A STUDY OF CATASTROPHIC HEALTH EXPENDITURES IN INDIA - EVIDENCE FROM NATIONALLY REPRESENTATIVE SURVEY DATA: 2014-2018

Catastrophic health expenditure of inpatients in emerging economies: evidence from the Indian subcontinent

BACKGROUND

Catastrophic health expenditures condensed the vital concern of households struggling with notable financial burdens emanating from elevated out-of-pocket healthcare expenditures. In this regard, this study investigated the nature and magnitude of inpatient healthcare expenditure in India. It also explored the incidence and determinants of inpatient catastrophic health expenditure.

METHODOLOGY

The study used the micro-level data collected in the 75th Round of the National Sample Survey on 93 925 households in India. Descriptive statistics were used to examine the nature, magnitude and incidence of inpatient healthcare expenditure. The heteroscedastic probit model was applied to explore the determinants of inpatient catastrophic healthcare expenditure.

RESULTS

The major part of inpatient healthcare expenditure was composed of bed charges and expenditure on medicines. Moreover, results suggested that Indian households spent 11% of their monthly consumption expenditure on inpatient healthcare and 28% of households were grappling with the complexity of financial burden due to elevated inpatient healthcare. Further, the study explored that bigger households and households having no latrine facilities and no proper waste disposal plans were more vulnerable to facing financial burdens in inpatient healthcare activity. Finally, the result of this study also ensure that households having toilets and safe drinking water facilities reduce the chance of facing catastrophic inpatient health expenditures.

CONCLUSIONS

A significant portion of monthly consumption expenditure was spent on inpatient healthcare of households in India. It was also conveyed that inpatient healthcare expenditure was a severe burden for almost one fourth of households in India. Finally, it also clarified the influence of socio-economic conditions and sanitation status of households as having a strong bearing on their inpatient healthcare.

Exploring the road to public healthcare accessibility: a qualitative study to understand healthcare utilization among hard-to-reach groups in Kerala, India

BACKGROUND

Kerala, a southern state in India, is known to be atypical due to its high literacy rate and advanced social development indicators. Facing competition from a dominant private healthcare system, recent government health system reforms have focused on providing free, high-quality universal healthcare in the public sector. We carried out an analysis to ascertain the initial impacts of these measures among 'hard to reach groups' as part of a larger health policy and systems research study, with a focus on public sector health service utilisation.

METHODS

We conducted Focus Group Discussions (FGDs) among identified vulnerable groups across four districts of Kerala between March and August of 2022. The FGDs explored community perspectives on the use of public healthcare facilities including enablers and barriers to healthcare access. Transliterated English transcripts were coded using ATLAS.ti software and thematically analyzed using the AAAQ framework, supplemented with inductive code generation.

RESULTS

A total of 34 FGDs were conducted. Availability and cost-effectiveness were major reasons for choosing public healthcare, with the availability of public insurance in inpatient facilities influencing this preference. However, accessibility of public sector facilities posed challenges due to long journeys and queues. Uneven roads and the non-availability of public transport further restricted access. Gaps in acceptability were also observed: participants noted the need for the availability of special treatments available, reduced waiting times for special groups like those from tribal communities or the elderly mindful of their relatively greater travel and need for prompt care. Although quality improvements resulting from health reform measures were acknowledged, participants articulated the need for further enhancements in the availability and accessibility of services so as to make public healthcare systems truly acceptable.

CONCLUSION

The 'Kerala Model of Development' has been applauded internationally for its success in recent years. However, this has not inured the state from the typical barriers to public sector health care use articulated by participants in the study, which match global evidence. In order to deepen the impact of public sector reforms, the state must try to meet service user expectations- especially among those left behind. This requires attention to quality, timeliness, outreach and physical access. Longer term impacts of these reforms - as we move to a post-COVID scenario - should also be evaluated.

