How To Find Out If A Health Care Coalition Has A Diverse Network
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1 Paul C. Erwin, MD, DrPH Danielle Varda, PhD Victoria Mills, BA Denise Bates, PhD
2 coalitions are interorganizational, cooperative and synergistic working alliances. The word 'coalition', itself, is derived from two Latin roots, coalescere, 'to grow together', and coalitio, 'a union'. Coalitions unite individuals and groups in a shared purpose. Butterfoss, 1993.
3 Local Public Health System (LPHS): All public, private, and voluntary entities that contribute to the delivery of the Essential Public Health Services within a given jurisdiction. (CDC) More than just the LHD, but with the LHD playing a key convener and leadership role The focus of the National Public Health Performance Standards Program/Local Public Health System Assessment in MAPP Rarely conceptualized as an organizational entity, therefore a challenge in assessing and holding accountable
4 EMS Schools Neighborhood Organizations Civic Groups Non-Profit Organizations Nursing Homes Community Centers Hospitals Doctors CHCs Drug Treatment Law Enforcement Employers Corrections Public Health Agency Tribal Health Laboratories Faith Institutions Elected Officials Fire Home Health Mental Health Transit
5
6 Do high functioning health coalitions [LPHS] have more diverse networks? How much diversity exists in health coalitions? Is there a relationship between functional attributes and diversity of network connections? What are the network characteristics of highly functioning coalitions and how can such characteristics be measured?
7 Network Theories Explain Why Diverse Systems May Perform Better Strength of Weak Ties (Granovetter 1973) How do people find jobs? Through their friends of friends (in other words their weak ties). Weak ties provide people with access to novel information, whereas strong ties tend to know the same things (e.g. funding opportunities, access to populations, etc.). Hence, the denser the ties in an ego network, the stronger the ties, and the more insular the ego network and also the more homogeneous. Weak ties = Diverse Ties = Network Benefits
8 Source of data Focus: County Health Councils in Tennessee Web-based survey instrument sent to Chairs or Co-chairs of CHCs Determining Functional Score Measures of seven functional characteristic were identified scored Total Functional Score (TFS) was calculated by summing 7 (# of partners excluded from this scores) functional characteristics scores: > Resources > External linkages > Communication > Team leadership > Task-focused climate > Active member participation > Formal rules, roles and procedures
9 Characteristic of County Health Council Written By-laws 64% Strategic Plan 50% Financial Resources 39% Non-Profit Status 12.5% Have a Lead Agency 37.5% Formalized by decree 22.2% Mean membership/attend 24/15 % of CHCs (n=64) (Response Rate of 77%)
10 How much diversity exists in health coalitions? Social Network Analysis of Affiliation Networks (chair x sector) Descriptive Analysis Scaling Analysis to look for patterns Is there a relationship between functional score and diversity of network connections? Autocorrelations & Regression: Accounting for nonindependent nature of the data. What are the network characteristics of highly functioning coalitions and how can such characteristics be measured? Centrality Scores and Ego-Centric networks
11 1. How much diversity exists in health coalitions? 2. Is there a relationship between functional attributes and diversity of network connections? 3. What are the network characteristics of highly functioning coalitions and how can such characteristics be measured?
12 Sector Selection Frequency
13 Many Sectors, Largely Equally Selected From this perspective, the diversity of the networks is evident; the lack of variability is also evident.
14 2 Mode Network Larger Nodes are the Sectors More Frequently Selected Visualization of the 2-Mode Network. Blue nodes are sectors, red nodes (very small) are respondents. The larger the nodes, the more times it was selected.
15 1. How much diversity exists in health coalitions? 2. Is there a relationship between functional attributes and diversity of network connections? 3. What are the network characteristics of highly functioning coalitions and how can such characteristics be measured?
16 Relationships Between Adjacent Network Members and Total Functional Scores The Geary statistic suggests that the difference of our result from the average of 1,000 random trials (0.896) is statistically significant (p =.021). 1,000 Random Trials Autocorrelation Significance Permutation Average Standard Error Proportion as large Proportion as small (positive correlation) Geary Correlations Show a Weak, but Positive Correlation
17 Total Functional Score Can it Predict Diversity of Coalition Networks? The correlation matrix shows moderate collinearity between the TFS and number of sectors selected. (0.351) The R-squared is small for this simple model (0.123), although highly significant using permutation tests ( p =.005). MODEL FIT Adjusted One-Tailed R-square R-square F Value Probability
18 1. How much diversity exists in health coalitions? 2. Is there a relationship between functional attributes and diversity of network connections? 3. What are the network characteristics of highly functioning coalitions and how can such characteristics be measured?
19 Individual Network Scores Tell Us About Each Coalition s Network Characteristics Centrality ( Embeddedness Characteristics ) Degree - Size of network (normalized). Closeness. - Reach to other members of the network Betweeness. - Extent that each node bridges members of the network. Ego Centric Measures ( Neighborhood Characteristics ) Size - Size of ego network. Ties - Number of directed ties. Pairs - Number of ordered pairs.
20 Centrality Scores of Sectors Degree: # of Connections; LHDs are 1.00 because everyone selected them; these are percentages of all possible (64) ties. Closeness: very reflective of degree; this represents the smallest # of paths from each sector to all other nodes. Betweeness: represents bridges but this network is so dense, there are no subgroups all one component, so no bridges.
21 Ego Network Characteristics Explain Some of the Variability in Network Scores Coalition With the Highest Functional Score Coalitions With the Top Two Functional Scores. Some common partners, but also a number of different partners.
22 The More Ego Networks Included, the Variability in Their Neighborhoods is Visualized Coalition With the Top Three Functional Scores. Some common partners, but still new ones introduced (these explain the variability in scores such as betweeness ). By the time all are ego networks are combined to one large network, we see some patterns, but generally a well-connected networks.
23 Structure, in this case diversity (defined by the number of connections to other sectors), is related to functional score. While size of network is significant, when we look at health coalitions as ego networks, we see that who they are related to differs across functional scores, even for those with high scores.
24 Conclusions The study of Health Coalitions may provide a pathway to understanding SYSTEM functionality. While size/diversity of SYSTEM partners matters, more is better is not the simple answer to improving SYSTEM functionality. Understanding WHY some partners are selected and others are not, and the quality of those connections even for similarly highly functioning Health Coalitions may provide further insights into why some SYSTEMS function well and others do not.
25
26 EMS Schools Neighborhood Organizations Civic Groups Non-Profit Organizations Nursing Homes Community Centers Hospitals Doctors CHCs Drug Treatment Public Health Agency Law Enforcement Tribal Health Employers Corrections Laboratories Faith Institutions Elected Officials Fire Home Health Mental Health Transit
27 Community Coalition Action Theory (Butterfoss & Kegler, 2009)
28 A conceptual framework for a Local Public Health System(Handler, Issel, & Turnock, 2001)
29
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