Including health insurance in poverty measurement: The impact of Massachusetts health reform on poverty

The relationship between health insurance and economic performance: an empirical study based on meta-analysis

Health insurance stands as a pivotal facet of social wellbeing, with profound implications for the overarching landscape of economic development. The existing research, however, lacks consensus on the relationship between health insurance and economic performance and provides no evidence about the magnitude of the correlation. This lack of information seriously impedes the high-quality development of the healthcare system. Therefore, to scientifically elucidate the relationship between the two, this study involved a meta-analysis, analyzing 479 effect values derived from 34 independent research samples. The results reveal a strongly positive correlation between health insurance and economic performance [r = 0.429, 95% CI = (0.381, 0.475)]. Findings show that health insurance in developed countries more effectively fosters economic performance than in developing countries. Moreover, public health insurance exerts a stronger promoting effect on economic performance than commercial health insurance. The relationship between health insurance and economic performance is moderated by data type, research method, country of sample origin, literature type, journal impact factor, publication year, type of health insurance, and the research populations. Based on meta-analysis, this study not only scientifically responds to the controversy of the relationship between health insurance and economic performance, and the magnitude of a correlation, but also further reveals the inner conduction mechanism between the two. Our research findings are meaningful for policymakers to choose an appropriate healthcare strategy according to their unique attributes, propelling sustainable economic development.

Medical insurance, vulnerability to poverty, and wealth inequality

Background

China has made remarkable achievements in alleviating poverty under its current poverty standards. Despite these immense successes, the challenge of consolidating these achievements remains. In reality, health risks are among the significant factors causing rural households to fall into poverty, and medical insurance is the significant factor mitigating household vulnerability to poverty. Therefore, alleviating or guarding against households falling into poverty is essential.

Methods

This paper establishes a multi-equilibrium model that incorporates heterogeneous health risks and medical insurance. Through parameter calibration and value function iteration, numerical solutions are derived.

Results

Heterogeneous health risks significantly increase poverty vulnerability and wealth inequality in rural households. Medical insurance, through its investment incentives and loss compensation effects, efficiently mitigates these issues, especially benefiting those in poorer health. Furthermore, the dual-slanted compensation policy efficiently mitigates the adverse effects of "reverse redistribution."

Conclusion

Medical insurance effectively mitigates household vulnerability to poverty and wealth inequality. Government departments must establish health records for residents. By recognizing variations in health conditions, these departments can provide households with poorer health conditions with a higher medical expense compensation ratio. In addition, the government should further focus medical expense reimbursements toward households on the cusp of escaping poverty to ensure that they are not plunged back (or further) into poverty due to medical expenses.

On the Importance and Intrinsic Difficulties of Incorporating Health Insurance Benefits in Absolute Poverty Trends

CONTEXT

US government poverty measures do not include health insurance in the threshold or health insurance benefits in resources. Yet the 2019 Economic Report of the President presented long-term trends using the full-income poverty measure (FPM), which includes health insurance benefits as resources. A 2021 technical advisory report recommended statistical agencies produce absolute poverty trends with and without health insurance.

METHODS

The authors analyzed the conceptual validity and relevance of long-term absolute poverty trends incorporating health insurance benefits. They estimated the extent to which the FPM credits health insurance benefits with meeting nonhealth needs.

FINDINGS

In FPM estimates, health insurance benefits alone remove many households from poverty. Long-term absolute poverty trends incorporating health insurance benefits have intrinsic difficulties, because health insurance benefits are in-kind, mostly nonfungible, and large, and because health care undergoes substantial technological change-features that interact to undermine validity. Valid poverty measures with health insurance benefits require resources and thresholds consistent at each point in time, while absolute poverty measures require thresholds constant in real terms over time. These goals conflict.

CONCLUSIONS

Statistical agencies should not produce absolute poverty trends incorporating health insurance benefits. Instead, they should focus on less-absolute poverty measures with health insurance benefits.

Perspectives and evaluation on the effect of financial burden relief of medical insurance for people with catastrophic diseases and its influencing factors

Background

Catastrophic disease sufferers face a heavy financial burden and are more likely to fall victim to the "illness-poverty-illness" cycle. Deeper reform of the medical insurance system is urgently required to alleviate the financial burden of individuals with catastrophic diseases.

Methods

Data were obtained from a cross-sectional questionnaire survey conducted in Heilongjiang in 2021, and logistic regression and restricted cubic spline model was used to predict the core factors related to medical insurance that alleviate the financial burden of people with catastrophic diseases.

Results

Overall, 997 (50.92%) medical insurance-related professionals negatively viewed financial burden relief for people with catastrophic diseases. Factors influencing its effectiveness in relieving the financial burden were: whether or not effective control of omissions from medical insurance coverage (OR = 4.04), fund supervision (OR = 2.47) and degree of participation of stakeholders (OR = 1.91). Besides, the reimbursement standards and the regional and population benefit package gap also played a role. The likelihood of financial burden relief increased by 21 percentage points for each unit increase in the level of stakeholder discourse power in reform.