An Examination of Inter-State Variation in Utilization of Healthcare Services, Associated Financial Burden and Inequality: Evidence from Nationally Representative Survey in India

This study examines the health care utilization pattern, associated financial catastrophes, and inequality across Indian states to understand the subnational variations and aid the policy makers in this regard. Data from recent National Sample Survey (2017-2018), titled, "Household Social Consumption: Health," covering 113,823 households, was employed in the study. Descriptive statistics, Erreygers concentration index (CI), and recentered influence function decomposition were applied in the study. We found that, in India, 7 percent of households experienced catastrophic health expenditure (CHE) and 1.9 percent of households were pushed below poverty line due to out-of-pocket expenditure on hospitalization. Notably, outpatient care was more burdensome (CHE: 12.1%; impoverishment: 4%). Substantial interstate variations were observed, with high financial burden in poorer states. Utilization of health care services from private health care providers was pro-rich (hospitalization CI 0.31; outpatient CI 0.10), while the occurrence of CHE incidence was pro-poor (hospitalization CI -0.10; outpatient CI -0.14). Education level, economic status, health insurance, and area of residence contributed significantly to inequalities in utilization of health care services from private providers and financial burden. The high financial burden of seeking health care necessitates the need to increase public health spending and strengthen public health infrastructure. Also, concerted efforts directed towards increasing awareness about health insurance and introducing comprehensive health insurance products (covering both inpatient and outpatient services) are imperative to augment financial risk protection in India.

Measurement of Catastrophic Health Expenditure in India: A Systematic Review and Meta-Analysis

INTRODUCTION

The escalating burden of catastrophic health expenditure (CHE) poses a significant threat to individuals and households in India, where out-of-pocket expenditure (OOP) constitutes a substantial portion of healthcare financing. With rising OOP in India, a proper measurement to track and monitor CHE due to health expenditure is of utmost important. This study focuses on synthesizing findings, understanding measurement variations, and estimating the pooled incidence of CHE by health services, reported diseases, and survey types.

METHOD

Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a thorough search strategy was employed across multiple databases, between 2010 and 2023. Inclusion criteria encompassed observational or interventional studies reporting CHE incidence, while exclusion criteria screened out studies with unclear definitions, pharmacy revenue-based spending, or non-representative health facility surveys. A meta-analysis, utilizing a random-effects model, assessed the pooled CHE incidence. Sensitivity analysis and subgroup analyses were conducted to explore heterogeneity.

RESULTS

Out of 501 initially relevant articles, 36 studies met inclusion criteria. The review identified significant variations in CHE measurements, with incidence ranging from 5.1% to 69.9%. Meta-analysis indicated the estimated incidence of CHE at a 10% threshold is 0.30 [0.25-0.35], indicating a significant prevalence of financial hardship due to health expenses. The pooled incidence is estimated by considering different sub-groups. No statistical differences were found between inpatient and outpatient CHE. However, disease-specific estimates were significantly higher (52%) compared to combined diseases (21%). Notably, surveys focusing on health reported higher CHE (33%) than consumption surveys (14%).

DISCUSSION

The study highlights the intricate challenges in measuring CHE, emphasizing variations in recall periods, components considered in out-of-pocket expenditure, and diverse methods for defining capacity to pay. Notably, the findings underscore the need for standardized definitions and measurements across studies. The lack of uniformity in reporting exacerbates the challenge of comparing and comprehensively understanding the financial burden on households.

Relationship between the cost of illness and quality of life among adolescents with type 1 diabetes-a mixed method study

Type 1 diabetes mellitus (T1DM) is a major problem worldwide that affects the quality of life, well-being of patients and their families. This study aimed to determine the relationship between the cost of illness and quality of life among patients with T1DM. A concurrent, parallel, mixed-method study of 113 adolescents with T1DM registered in public and private hospitals in the Mysore district was conducted by obtaining data related to the cost of illness and quality of life using a validated Diabetes-Specific Quality of Life (DSQoL) questionnaire. Thematic analysis was used to identify the themes. There was a significant association amonghealth insurance status, treatment facility type, catastrophic health expenditure (CHE), and cost of illness. The CHE proportion was32.7%. Financial sources for treatment were met primarily by borrowing money with interest (58 patients, 51.3%), followed by individualincome (40 patients, 35.3%), contributions from friends and relatives (10 patients, 8.8%), and selling of assets (5 patients, 4.4%). The monthly health expenditures of approximately 22 (19.46%) households were greater than their monthly incomes. There was a positive correlation (rvalue of 0.979) between the cost of treatment and the DSQoL score, and this correlation was statistically significant, with a p value < 0.001. The higher theDSQoL score was, the worse the quality of life and the worse the well-being of T1DM patients. Three themes were identified: the impact of financial cost on family coping, the impact of financial cost on seeking care and the emotional burden of financial cost. There was a statistically significant positive correlation between the cost of treatment and the DSQoLscore. Adolescents with T1DM who had greatertreatment costs had worseDSQoL, and significantly lower health expenses were observed among adolescentswho had health insurance. Cost of illness acts as a barrier to treatment and placesa burden on patients and their families.

