NGO management and health care financing approaches in the Eastern Democratic Republic of the Congo

Abstract

The role of cost-sharing in health care is a crucial, yet contentious issue. In conflict situations, cost-sharing becomes even more controversial as health and other institutions are failing. In such situations, NGOs manage health programmes which aim to aid populations in crisis and improve or at least sustain a deteriorating health system. This study looks at the issue of cost-sharing in the wider context of utilization rates and management approaches of three NGOs in the chronic, high-mortality crisis of the eastern DRC. Approaches to increase access to health care were found to exist, yet cost-recovery, even on the basis of maximum utilization rates, would only partially sustain the health system in the eastern DRC. Factors external to the direct management of NGO health programs, such as the wider economic and security situation, local management structures, and international donor policies, need to be taken into account for establishing more integrated management and financing approaches.

Keywords:

• Cost-recovery
• chronic emergency
• Non-Governmental Organizations (NGOs)
• management and financing

Acknowledgments

The authors would like to thank Ron Waldman, Jannes van der Wijk, Annemarie ter Veen, and Steve Hansch, as well as the National Research Council for their contributions to and criticism on earlier versions of this article. Additional thanks go to two anonymous reviewers for their constructive comments.

Notes

1. In addition, cost-recovery in health has often been introduced to achieve macroeconomic balance, as promoted by the World Bank and International Monetary Fund (Creese and Kutzin 1995: 3–5).

2. Dividing the population by twelve allowed for comparison per month in the context of price decreases or increases. In addition, one NGO had already calculated its rates in this way and the data from the remaining two NGOs were converted to percentages in this manner to allow for comparison.

3. For a more elaborate analysis, see Dijkzeul and Lynch (2005).

4. An example of criteria for indigence are (IRC): the poor without possessions, widows or widowers without other support, the severely malnourished, orphans without any other support, mentally and physically handicapped without possessions, people without work or land, and the chronically ill.

5. Calculated on the basis of table 2.

6. Population estimates are based on extrapolations from 1984. The effect of this lack of recent demographic data on utilization rate however may be limited by the fact that a change in the numerator (i.e. utilization) will have a much larger effect than a change in the denominator (population). As an example of how different population estimates may affect the utilization rates which have been calculated, we can look at the peak period of utilization for IRC (March 2001). During this period, according to population estimates used the utilization rate was 80%. If we take into account a 10% difference in population estimate, the utilization rates will then vary accordingly to between 73–89%. By the same token, a population estimate which is 20% different from that used for the calculations, would result in utilization rates between 67–100%. However, it is unlikely that the population estimates would vary to such a degree.