Towards Universal Health Coverage: An Evaluation of Rwanda Mutuelles in Its First Eight Years

Background: Mutuelles is a community-based health insurance program, established since 1999 by the Government of Rwanda as a key component of the national health strategy on providing universal health care. The objective of the study was to evaluate the impact of Mutuelles on achieving universal coverage of medical services and financial risk protection in its first eight years of implementation. Methods and Findings: We conducted a quantitative impact evaluation of Mutuelles between 2000 and 2008 using nationally-representative surveys. At the national and provincial levels, we traced the evolution of Mutuelles coverage and its impact on child and maternal care coverage from 2000 to 2008, as well as household catastrophic health payments from 2000 to 2006. At the individual level, we investigated the impact of Mutuelles' coverage on enrollees' medical care utilization using logistic regression. We focused on three target populations: the general population, under-five children, and women with delivery. At the household level, we used logistic regression to study the relationship between Mutuelles coverage and the probability of incurring catastrophic health spending. The main limitation was that due to insufficient data, we are not able to study the impact of Mutuelles on health outcomes, such as child and maternal mortalities, directly. The findings show that Mutuelles improved medical care utilization and protected households from catastrophic health spending. Among Mutuelles enrollees, those in the poorest expenditure quintile had a significantly lower rate of utilization and higher rate of catastrophic health spending. The findings are robust to various estimation methods and datasets. Conclusions: Rwanda's experience suggests that community-based health insurance schemes can be effective tools for achieving universal health coverage even in the poorest settings. We suggest a future study on how eliminating Mutuelles copayments for the poorest will improve their healthcare utilization, lower their catastrophic health spending, and affect the finances of health care providers

Logistic regression results for medical care utilization among the general population who reported illness using unmatched data, matched data, and matched data with IV method.

<p>Abbreviations: N: sample size, OR: odds ratio, SE: standard error.</p>*<p>: statistically significant at the 0.05 level.</p>**<p>: statistically significant at the 0.01 level.</p

Trends of <i>Mutuelles</i> coverage and utilization of child care and skilled-birth attendance.

<p>The trends are between 2000 and 2008. The data is taken from the Rwanda Demographic and Health Survey in 2000, 2005, and 2008. Error bars represent 95% confidence intervals (CI). * Estimate is based on a study by Schneider and Diop in 2004 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039282#pone.0039282-Schneider1" target="_blank">[20]</a>. ** Estimate is from Community Based Health Insurance in Rwanda (<a href="http://www.cbhirwanda.org.rw/" target="_blank">http://www.cbhirwanda.org.rw/</a>) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039282#pone.0039282-Community1" target="_blank">[16]</a>.</p

Individuals included in the analyses of child and maternal care with RDHS.

<p>Individuals included in the analyses of child and maternal care with RDHS.</p

Regression results for child and maternal care analyses with panel data at the provincial level.

<p>Abbreviations: SE: standard error; N: sample size.</p>*<p>: statistically significant at the 0.05 level.</p>**<p>: statistically significant at the 0.01 level.</p

Households and individuals included in the analyses of financial risk protection and medical care utilization with EICV.

<p>Households and individuals included in the analyses of financial risk protection and medical care utilization with EICV.</p

Descriptive statistics for variables used in analyzing medical care utilization of the general population who reported illness in the prior two weeks of the survey (EICV 2006).

<p>Abbreviations: N: sample size; SD: standard deviation; Unmatched data: full set of data; Matched data: subset of data which excluded outliers in observed variables.</p

Checking endogeneity of <i>Mutuelles</i>: mean difference of self-reported illness and birth delivery by <i>Mutuelles</i> status (RDHS).

<p>Checking endogeneity of <i>Mutuelles</i>: mean difference of self-reported illness and birth delivery by <i>Mutuelles</i> status (RDHS).</p

Descriptive statistics for variables used in analyzing household catastrophic health spending (EICV 2006).

<p>Abbreviations: N: sample size; SD: standard deviation; Unmatched data: full set of data; Matched data: subset of data which excluded outliers in observed variables.</p

Improved health outcome indicators over time.

<p>Source: WHO, UNICEF, UNFPA and the World Bank (<a href="http://www.childinfo.org/maternal_mortality.html" target="_blank">http://www.childinfo.org/maternal_mortality.html</a>).</p