Conclusion

China's current medical insurance policies have not yet fully addressed the needs of vulnerable populations, especially the need to reduce their financial burden continuously. Future reform should focus on addressing core issues by reducing the uninsured, enhancing the width and depth of medical insurance coverage, improving the level and capacity of medical insurance governance that provides more discourse power for the vulnerable population, and building a more responsive and participatory medical insurance governance system.

The Impact of Mobile Payment on Household Poverty Vulnerability: A Study Based on CHFS2017 in China

Changes in digital technology have brought about new opportunities in the field of financial poverty alleviation in China, and mobile payment as a new digital financial model is important in helping families to lift themselves out of poverty effectively and prevent a return to poverty. This paper examines the impact of mobile payment on household poverty vulnerability and the mechanism of action using the China Household Finance Survey (CHFS) 2017 microsurvey data. After adopting the IVprobit model and a series of robustness tests, we found: (1) mobile payment significantly negatively impacts household poverty vulnerability; (2) the mechanism analysis indicates that promoting entrepreneurship and improving risk management capabilities are the main channels through which mobile payment mitigates household poverty vulnerability; (3) household entrepreneurship and entrepreneurial survival significantly reduce the probability of poverty vulnerability; and (4) the probit regression analysis explores how mobile payment has a greater negative impact on poverty vulnerability among low-income, homeless, and relatively backward households in rural or western areas. This work contributes to the literature on the use of electronic communication technology to eradicate poverty and on inclusive finance, providing vital results for other countries to use as an example.

The Effect of the "Triple-Layer Medical Security" Policy on the Vulnerability as Expected Poverty of Rural Households: Evidence from Yunnan Province, China

China launched the "critical battle against poverty" nationwide in 2012. As its main battlefield, Yunnan province promulgated the "triple medical security" (TMS) policy in 2017. This study, based on the pooled cross-section database of 2015-2020 of registered poor households in Yunnan province, employed the logit model to examine the effect of TMS on the vulnerability as expected poverty (VEP) of these households. It found that increasing the reimbursement rates for overall medical expenses and inpatient expenses and decreasing the proportion of out-of-pocket medical payment to income reduced the VEP; increases in the number of sick people in the family increased its VEP, and although the increase in the reimbursement rate for overall medical expenses or for inpatient expenses partially offset the VEP caused by the increase in the number of chronically ill people in the family, the VEP caused by the increase in the number of critically ill people would increase in the short term with the increase in the reimbursement rate for overall medical expenses or for inpatient expenses. The findings help improve policies concerning the medical security and health of the rural poor population, providing theoretical reference and practical guidance for future research.

Measurement and Decomposition of the Health Poverty of Rural Residents in China

Narrowing the health gap and promoting health equality is the key to effectively blocking the intergenerational transmission of rural poverty. Previous studies have mainly focused on the relationship between health and poverty, but assessments of health poverty are lacking, especially with regard to the health poverty of rural residents. Based on China's large sample household survey data, this study uses the Alkire-Foster (AF) method to measure and decompose the health poverty of rural residents. The results show that the health poverty of Chinese rural residents greatly improved from 2016 to 2018. However, significant regional differences exist with regard to the level of health poverty. The marginal contribution of economic poverty alleviation is diminishing; the equalization of health services and security has shifted to a policy focus. Community environmental management has also become an important aspect of health poverty governance, and individual health literacy and behavior have played an important role in endogenous poverty alleviation. Ultimately, this paper offers some insightful policy implications. This study extends the multidimensional poverty measurement system and reveals the relationship between health poverty and regional economic and social development. The findings also enhance the understanding of the health poverty of rural residents in developing countries.

Examining Poverty Reduction of Poverty-Stricken Farmer Households under Different Development Goals: A Multiobjective Spatio-Temporal Evolution Analysis Method

Accurately identifying the degree of poverty and poverty-causing factors of poverty-stricken farmer households is the first key step to alleviating absolute and relative poverty. This paper introduces a multiobjective spatio-temporal evolution analysis method to examine poverty reduction of poverty-stricken farmer households under different development goals. A G-TOPSIS model was constructed to evaluate poverty-stricken households under short-, medium-, and long-term development goals. Then, GIS analysis methods were employed to reveal the spatio-temporal distribution of poverty-stricken households, and poverty causing factors were detected using the obstacle degree model. Taking Fugong County in Yunnan Province, China, as an example, the empirical results show that: (1) Great progress has been made in poverty reduction during the study period; however, some farmer households which have escaped absolute poverty are still in relative poverty and are still highly vulnerable. (2) Farmers with higher achievement rates under three different development goals are mainly distributed in the central and northern regions of study area, with a pattern of high-high agglomeration under the medium and low development goals, while low-low agglomeration mostly appears in central-southern regions. (3) Under the short-term development goals, the main poverty-causing factors are per capita net income, safe housing, sanitary toilets, years of education of labor force and family health. Under the medium- and long-term goals, per capita net income, labor force education and safe housing are the development limitations. (4) Infrastructure and public service are crucial to ending absolute poverty, and the endogenous force of regional development should be applied to alleviate the relative poverty through sustainable development industries and high-quality national education.

