Interorganizational Networks: Using a Theoretical Model to Predict Effectiveness of Rural Health Care Delivery Networks
Author: ALICE M. SCHUMAKER
Published in JHHSA, Vol. 25 No. 3
Interorganizational health care delivery networks have potential for sustaining health services delivery in rural areas faced with economic and demographic challenges. Four Nebraska rural health care delivery networks (Albion-Ord, Blue River Vally, Rural Partners, Inc., and Western Nebraska) were compared to an interorganizational model based on theories of interorganizational relations, exchange, population ecology, and synthesized collaboration. It assumes that outcomes, including effectiveness, are influenced by external and internal factors that are operationalized through external control, technology, structure, and operational process variables.
Data were collected by a non-random, two-level cluster mail survey of network members (45/59 = 76.3% response rate). All networks received technical assistance from the Nebraska Office of Rural Health. Networks have formal organization, strategic plans, and official coordinators. Hospital administrators hold most leadership positions; few doctors or citizens are involved.
Correlation and multiple regression analysis show partial fit between the research model and study networks. Effectiveness, measure by the gap between best possible and actual practice, increased with network connectivity (r=.36 p<.05), group methods of administrative decision-making (r=.52, p<.001) and sequential pattern of service delivery (r=.39, p<.05). Greater dependence on vertical funding corresponds to greater external control (r=.43, p<.01). The prediction that, as scope narrows, task intensity (r=.56, p<.001), duration (r=.41, p<.01), and task volume (r=.50, p<.01) increase is upheld. Centrality and network size decrease together (r=.43, p<.01) where there is little reliance on vertical sources of funds (r=.36, p<.05). the integrated interorganizational model demonstrates some efficacy for testing potential effectiveness of networks.
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