This study makes an important contribution to the existing literature as one of few studies addressing factors associated with health insurance coverage in Peru. While prior studies have primarily focused on examining effects of different insurance schemes on health coverage and service access (38), as well as financial protection (19, 20), no explicit examination of determinants of insurance coverage in Peru has been reported so far. With its narrow focus on women, our study also contributes to the rather limited literature on gender aspects in health financing, such as the identification of coverage gaps specifically faced by women (22).
Our study confirmed almost all the expected associations indicated in Table 1, except for “Age”, where every increasing year of age made it more likely that the individual would have “Standard Insurance” and decreased the likelihood of them having SIS coverage.
Our findings reveal that in spite of the efforts made by the government over the last few years, a relatively large proportion of women of reproductive age (about 25%) still lacks insurance coverage and as such have limited financial risk protection in case of illness. This value is aligned with official population-based estimates, suggesting that following the introduction of SIS in the early 2000s, the proportion of uninsured people decreased from 57.7% in 2007 to 24.5% in 2017 (13), and in the case of women to around 22% in 2017 (39). The results from our study are consistent with national estimates, which reported that the proportion of uninsured women was lower (22.1%) compared with men (27.2%) (11). Based on these estimates, we further conclude that women likely did not face stronger barriers to enrolling under SIS compared to men.
Our findings are worrisome since compared to other LAC countries, such as Colombia, Brazil or Chile, where insurance coverage has reached 90% (40, 41), Peru still lags behind when it comes to securing social health protection through publicly funded insurance schemes. However, findings from these countries is not stratified by population groups and therefore may hide inequities in respect to gender and therefore not fully comparable to our current findings.
This coverage gap may appear surprising given that SIS was launched with the specific intention of fostering progress towards UHC by increasing insurance coverage. However, since it launch the SIS has remained a targeted scheme ensuring coverage of vulnerable populations working in the informal sector in general, not women per se (6). Highlighting the existence of a positive association between SIS coverage and lower socio-economic status, lower education, rural settings and no current employment, our findings suggest that SIS was nevertheless largely successful in reaching a considerable portion of the Peruvian population it intended to reach. Yet, and contrary to our expectations, women living in urban settings were also less likely to belong to the “Standard Insurance” group. While this might be due to increases in low-income earners across cities, further research would be needed to fully explain this finding.
Still surprising, uninsured women were neither necessarily the poorest and less educated, nor the highest educated and richest. Rather, they seemed to represented a middle-class stratum of urban women characterized by being single, of Spanish ethnicity, with few or no children compared with insured women. This finding might directly point at problems related to fragmented health financing structures. While Peru, similar to other LAC countries, kept some level of fragmentation in its financing and organization of health systems by introducing a separate tax-financed insurance scheme targeting the poor (2, 42), the co-existence of multiple pools, each targeting a specific segment of the population, inevitably leaves the most vulnerable groups more exposed to the risk associated with falling ill (43), resulting in inequities and inefficiencies in health coverage (44, 45).
One of the remaining challenges for the Peruvian Government in the coming years is to more specifically target these various population groups to overcome persisting inequities in the country (46). So far, the government has introduced an additional insurance package within the SIS that also allows workers from the informal sector, who don’t necessarily live in extreme poverty, to enroll by paying small monthly contributions that enable access to the SIS physician and hospital network nationwide. However, related research indicates that in order to reduce inequities there needs to be a stronger focus on increasing the amount of pooled finances in the current context of multiple co-existing insurance pools (2, 47).
The key strengths of this study lie in its large sample size and the resulting analytical robustness. Nevertheless, we must acknowledge several weaknesses. First, as we relied on secondary data, our sample is limited to women of reproductive age (15-49 years old), thus not allowing any insight on insurance coverage of older women in the country. We cannot exclude the possibility that different, possibly lower coverage rates might pertain to older women, possibly due to gaps in their knowledge of their entitlements. Second, given the reliance on secondary data, we were limited to variables available in the original survey. For instance, we could not look at the role distance to public health facilities might have played in determining insurance coverage in Peru. Similarly, we were unable to include any information on household heads and the extent to which health-related decision making at the household level hence might have determined women’s insurance status.