The disparities in health insurance ownership of hospital-based birth deliveries in eastern Indonesia

Factors Related to Hospital Inpatients among the Poor in Indonesia

Background

The poor are vulnerable when they fall seriously ill and require hospitalization. The study aimed to analyze the factors related to hospital inpatients among the poor in Indonesia.

Methods

We analysed the 2018 Indonesian Basic Health Survey data. This cross-sectional study examined 233778 respondents through stratification and multistage random sampling. We used seven independent variables age, gender, marital status, education, employment, and health insurance, in addition to the hospital inpatient, as a dependent variable. We employed binary logistic regression to evaluate the data.

Results

The poor in urban areas were 1.315 times more likely to be hospital inpatients than those in rural areas (95%CI 1.249-1.385). Age, gender, and marital status were related to the hospital inpatients. The better the education level, the higher the hospital inpatient proportion. Meanwhile, the employed were 40% less likely than the unemployed to be hospital inpatients (95%CI 0.565-0.634). Furthermore, the insured were 3.513 times more likely than the uninsured to be hospital inpatients (95%CI 3.264-3.780).

Conclusion

Seven variables were related to hospital inpatients among the poor in Indonesia: residence, age, gender, marital status, education, employment, and health insurance. Health insurance was the main factor associated with hospital inpatients among low-income people. The government must increase the subsidy quota for the poor's participation in National Health Insurance.

Role of Socioeconomic Status in National Health Insurance Ownership in Indonesia's Rural Areas

BACKGROUND

National Health Insurance (NHI) is one of the Indonesian Government's policies to increase public access to health services. The study analyzed the role of socioeconomic status in NHI ownership in rural Indonesia. Study Design: A cross-sectional study.

METHODS

The study population included residents of rural Indonesia. The study examined secondary data from the survey entitled "Abilities and Willingness to Pay, Fee, and Participant Satisfaction in Implementing National Health Insurance in Indonesia in 2019", involving 33225 respondents representing Indonesia's rural areas. The study was conducted from March to December 2019. The variables analyzed included NHI, socioeconomic level, age group, gender, education level, employment status, and marital status. In the final step, the study employed binary logistic regression to explain the relationship between socioeconomic status and NHI ownership.

RESULTS

The results show that 63.8% of the population in rural Indonesia participated in the NHI. The poorer residents were 1.235 times more likely to have NHI than the most impoverished population (AOR 1.235; 95% CI 1.234-1.237). People with middle wealth status were 1.086 times more likely to have NHI than the poorest (AOR 1.086; 95% CI 1.085-1.087). The richer residents were 1.134 times more likely to have NHI than the poorest (AOR 1.134; 95% CI 1.133-1.136). The richest residents were 1.078 times more likely to have NHI than the poorest residents (AOR 1.078; 95% CI 1.077-1.079).

CONCLUSION

The study concluded that socioeconomic status is related to NHI ownership in rural Indonesia. The analysis indicated that all socioeconomic categories were more likely to become NHI participants than the poorest in Indonesia.

The Role of Travel Time on Hospital Utilization in the Islands Area: A Cross-Sectional Study in the Maluku Region, Indonesia, in 2018

Background

Maluku region is one of the vulnerable areas in Indonesia, and this region has extreme geographical conditions with thousands of islands. The study aims to analyze the role of travel time to a hospital in the Maluku region in Indonesia.

Material and Methods

This cross-sectional study analyzed the 2018 Indonesian Basic Health Survey data. The research included 14,625 respondents by stratification and multistage random sampling. The study used hospital utilization as an outcome variable and the travel time to the hospital as an exposure variable. Moreover, the study employed nine control variables: province, residence, age, gender, marital status, education, employment, wealth, and health insurance. The study performed binary logistic regression to interpret the data in the final analysis.

Results

The result shows a relationship between travel time and hospital utilization. Someone with a travel time of 30 min or less to the hospital has a 1.792 (95% CI 1.756-1.828) higher probability than those with a travel time of more than 30 min. The results of this analysis find that shorter travel time to the hospital has a better possibility of hospital utilization. In addition, the study also found eight control variables to have a significant relationship with hospital utilization.

Conclusion

Shorter travel time to the hospital is more likely to be utilized in the Maluku region.

Predictors of national health insurance membership among the poor with different education levels in Indonesia

BACKGROUND

Indonesia has made significant progress in expanding universal health coverage (UHC) through its National Health Insurance (NHI) mechanism. However, in the context of NHI implementation in Indonesia, socioeconomic disparities caused its subpopulations to have different literacy of NHI concepts and procedures, increasing the risk of healthcare access inequities. Hence, the study aimed to analyse the predictors of NHI membership among the poor with different education levels in Indonesia.

METHODS

This study used the secondary dataset of the nationwide survey "Abilities and Willingness to Pay, Fee, and Participant Satisfaction in implementing National Health Insurance in Indonesia in 2019" by The Ministry of Health of the Republic of Indonesia. The study population was the poor population in Indonesia and included a weighted sample of 18,514 poor people. The study used NHI membership as a dependent variable. Meanwhile, the study analysed seven independent variables: wealth, residence, age, gender, education, employment, and marital status. In the final step of the analysis, the study used binary logistic regression.

