health Educ Behav. 2013;40(1 suppl):33S–42S.CrossRefPubMed
30.
Paulhus DL. Measurement and control of response bias. In Robinson JP, Shaver PR, Wrightsman LS, (Ed). Measures of personality and social psychological attitudes. Measures of social psychological attitudes. Vol 1. San Diego: Academic Press. pp. 17-59.
31.
Kossinets G. Effects of missing data in social networks. Soc Networks. 2006;28(3):247–68.CrossRef
32.
Borgatti SP, Carley KM, Krackhardt D. On the robustness of centrality measures under conditions of imperfect data. Soc Networks. 2006;28(2):124–36.CrossRef
Metadata
Title
Partnership capacity for community health improvement plan implementation: findings from a social network analysis
Authors
J. Mac McCullough
Eileen Eisen-Cohen
S. Bianca Salas
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2016
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-016-3194-7

Other articles of this Issue 1/2016

BMC Public Health 1/2016 Go to the issue

Research article

Distribution and patterning of non-communicable disease risk factors in indigenous Mbororo and non-autochthonous populations in Cameroon: cross sectional study

Erratum

Erratum to: ‘HIV prevalence in the Israeli tuberculosis cohort, 1999–2011’

Erratum

Erratum to: Childhood maltreatment as a risk factor for diabetes: findings from a population-based survey of Canadian adults

Research article

Epidemiology and risk factors for pneumonia severity and mortality in Bangladeshi children <5 years of age before 10-valent pneumococcal conjugate vaccine introduction

Research article

Incidence of tuberculosis among school-going adolescents in South India

Research article

Substituting sugar confectionery with fruit and healthy snacks at checkout – a win-win strategy for consumers and food stores? a study on consumer attitudes and sales effects of a healthy supermarket intervention