# Equity of Social Health Insurance Coverage for Migrants in Thailand: A Concentration Index Analysis
## 4 Discussion
Another point worth mentioning is that before 2018 the CI for the industrial sector demonstrated a pro-rich pattern, while the CI for the agricultural sector was reported as pro-poor. This issue draws a point for policy consideration which is that by focusing on the industrial sector, the SSS coverage was concentrated among the rich provinces. In contrast, in the agricultural sector, the SSS coverage was concentrated among the less affluent provinces. The situation also alludes to the fact that the law requiring agricultural migrantworkers to be enrolled in the SSS was poorly enforced [21]. This contradicted the primary policy intention that the employment law would be effectively enforced nationwide which is why we initially expected an equitable distribution of the SSS coverage across provincial economy (near-zero CI). Concerning policy implications, policy makers or public health practitioners may consider using CI or CC to monitor the insurance coverage of migrants in addition to the crude coverage. The analysis may be more granular if sub-provincial data are available. The CI may help prioritize areas for actions and identify which provinces (varying by economic status) are performing well (or poorly) in enrolling migrants to the insurance and which areas need more intensive enforcement of the insurance enrollment than others. Areas where the agricultural business plays a critical role are mostly located in the border areas, while areas close to the country's centre, including Bangkok and its vicinity, mostly depend on industrial businesses. Future research that explores the geographical effect on insurance coverage may be useful to help tailor policies to promote migrant insurance enrollment. This article has extended the academic value of research in migrant health. We suggested that the coverage of the insurance is, to some extent, linked with the macro-economic indicators. Most prior research that explored reasons for why migrants dropped out from the public insurance schemes usually pointed to their individual interaction between health providers and migrant themselves. Reasons for this included discrimination, language differences and the lack of support to be integrated in the destination country's healthcare system. Despite a comprehensive analysis, some limitations remain. First, the data we retrieved might not be able to reflect \"all\" migrants in Thailand. Some migrant workers (of unknown number) stay undocumented and untraceable by the government. Most of them are suspected to be in the informal sector rather than the formal sector. Second, the GPP per capita (though tallied by business sectors) might not serve as a perfect indicator for provincial prosperity. However, it is the only composite indicator we could obtain from the online public domains. Third, the data of SSS members, the data related to the number of migrants, and the economic data were retrieved from different sources. This would explain why the SSS coverage in certain moments of time exceeded one and this justified why we preferred the term \"ratio\" over \"proportion\" when referring to SSS coverage. Such phenomenon might occur because of many reasons. For instance, some migrants' work permits had already expired, and this excluded them from the SSS, but it was possible that the number of SSS members had not been updated. This issue also pointed towards room for improvement of intersectoral integration of the information system on migrants in the country. Last is the issue of ecological fallacy [22]. As this research is an ecological study in nature, ecological fallacy is inevitable. That is, the measure of association between variables at the group level might not always represent the association at the individual level. Further studies that explore the relationship between socioeconomic status and insurance status at the individual or household levels are worth exploring. However, this needs huge support from the state authorities and huge effort in data collection processes as a primary survey is required [23].