RESULTS

The results show that the NHI membership among the poor population tends to be higher among those who have higher education, live in urban areas, are older than 17 years old, are married and are wealthier. The poor population with higher education levels is more likely to become NHI members than those with lower education. Their residence, age, gender, employment, marital status, and wealth also predicted their NHI membership. Poor people with primary education are 1.454 times more likely to be NHI members than those without education (AOR 1.454; 95% CI 1.331-1.588). Meanwhile, those with secondary education are 1.478 times more likely to be NHI members than those with no education (AOR 1.478; 95% CI 1.309-1.668). Moreover, higher education is 1.724 times more likely to result in being an NHI member than no education (AOR 1.724; 95% CI 1.356-2.192).

CONCLUSION

Education level, residence, age, gender, employment, marital status, and wealth predict NHI membership among the poor population. Since significant differences exist in all of those predictors among the poor population with different education levels, our findings highlighted the importance of government investment in NHI, which must be supported with investment in the poor population's education.

Hospital utilization among urban poor in Indonesia in 2018: is government-run insurance effective?

BACKGROUND

An urban poor is a vulnerable group that needs government financing support to access health services. Once they are sick, they will fall deeper into poverty. The study aims to analyze the effectiveness of government-run insurance in hospital utilization in urban poor in Indonesia.

METHODS

The research analyzed the 2018 Indonesian Basic Health Survey data. This cross-sectional survey collected 75,970 participants through stratification and multistage random sampling. Meanwhile, the study employed hospital utilization as an outcome variable and health insurance ownership as an exposure variable. Moreover, the study looked at age, gender, marital status, education, and occupation as control factors. The research employed a binary logistic regression to evaluate the data in the final step.

RESULTS

The results show that someone with government-run insurance is 4.261 times more likely than the uninsured to utilize the hospital (95% CI 4.238-4.285). Someone with private-run insurance is 4.866 times more likely than the uninsured to use the hospital (95% CI 4.802-4.931). Moreover, someone with government-run and private-run insurance has 11.974 times more likely than the uninsured to utilize the hospital (95% CI 11.752-12.200).

CONCLUSION

The study concluded that government-run insurance is more effective than the uninsured in improving hospital utilization among the urban poor in Indonesia. Meanwhile, private-run is more effective than government-run and uninsured in improving hospital utilization among the urban poor in Indonesia. Moreover, the most effective is to combine the kind of health insurance ownership (government-run and private-run).

Regional disparities in hospital utilisation in Indonesia: a cross-sectional analysis data from the 2018 Indonesian Basic Health Survey

OBJECTIVES

Policymakers must ensure that the entire population has equal access to health services, and efforts to minimise inequalities are needed. This study aimed to analyse the regional disparities in hospital utilisation in Indonesia.

DESIGN

A cross-sectional study analysing secondary data from the 2018 Indonesian Basic Health Survey.

SETTING

National-level survey data from Indonesia.

PARTICIPANTS

A total of 629 370 participants were included in the study.InterventionWe employed no interventionPrimary and secondary outcome measuresThe primary outcome was hospital utilisation. Aside from region, we utilise residence type, age, gender, marital status, educational level, occupation, wealth, insurance and travel time as control variables. We used binary logistic regression in the final analysis RESULTS: The respondents in Sumatra were 1.079 times (95% CI 1.073 to 1.085) more likely than those in Papua to use the hospital. Furthermore, compared with the respondents in Papua, those in the Java-Bali region (1.075 times, 95% CI 1.069 to 1.081), Nusa Tenggara (1.106 times, 95% CI 1.099 to 1.113), Sulawesi (1.008 times, 95% CI 1.002 to 1.014) and Kalimantan (1.212 times, 95% CI 1.205 to 1.219) were more likely to use the hospital. However, those in Maluku were less likely than those in Papua to use the hospital (0.827 times, 95% CI 0.820 to 0.835). Six demographic variables (age, gender, marital status, educational level, occupation and wealth) and three other control variables (residence type, insurance and travel time to the hospital) were found to be associated with hospital utilisation.

CONCLUSIONS

Our findings highlight the existence of regional disparities in hospital utilisation in Indonesia.

Policy to expand hospital utilization in disadvantaged areas in Indonesia: who should be the target?

BACKGROUND

The disadvantaged areas are one of the government's focuses in accelerating development in Indonesia, including the health sector. The study aims to determine the target for expanding hospital utilization in disadvantaged areas in Indonesia.

METHODS

The study employed the 2018 Indonesian Basic Health Survey data. This cross-sectional study analyzed 42,644 respondents. The study used nine independent variables: residence, age, gender, marital, education, employment, wealth, insurance, and travel time, in addition to hospital utilization, as a dependent variable. The study employed binary logistic regression to evaluate the data.