Decomposing the inequalities in the catastrophic health expenditures on the hospitalization in India: empirical evidence from national sample survey data

Introduction

Sustainable Development Goal (SDG) Target 3.8.2 entails financial protection against catastrophic health expenditure (CHE) by reducing out-of-pocket expenditure (OOPE) on healthcare. India is characterized by one of the highest OOPE on healthcare, in conjunction with the pervasive socio-economic disparities entrenched in the population. As a corollary, India has embarked on the trajectory of ensuring financial risk protection, particularly for the poor, with the launch of various flagship initiatives. Overall, the evidence on wealth-related inequities in the incidence of CHE in low- and middle-Income countries has been heterogenous. Thus, this study was conducted to estimate the income-related inequalities in the incidence of CHE on hospitalization and glean the individual contributions of wider socio-economic determinants in influencing these inequalities in India.

Methods

The study employed cross-sectional data from the nationally represented survey on morbidity and healthcare (75th round of National Sample Survey Organization) conducted during 2017-2018, which circumscribed a sample size of 1,13,823 households and 5,57,887 individuals. The inequalities and need-adjusted inequities in the incidence of CHE on hospitalization care were assessed via the Erreygers corrected concentration index. Need-standardized concentration indices were further used to unravel the inter- and intra-regional income-related inequities in the outcome of interest. The factors associated with the incidence of CHE were explored using multivariate logistic regression within the framework of Andersen's model of behavioral health. Additionally, regression-based decomposition was performed to delineate the individual contributions of legitimate and illegitimate factors in the measured inequalities of CHE.

Results

Our findings revealed pervasive wealth-related inequalities in the CHE for hospitalization care in India, with a profound gap between the poorest and richest income quintiles. The negative value of the concentration index (EI: -0.19) indicated that the inequalities were significantly concentrated among the poor. Furthermore, the need-adjusted inequalities also demonstrated the pro-poor concentration (EI: -0.26), denoting the unfair systemic inequalities in the CHE, which are disadvantageous to the poor. Multivariate logistic results indicated that households with older adult, smaller size, vulnerable caste affiliation, poorest income quintile, no insurance cover, hospitalization in a private facility, longer stay duration in the hospital, and residence in the region at a lower level of epidemiological transition level were associated with increased likelihood of incurring CHE on hospitalization. The decomposition analysis unraveled that the contribution of non-need/illegitimate factors (127.1%) in driving the inequality was positive and relatively high vis-à-vis negative low contribution of need/legitimate factors (35.3%). However, most of the unfair inequalities were accounted for by socio-structural factors such as the size of the household and enabling factors such as income group and utilization pattern.

Conclusion

The study underscored the skewed distribution of CHE as the poor were found to incur more CHE on hospitalization care despite the targeted programs by the government. Concomitantly, most of the inequality was driven by illegitimate factors amenable to policy change. Thus, policy interventions such as increasing the awareness, enrollment, and utilization of Publicly Financed Health Insurance schemes, strengthening the public hospitals to provide improved quality of specialized care and referral mechanisms, and increasing the overall budgetary share of healthcare to improve the institutional capacities are suggested.

