Using Geographic Information System Tools to Address Disparities in Access to Family Planning Services and Commodities in Latin America and the Caribbean

This paper from the United States Agency for International Development (USAID) | DELIVER PROJECT demonstrates a methodology that Latin America and the Caribbean (LAC) ministries of health can use to geographically identify and focus on scarce resources to improve access to family planning (FP). The tools used for achieving reproductive health commodity security are geographic information system (GIS) technology and geo-referenced survey data to visualise the distribution of vulnerable populations and to identify specific areas for targeted interventions.

Guatemala was chosen as a case study for implementing the methodology, in large part because of the disparities that exist between its different sub-populations. Within these areas, the factors that contribute to inequity may be diverse, ranging from operational barriers to cultural barriers and obstacles. More specifically, a study identified the following barriers that contribute to lower contraceptive prevalence among indigenous populations: "primarily, these barriers are operational barriers at health facilities (e.g., discrimination against indigenous women by health personnel, inadequate facilities, and inadequate informational material), and cultural barriers within the community and family environments (e.g., beliefs about negative physical and social effects of FP, and the influence of religious beliefs that oppose FP)." The second study found that barriers in non-indigenous populations include socioeconomic bias and client fears of negative physical effects.

The methodology included the following steps:

1. Inequity was defined and mapped using the following descriptors: rural, low socioeconomic quintile, low levels of education, high unmet need for FP, and a high percentage of indigenous population. The contraceptive prevalence rates (CPR) were included, since the study considered low CPR as a measure of inequity. The geo-referenced survey locations from the 2002 Reproductive Health Survey (RHS) were used to create maps depicting each variable from the inequity definition. "By analyzing the geographic variability in the unmet need data, policymakers can identify and quantify the extent of areas that are underserved because of weaknesses in the contraceptive supply chain, varying socioeconomic or cultural conditions, or location of facilities."
2. Multiple maps were then laid on top of one another within the GIS to combine the values of the different variables into a new single index value. This method, also known as 'suitability analysis', involves first dividing each variable into quintiles and then reclassifying the maps so that numbers 1 - 5 are assigned depending on the comparative magnitude of the factor mapped.
3. The last step in creating the inequity index involves laying the maps on top of each other and adding together the reclassified scores for each variable, by survey location.

According to the document, "[T]his methodology allows policymakers to visualise multiple variables simultaneously and identify where Guatemala's greatest disparities exist between wealthy and poor, urban and rural, indigenous and non-indigenous, and more educated and less educated. It also facilitates a much more geographically disaggregated analysis of disparities in health care, in this case in access to family planning. With additional analysis done in the field, barriers can be further investigated and specific, targeted interventions to improve access can be developed."

Field visits were used to compliment the mapping results. Interviewing showed cultural barriers of machismo and language, physical barriers of travel distances to health posts and economic deficits preventing making FP health rounds to villages, and operational barriers of provider bias against women making FP decision for themselves and contraceptive stock outs. The study suggests that the mapping and interview results point to approaches and interventions that may involve service delivery providers, particularly the Ministry of Health (MOH) and community-based non-governmental organisations (NGOs). Other strategies which might be used by advocacy and interest/community groups and local religious leaders include working on advocacy and community engagement; information, education, and communication; quality of service delivery; and organizational strengthening. Findings include the fact that health posts are not always stocked by the closest health district office. "One recommendation for further improvements in the logistics system is to determine if the distribution networks of MOH Areas... are designed so that health districts supply commodities to the health facilities closest to them."

The document concludes that "... from a more general standpoint, using GIS as a planning tool for policymakers demonstrates how existing data sources can be leveraged to gain new information about the complex issue surrounding health inequities and poverty. Approaching the problem from an inherently geographic perspective allows detailed variations in health and demographic data to be examined for spatial trends, and using GIS tools facilitates an integrated analysis of multiple variables to identify priority areas for future targeted initiatives to reduce inequity in access to FP." It suggests that "[t]he potential exists to link automated logistics management information systems with a GIS to enable geographic monitoring and evaluation of logistics system performance. Ministries of Health may also analyze their distribution networks to ensure that they place facilities close to vulnerable populations to deliver commodities to the last mile."

This publication is available in English and Spanish.