RESULTS

The results found that average hospital utilization in disadvantaged areas in Indonesia in 2018 was 3.7%. Urban areas are 1.045 times more likely than rural areas to utilize the hospital (95% CI 1.032-1.058). The study also found age has a relationship with hospital utilization. Females are 1.656 times more likely than males to use the hospital (95% CI 1.639-1.673). Moreover, the study found marital status has a relationship with hospital utilization. The higher the education level, the higher the hospital utilization. Employed individuals have a 0.748 possibility to use the hospital compared with those unemployed (95% CI 0.740-0.757). Wealthy individuals have more chances of using the hospital than poor individuals. Individuals with all insurance types are more likely to utilize the hospital than those uninsured. Individuals with travel times of ≤ 1 h are 2.510 more likely to use the hospital than those with > 1 h (95% CI 2.483-2.537).

CONCLUSION

The specific targets to accelerate the increase in hospital utilization in disadvantaged areas in Indonesia are living in a rural area, being male, never in a union, having no education, being employed, being the poorest, uninsured, and having a travel time of > 1 h. The government should make a policy addressing the problem based on the research findings.

The Role of Government-run Insurance in Primary Health Care Utilization: A Cross-Sectional Study in Papua Region, Indonesia, in 2018

Health development in the Papua region often lags behind other areas of Indonesia. The study aims to analyze the role of government-run insurance in primary health care utilization in the Papua region, Indonesia. The study examined 17,879 Papuan. The study used primary health care utilization as an outcome variable and health insurance ownership as an exposure variable. The study also employed nine control variables: province, residence, age, gender, marital status, education, employment, wealth, and travel time to primary health care. The research employed data using binary logistic regression in the final analysis. The results show that Papuans with government-run insurance were three times more likely to utilize primary health care than uninsured Papuans (AOR 3.081; 95% CI 3.026-3.137). Meanwhile, Papuan with private-run insurance were 0.133 times less likely to utilize primary health care than uninsured Papuans (AOR 0.133; 95% CI 0.109-0.164). Moreover, Papuans who have two types of health insurances (government-run and private-run) were 1.5 times more likely to utilize the primary health care than uninsured Papuan (AOR 1.513; 95% CI 1.393-1.644). The study concluded that government-run insurance increases the chance of primary health care utilization in the Papua region, Indonesia. Government-run insurance has the most prominent role compared to other health insurance categories.

Geographic and Socioeconomic Disparity in Child Undernutrition across 514 Districts in Indonesia

BACKGROUND

Globally, in 2020, 45 million children were estimated to be wasted, and 149 million children under five years of age were estimated to be stunted. Undernutrition makes children in particular much more vulnerable to disease and death. Our study aims to examine geographic and socioeconomic disparities in child undernutrition across 514 districts in Indonesia.

METHODS

Employing both geospatial and quantitative analyses (descriptive statistics and Ordinary Least Squares regressions), we analyzed the disparities in the prevalence of underweight, severe underweight, wasting, severe wasting, stunting, and severe stunting among districts. Child undernutrition data were from Indonesia Basic Health Survey (Riskesdas) 2018, which included a sample of 93,620 children under five years. Socioeconomic data were from the World Bank.

RESULTS

We found a relatively large geographic and socioeconomic disparity in child undernutrition in Indonesia. By region, districts in the Papua region (including Maluku and Nusa Tenggara) had a significantly higher prevalence of underweight and wasting than those in the Java region (including Bali). Districts in Papua had 44%, 121%, 38%, and 57% higher prevalence of underweight, severe underweight, wasting, and severe wasting, respectively. Similarly, the poorest districts had a significantly higher prevalence of underweight, wasting, and stunting than the wealthiest districts. The poorest districts had 30%, 83%, 16%, 21%, and 74% higher prevalence of underweight, severe underweight, wasting, stunting, and severe stunting, respectively. These results were similar among rural districts.

CONCLUSION

There is a significant disparity in child undernutrition across districts in Indonesia. The government needs to prioritize the reduction of child undernutrition, especially in rural areas, districts outside of Java and Bali, and the poorest and least educated areas.

Socioeconomic Disparities in Hospital Utilization Among Female Workers in Indonesia: A Cross-Sectional Study

BACKGROUND

The study aims to analyze the relationship between socioeconomic and hospital utilization among female workers in Indonesia.

METHODS

The study analyzed secondary data from the 2018 Indonesian Basic Health Survey. The study gathered 161 186 female workers through stratification and multistage random sampling. As control factors, the study looked at age, marital status, education, occupation, and health insurance, in addition to the categories of socioeconomic and hospital utilization. The study used binary logistic regression to evaluate the data in the final step.

RESULTS

The result shows female workers with poorer wealth status are 1.142 times more likely than the most impoverished female workers to utilize the hospital (AOR 1.142; 95% CI 1.135-1.148). Female workers with median wealth status are 1.509 times more likely than the poorest female workers to take advantage of the hospital (AOR 1.509; 95% CI 1.501-1.517). Female workers with wealthier wealth status are 1.808 times more likely than the poorest female workers to use the hospital (AOR 1.808; 95% CI 1.799-1.817). The wealthiest female workers are 2.399 times more likely than the poorest female workers to utilize the hospital (2.399; 95% CI 2.387-2.411).

CONCLUSION

The study concluded a relationship between socioeconomic status and hospital utilization among female workers in Indonesia. The better the socioeconomic, the better the hospital utilization.