Improving Referrals and Integrating Family Planning and HIV Services through Organizational Network Strengthening
Author(s): Thomas JC, Reynold HW, Alterescu X, Bevc C, Tsegave A
Integrated human immunodeficiency virus (HIV) and family planning services improve quality of care, increase uptake of services, and result in positive effects on outcomes such as contraceptive use and pregnancy incidence. Nevertheless, there have been few evaluations of scalable integration strategies.
To reduce unmet patient needs by increasing referral coordination for HIV and family planning (measured as network density), MEASURE Evaluation conducted organizational network analysis of organizations providing services for HIV care or family planning in two of Addis Ababa’s 10 sub-cities. In one, the researchers sought to increase referrals through three network strengthening meetings. The network analysis was conducted again in both sub-cities to measure any changes since baseline, and the researchers also quantitatively measured reported client service needs in both sub-cities before and after the intervention with two cross-sectional samples of face-to-face interviews with clients.
In the sub-city with the intervention, the number of referral connections between organizations, measured as network density, increased 55%. In the control community, the density decreased over the same period. Reported unmet client service needs declined more consistently across services in the intervention community. This quasi experiment demonstrated that (1) an organizational network analysis can inform a network-strengthening intervention, (2) a modest network strengthening intervention can enhance client referrals in the network, (3) improvement in client referrals was accompanied by a decrease in client-reported unmet needs, and (4) a series of network analyses can be a useful evaluation tool.
This research was the first quantitatively evaluated study of network strengthening in a developing country, and the first anywhere with a control network for comparison.
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