Participating in health insurance and health improvements for the relatively poor population: A propensity score analysis

This study examined the causal relationship between participation in the New Rural Cooperative Medical Scheme (NRCMS) and health status among relatively poor population in rural China. Data were obtained from the China Family Panel Studies (CFPS) conducted in 2018, which contained 4,507 samples. This study used propensity score matching (PSM) to examine the net effect of participation in the NRCMS on the health of the relatively poor population, and this effect was tested for equilibrium using nearest neighbor matching, radius matching, and kernel matching. This study showed that participation in the NRCMS has a significant and positive effect on the health status of the relatively poor population and the positive health effect may come from three channels, including the increased frequency of physical activity, the fact that an individual is more likely to seek medical care at a lower level of visit, and a plan to reduce health care expenditures.

Does Social Medical Insurance Achieve a Poverty Reduction Effect in China?

This paper aims to explore the impact of social medical insurance (SMI) on poverty reduction (PR) in China. Considering the time-varying characteristics of factors, this paper uses the bootstrap Granger full sample causality and subsample rolling window model to find the relationship between SMI and PR. The results highlight that in some periods, there is a bidirectional causal link between SMI and PR. Influenced by the medical insurance reform and medication measures. Social medical insurance does not have a positive impact on poverty reduction in some periods. These results are supported by the Utility Maximization Model of Insurance Consumption, which highlights that individuals make utility maximization choices when choosing insurance. The effect of medical insurance on poverty alleviation depends on whether an individual's investment in medical insurance can maximize its utility. If the proportion of social medical insurance reimbursement is too low, individuals will give up buying social medical insurance. Thus, the anti-poverty effect of social medical insurance is difficult to achieve. Therefore, authorities need to pay attention to specific contexts and social medical insurance policies and further improve the social medical insurance system to promote the realization of the anti-poverty of social medical insurance.

Improving estimates of Medicaid's effect on poverty: Measures and counterfactuals

OBJECTIVE

To re-evaluate the effect of Medicaid on poverty using a poverty measure that accounts for health insurance needs and benefits and an evaluation approach that reflects disparities in access to alternative coverage.

DATA SOURCES

The Current Population Survey (CPS) for calendar year 2015.

STUDY DESIGN

We estimate the effect of losing Medicaid on poverty, combining two previous approaches: (1) A propensity impact, which simulates a no-Medicaid counterfactual incorporating changes to health insurance and medical out-of-pocket spending, using the Supplemental Poverty Measure (SPM). This measure does not reflect a need for health care access nor how health benefits meet that need. (2) An accounting impact, which assumes that those losing Medicaid remain uninsured and does not incorporate any behavioral changes, using the health-inclusive poverty measure (HIPM). This measure includes a need for health insurance in the threshold and health insurance benefits in resources.

DATA COLLECTION/EXTRACTION METHODS

Not applicable.

PRINCIPAL FINDINGS

Using the propensity-matched approach, we attributed a 2.5 percentage point reduction in health-inclusive poverty among those younger than age 65 to the Medicaid program, between the 1.0-point SPM propensity-match impact and the 3.9-point HIPM accounting impact. Medicaid's antipoverty impact and HIPM-SPM differences are greater among those who would become uninsured. HIPM propensity-matched estimates reveal much larger impacts of Medicaid on poverty disparities linked to race/ethnicity and single parenthood than SPM-based propensity estimates.

CONCLUSIONS

Both the poverty measure and the method used to estimate the counterfactual make substantial, policy-relevant differences to estimates of Medicaid's impact on poverty. A poverty measure that fails to incorporate health insurance needs and benefits substantially underestimates Medicaid's effect. Failing to consider adjustments in insurance coverage and out-of-pocket spending substantially overestimates Medicaid's effect and underestimates its reduction of disparities.

The Affordable Care Act Reduced Income Inequality In The US

Income inequality estimates based on traditional poverty measures do not capture the effects of health care spending and health insurance. To explore the distributional effects of the Affordable Care Act's (ACA's) expansion of health benefits and the resulting income inequality, this study used alternative income measures that incorporate the value of the ACA's health insurance changes under the law. The study simulated the impact of the ACA on income inequality in 2019 compared with a scenario without the ACA. We found that the ACA reduced income inequality and that the decrease was much larger in states that expanded Medicaid than in states that did not. We also decomposed the effect of the ACA on inequality by race/ethnicity, age, and family educational attainment. The ACA reduced inequality both across groups and within these groups. With efforts to repeal the ACA-specifically, California v. Texas-having shifted from Congress to the courts, it remains important to consider the consequences of fully repealing the ACA, which would likely reverse reduced inequality observed under the law.