Examining the factors contributing to a reduction in hardship financing among inpatient households in India

In India, the rising double burden of diseases and the low fiscal capacity of the government forces people to resort to hardship financing. This study aimed to examine the factors contributing to the reduction in hardship financing among inpatient households in India. The study relies on two rounds of National Sample Surveys with a sample of 34,478 households from the 71st round (2014) and 56,681 households from the 75th round (2018). We employed multivariable logistic regression and multivariate decomposition analyses to explore the factors associated with hardship financing in Indian households with hospitalized member(s) and assess the contributing factors to the reduction in hardship financing between 2014 and 2018. Notably, though hardship financing for inpatient households has decreased between 2014 and 2018, households with catastrophic health expenditure (CHE) had higher odds of hardship financing than those without CHE. While factors such as CHE, prolonged hospitalization, and private hospitals had impoverishing effects on hardship financing in 2014 and 2018, the decomposition model showed the potential of CHE (32%), length of hospitalization (32%), and private hospitals (24%) to slow down this negative impact over time. The findings showed the potential for further improvements in financial health protection for inpatient care over time, and underscore the need for continuing efforts to strengthen the implementation of public programs and schemes in India such as Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PMJAY).

Do hospitalizations push households into poverty in India: evidence from national data

Introduction

High percentage of OOP (Out-of-Pocket) costs can lead to poverty and exacerbate existing poverty, with 21.9% of India's 1.324 billion people living below the poverty line. Factors such as increased patient cost-sharing, high-deductible health plans, and expensive medications contribute to high OOP costs. Understanding the poverty-inducing impact of healthcare payments is essential for formulating effective measures to alleviate it.

Methods

The study used data from the 75th round of the National Sample Survey Organization (Household Social Consumption in India: Health) from July 2017-June 2018, focusing on demographic-socio-economic characteristics, morbidity status, healthcare utilization, and expenditure. The analysis included 66,237 hospitalized individuals in the last 365 days. Logistic regression model was used to examine the impact of OOP expenditures on impoverishment.

Results

Logistic regression analysis shows that there is 0.2868 lower odds of experiencing poverty due to OOP expenditures in households where there is the presence of at least one child aged 5 years and less present in the household compared to households who do not have any children. There is 0.601 higher odds of experiencing poverty due to OOP expenditures in urban areas compared to households in rural areas. With an increasing duration of stay in the hospital, there is a higher odds of experiencing poverty due to OOP health expenditures. There is 1.9013 higher odds of experiencing poverty due to OOP expenditures if at least one member in the household used private healthcare facility compared to households who never used private healthcare facilities.

Conclusion

In order to transfer demand from private to public hospitals and reduce OOPHE, policymakers should restructure the current inefficient public hospitals. More crucially, there needs to be significant investment in rural areas, where more than 70% of the poorest people reside and who are more vulnerable to OOP expenditures because they lack coping skills.

Are institutional deliveries equitable in the southern states of India? A benefit incidence analysis

BACKGROUND

Despite a commendable rise in the number of women seeking delivery care at public health institutions in South India, it is unclear if the benefit accrues to wealthier or poorer socio-economic groups. The study's aim was to investigate at how the public subsidy is distributed among Indian women who give birth in public hospitals in the southern regions.

METHODS

Data from the Indian Demographic Health Survey's fifth wave (NFHS-5, 2019-21) was used in this study. A total of 22, 403 were institutional deliveries across all the southern states of India were included. Out-of-pocket expenditure (OOPE) on childbirth in health institutions was the outcome variable. We used summary statistics, Benefits Incidence Analysis (BIA), concentration index (CI), and concentration curve (CC) were used.

RESULTS

Most women in the lowest, poorest, and medium quintiles of wealth opted to give birth in public facilities. In contrast, about 69% of mothers belonging to highest quintile gave birth in private health institutions. The magnitude of CI and CC of institutional delivery indicates that public sector usage was concentrated among poorer quintiles [CIX: - 0.178; SE: 0.005; p < 0.001] and private sector usage was concentrated among wealthier quintiles [CIX: 0.239; SE: 0.006; p < 0.001]. Benefit incidence analyses suggest that middle quintile of women received the maximum public subsidy in primary health centres (33.23%), followed by richer quintile (25.62%), and poorer wealth quintiles (24.84%). These pattern in the secondary health centres was similar.

