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Socioeconomic inequality in informal payments for health services among Iranian households: a national pooled study
Socioeconomic inequality in informal payments for health services among Iranian households: a national pooled study
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Socioeconomic inequality in informal payments for health services among Iranian households: a national pooled study
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Socioeconomic inequality in informal payments for health services among Iranian households: a national pooled study
Socioeconomic inequality in informal payments for health services among Iranian households: a national pooled study

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Socioeconomic inequality in informal payments for health services among Iranian households: a national pooled study
Socioeconomic inequality in informal payments for health services among Iranian households: a national pooled study
Journal Article

Socioeconomic inequality in informal payments for health services among Iranian households: a national pooled study

2023
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Overview
Background There is limited evidence on the prevalence and socioeconomic inequality in informal payments (IP) of households in the Iranian health system. This study was conducted to investigate the prevalence of IP and related socioeconomic inequalities among Iranian households in all provinces. Method Data on Household Income and Expenditure Surveys (HIES) for 91,360 households were used to examine the prevalence and inequality in informal health sector payments in the years 2016 to 2018. The Normalized Concentration Index (NC) was used to examine inequality in these payments and the decomposition analysis by the Wagstaff approach was used to determine the share of variables affecting the measured inequality. Results Of the total households, 7,339 (7.9%) reported IP for using health services. Urban households had higher IP (10%) compared to rural ones (5.42%). Also, the proportion of households with IP in 2016 (11.69%) was higher than in 2017 (9.9%), and 2018 (4.60%). NC for the study population was 0.129, which shows that the prevalence of IP is significantly higher in well-off households. Also, NC was 0.213 ( p  < 0.0001) and -0.019 for urban and rural areas, respectively ( p  > 0.05). Decomposition analysis indicated that income, sex of head of household, and the province of residence have the highest positive contribution to measured inequality (with contributions of 156.2, 45.8, and 25.6%, respectively). Conclusion There are a significant prevalence and inequality in IP in Iran's health system and important variables have shaped it. On the whole, inequality was pro-rich. This may lead to increasing inequality in access to quality services in the country. Our findings showed that previous health policies such as regulatory tools, and the health transformation plan (HTP) have not been able to control IP in the health sector in the desired way. It seems that consumer-side policies focusing on affluent households, and high-risk provinces can play an important role in controlling this phenomenon.