GIS Data Linking to Enhance Multi-sectoral Decision Making for Family Planning and Reproductive Health: A Case Study in Rwanda
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Family planning and reproductive health (FP/RH) services help provide the foundation of a stable, healthy, and economically viable society. Past global strategies, however, have often led to a vertical implementation of FP/RH programs and policies, despite the value for integrated approaches to meeting health needs.
As a result, decision making for FP/RH can be hindered by a lack of information from other sectors, including other health areas, such as maternal and child health (MCH) or HIV/AIDS. Likewise, sectors outside the realm of public health, such as food security, education, physical infrastructure, and poverty, among others, are not routinely taken into account. Additionally, these other sectors do not typically have access to FP/RH data to contextualize their policies and programs.
Linking multi-sectoral data sources is often deterred by information systems that are developed and maintained independently of other information systems, leading to datasets that are unconnected or ‘stovepiped.’ Through its ability to link data using common geographic identifiers, a geographic information system (GIS) can help overcome this stovepiping of data. Once multi-sectoral data links have been established, a GIS can also be used to enhance the visualization and analysis of FP/RH program data. Enhanced data visualization and analysis can make program data much easier to understand and to use for evidence-based decision making.
- The benefits of linking multi-sectoral data using a GIS include the following:
- provides useful ways to visualize and communicate program data;
- establishes a foundation for data analysis within a geographic context;
- increases access, use, and value of data from multiple sectors;
- supplies a point of reference for discussion among stakeholders; and
- facilitates better targeting of resources.
To explore these benefits, the MEASURE Evaluation Population and Reproductive Health (PRH) Associate Award, which is funded by the United States Agency for International Development (USAID), sponsored an activity to investigate and document the process of using a GIS to link FP/RH data with data from multiple sectors. Rwanda was selected as a case study, and an assessment of available data and possible opportunities for linkages took place in the fall of 2011.
This document is not available in print from MEASURE Evaluation.