CONCLUSION

Poorer groups utilize the public sector for institutional delivery in greater proportions than the private sector. Middle quintiles seem to benefit the most from public subsidy in terms of the median cost of service and non-payment. Greater efforts must be made to understand how and why these groups are being left behind and what policy measures can enhance their inclusion and financial risk protection.

Assessing Health Seeking Behaviors and Economic Consequences of Morbidity in Indian Construction Workers: A Multicenter Study

Background

Construction laborers succumb to poor health due to the inherent workplace health hazards and poor socio-economic living conditions. With rising healthcare expenses, the increased risk of poor health may aggravate their economic status, pushing them deeper into poverty.

Settings and Design

The current cross-sectional multicenter study comprehensively investigated the determinants of health, health-seeking behavior, and poor economic impact regarding catastrophic health expenditure (CHE) among construction laborers.

Methods and Material

We collected details on illnesses among self and family members of the construction laborers that required healthcare visits during the previous year and their approximate expenses. Among the 1110 participants with complete data, 37% reported illness requiring a healthcare visit either for self or a family member.

Results

Regression models to ascertain demographic and living condition determinants of perceived illness revealed an increased risk of illness when the kitchen is shared with the living space (OR = 1.87) and use unhygienic smoky cooking fuels (OR = 1.87). More than 25% of those who reported illness incurred CHE.

Conclusion

We conclude that the frequency of perceived illness and the economic impact, i.e., CHE is relatively higher among the construction laborers. Our results demonstrate that poor living conditions add to the burden of morbidity in construction workers and families. Providing healthcare coverage for this population and engaging and educating them about affordable healthcare are necessary future steps to prevent the worsening of the economic situation.

Cost of acute respiratory illness episode and its determinants among community-dwelling older adults: a four-site cohort study from India

Introduction

Advocacy for the provision of public health resources, including vaccine for the prevention of acute respiratory illnesses (ARIs) among older adults in India, needs evidence on costs and benefits. Using a cohort of community-dwelling adults aged 60 years and older in India, we estimated the cost of ARI episode and its determinants.

Methods

We enrolled 6016 participants in Ballabgarh, Chennai, Kolkata and Pune from July 2018 to March 2020. They were followed up weekly to identify ARI and classified them as acute upper respiratory illness (AURI) or pneumonia based on clinical features based on British Thoracic Society guidelines. All pneumonia and 20% of AURI cases were asked about the cost incurred on medical consultation, investigation, medications, transportation, food and lodging. The cost of services at public facilities was supplemented by WHO-Choosing Interventions that are Cost-Effective(CHOICE) estimates for 2019. Indirect costs incurred by the affected participant and their caregivers were estimated using human capital approach. We used generalised linear model with log link and gamma family to identify the average marginal effect of key determinants of the total cost of ARI.

Results

We included 2648 AURI and 1081 pneumonia episodes. Only 47% (range 36%-60%) of the participants with pneumonia sought care. The mean cost of AURI episode was US$13.9, while that of pneumonia episode was US$25.6, with indirect costs comprising three-fourths of the total. The cost was higher among older men by US$3.4 (95% CI: 1.4 to 5.3), those with comorbidities by US$4.3 (95% CI: 2.8 to 5.7) and those who sought care by US$17.2 (95% CI: 15.1 to 19.2) but not by influenza status. The mean per capita annual cost of respiratory illness was US$29.5.

Conclusion

Given the high community disease and cost burden of ARI, intensifying public health interventions to prevent and mitigate ARI among this fast-growing older adult population in India is warranted.

Regional catastrophic health expenditure and health inequality in China

Background

Catastrophic health expenditures (CHE) can trigger illness-caused poverty and compound poverty-caused illness. Our study is the first regional comparative study to analyze CHE trends and health inequality in eastern, central and western China, exploring the differences and disparities across regions to make targeted health policy recommendations.

