1. Determinants of health insurance enrolment in Ghana
Evidence from three national household
surveys
Paola Salari1,2, Patricia Akweongo3, Moses Aikins3, and Fabrizio Tediosi1,2 1Swiss Tropical and Public Health Institute (Swiss TPH), Basel, Switzerland 2University of Basel, Switzerland 3Ghana School of Public Health, Accra, Ghana
Background
Since 2003 Ghana has been implementing a single National Health Insurance Scheme (NHIS) to move towards Universal Health Coverage. NHIS enrollment is mandatory for each Ghanaian citizen. In exchange for a yearly premium which ranges from GHS 7.2 (USD 1.60) to GHS (USD 10.60), Ghanaian citizens can benefit from a large package of healthcare services. Some population groups (indigents, elderly, pregnant women, children <18, etc.) are exempted from paying the premium. However, after more than ten years, less than 40% of the population is enrolled in the NHIS. The literature has listed some of the characteristics that influence health insurance enrollment, but the evidence appears mixed and studies often rely only on few variables. The aim of this study is to identify which socio-economic and demographic characteristics are associated with NHIS enrollment.
Data & Methods
We use three different household surveys designed to be representative at national level:
the Demographic and Health Survey (DHS),
the Multiple Indicators Cluster Surveys (MICs),
the Ghana Living Standard Survey (GLSS).
In terms of empirical strategy, we ran multilevel logistic regression models where the first level is a small geographic area (i.e. the enumeration area), the second level is the household and the third level is the individual. This econometric approach accounts not only for demand side factors, but also for specific cluster effects indirectly related to supply factors (e.g. the heterogeneity of health systems) and for the correlation between members of the same household.
Results
In line with the existing literature, we find that education and income/wealth are among the most important variables correlated with the choice of enrolling.
Also the presence of a pregnant woman in the house as well as the presence of children (both exempted categories from paying the monthly premium), are positively correlated with the probability of enrolling.
Other positively correlated factors are the marital status and to some extent also age (but not strongly).
Interestingly, the type of occupation shows significant results. Those working in the agricultural sector, casual and manual workers are less likely to be enrolled in the NHIS than people who are not working. Whereas those employed in the formal sector are more likely to enroll.
Conclusions
This study offers a novel contribution to the literature on the individual determinants of enrollment into social health insurance in low and middle income countries. The approach is new both in terms of the data used (i.e. nationally representative households surveys) and in terms of empirical strategy (accounting for contextual factors).
Policy implications
Policies aimed at identifying and subsidizing the lowest income population groups might not be enough to encourage health insurance enrollment.
Policies aimed at reducing the opportunity costs faced by informal workers may play an important role in boosting NHIS enrollment.
Acknowledgments
We thank the r4d Programme
for funding this study.