Methods

Using data from China's Household Panel Study (CFPS), we selected Shanghai, Henan and Gansu as representative eastern-central-western regional provinces to construct a unique 5-year CHE unbalanced panel dataset. CHE incidence was measured by calculating headcount; CHE intensity was measured by overshoot and CHE inequality was estimated by concentration curves (CC) and the concentration index (CI). A random effect model was employed to analyze the impact of household head socio-economic characteristics, the household socio-economic characteristics and household health utilization on CHE incidence across the three regions.

Results

The study found that the incidence and intensity of CHE decreased, but the degree of CHE inequality increased, across all three regions. For all regions, the trend of inequality first decreased and then increased. We also revealed significant differences across the eastern, central and western regions of China in CHE incidence, intensity, inequality and regional differences in the CHE influencing factors. Affected by factors such as the gap between the rich and the poor and the uneven distribution of medical resources, families in the eastern region who were unmarried, use supplementary medical insurance, and had members receiving outpatient treatment were more likely to experience CHE. Families with chronic diseases in the central and western regions were more likely to suffer CHE, and rural families in the western region were more likely to experience CHE.

Conclusions

The trends and causes of CHE varied across the different regions, which requires a further tilt of medical resources to the central and western regions; improved prevention and financial support for chronic diseases households; and reform of the insurance reimbursement policy of outpatient medical insurance. On a regional basis, health policy should not only address CHE incidence and intensity, but also its inequality.

Socioeconomic and geographic variation in coverage of health insurance across India

Introduction

In India, regular monitoring of health insurance at district levels (the most essential administrative unit) is important for its effective uptake to contain the high out of pocket health expenditures. Given that the last individual data on health insurance coverage at district levels in India was in 2016, we update the evidence using the latest round of the National Family Health Survey conducted in 2019-2021.

Methods

We use the unit records of households from the latest round (2021) of the nationally representative National Family Health Survey to calculate the weighted percentage (and 95% CI) of households with at least one member covered by any form of health insurance and its types across socio-economic characteristics and geographies of India. Further, we used a random intercept logistic regression to measure the variation in coverage across communities, district and state. Such household level study of coverage is helpful as it represents awareness and outreach for at least one member, which can percolate easily to the entire household with further interventions.

Results

We found that only 2/5th of households in India had insurance coverage for at least one of its members, with vast geographic variation emphasizing need for aggressive expansion. About 15.5% were covered by national schemes, 47.1% by state health scheme, 13.2% by employer provided health insurance, 3.3% had purchased health insurance privately and 25.6% were covered by other health insurance schemes (not covered above). About 30.5% of the total variation in coverage was attributable to state, 2.7% to districts and 9.5% to clusters. Household size, gender, marital status and education of household head show weak gradient for coverage under "any" insurance.

Discussion

Despite substantial increase in population eligible for state sponsored health insurance and rise in private health insurance companies, nearly 60% of families do not have a single person covered under any health insurance scheme. Further, the existing coverage is fragmented, with significant rural/urban and geographic variation within districts. It is essential to consider these disparities and adopt rigorous place-based interventions for improving health insurance coverage.

Evolution of Government-funded health insurance for universal health coverage in India

India has run multiple Government-Funded Health Insurance schemes (GFHIS) over the past decades to ensure affordable healthcare. We assessed GFHIS evolution with a special focus on two national schemes - Rashtriya Swasthya Bima Yojana (RSBY) and Pradhan Mantri Jan Arogya Yojana (PMJAY). RSBY suffered from a static financial coverage cap, low enrollment, inequitable service supply, utilization, etc. PMJAY expanded coverage and mitigated some of RSBY's drawbacks. Investigating equity in PMJAY's supply and utilization across geography, sex, age, social groups, and healthcare sectors depicts several systemic skews. Kerala and Himachal Pradesh with low poverty and disease burden use more services. Males are more likely to seek care under PMJAY than females. Mid-age population (19-50 years) is a common group availing services. Scheduled Caste and Scheduled Tribe people have low service utilization. Most hospitals providing services are private. Such inequities can lead the most vulnerable populations further into deprivation due to healthcare inaccessibility.

Illnesses and hardship financing in India: an evaluation of inpatient and outpatient cases, 2014-18

BACKGROUND

Progress towards universal health coverage requires strengthening the country's health system. In developing countries, the increasing disease burden puts a lot of stress on scarce household finances. However, this burden is not the same for everyone. The economic burden varies across the disease groups and care levels. Government intervention is vital in formulating policies in addressing financial distress at the household level. In India, even when outpatient care forms a significant proportion of out-of-pocket expenditure, government schemes focus on reducing household expenditure on inpatient care alone. Thus, people resort to hardship financing practices like informal borrowing or selling of assets in the event of health shocks. In this context, the present study aims to identify the disease(s) that correlates with maximum hardship financing for outpatients and inpatients and to understand the change in hardship financing over time.

METHODS

We used two waves of National Sample Survey Organisation's data on social consumption on health- the 71^st and the 75^th rounds. Descriptive statistics are reported, and logistic regression is carried out to explain the adjusted impact of illness on hardship financing. Pooled logistic regression of the two rounds is estimated for inpatients and outpatients. Marginal effects are reported to study the changes in hardship financing over time.

RESULTS

The results suggest that cancer had the maximum likelihood of causing hardship financing in India for both inpatients (Odds ratio 2.41; 95% Confidence Interval (CI): 2.03 - 2.86 (71^st round), 2.54; 95% CI: 2.21 - 2.93 (75^th round)) and outpatients (Odds ratio 6.11; 95% CI: 2.95 - 12.64 (71^st round), 3.07; 95% CI: 2.14 - 4.40 (75^th round)). In 2018, for outpatients, the hardship financing for health care needs was higher at public health facilities, compared to private health facilities (Odds ratio 0.72; 95% CI: 0.62 - 0.83 (75^th round). The marginal effects model of pooled cross-section analysis reveals that from 2014 to 2018, the hardship financing had decreased for inpatients (Odds ratio 0.747; 95% CI:0.80 - -0.70), whereas it had increased for outpatients (Odds ratio 0.0126; 95% CI: 0.01 - 0.02). Our results also show that the likelihood of resorting to hardship financing for illness among women was lesser than that of men.

CONCLUSION

Government intervention is quintessential to decrease the hardship financing caused by cancer. The intra-household inequalities play an important role in explaining their hardship financing strategies. We suggest the need for more financial risk protection for outpatient care to address hardship financing.

Effect of kangaroo mother care initiated in community settings on financial risk protection of low-income households: a randomised controlled trial in Haryana, India

INTRODUCTION

Many families in low-income and middle-income countries have high out-of-pocket expenditures (OOPE) for healthcare, and some face impoverishment. We aimed to assess the effect of Kangaroo Mother Care initiated in community setting (ciKMC) on financial risk protection estimated by healthcare OOPE, catastrophic healthcare expenditure (CHE) and impoverishment due to healthcare seeking for low birthweight infants, using a randomised controlled trial design.

METHODS

We included 4475 low birthweight infants randomised to a ciKMC (2491 infants) and a control (1984 infants) arm, in a large trial conducted between 2017 and 2018 in Haryana, India. We used generalised linear models of the Gaussian family with an identity link to estimate the mean difference in healthcare OOPE, and Cox regression to estimate the HRs for CHE and impoverishment, between the trial arms.

RESULTS

Overall, in the 8-week observation period, the mean healthcare OOPE per infant was lower (US$20.0) in the ciKMC arm compared with the control arm (US$25.6) that is, difference of -US$5.5, 95% CI -US$11.4 to US$0.3, p=0.06). Among infants who sought care it was US$8.5 (95% CI -US$17.0 to -US$0.03, p=0.03) lower in the ciKMC arm compared with the control arm. The HR for impoverishment due to healthcare seeking was 0.56 (95% CI 0.36 to 0.89, p=0.01) and it was 0.91 (95% CI 0.74 to 1.12, p=0.37) for CHE.

CONCLUSION

ciKMC can substantially reduce the cost of care seeking and the risk of impoverishment for households. Our findings show that supporting mothers to provide KMC to low birthweight infants at home, in addition to reducing early infant mortality, may provide financial risk protection.

TRIAL REGISTRATION NUMBER

CTRI/2017/10/010114.