Addressing data and methodological limitations in estimating catastrophic health spending and impoverishment in India, 2004-18

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.

Hospitalisation expenditure on tuberculosis among tribal populations in India: A repeated cross-sectional analysis of national sample survey data, 2004 to 2018

Objective

Tribal population in India (8.6% of the total population) have a greater prevalence of tuberculosis compared to the national average. The article aims to study out-of-pocket expenditure (OOPE), hardship financing, and impoverishment effects of TB hospitalisation treatment among tribal populations in India.

Methods

Data of three rounds of National Sample Surveys (NSS) 60th (2004-05), 71st (2013-14) and 75th (2017-18) rounds were analyzed. Descriptive statistics, bivariate estimates and multivariate models were performed to calculate the OOPE, healthcare burden (HCB), catastrophic health expenditure (CHE), hardship financing and impoverishment effects using standard definitions at February 2023 price values. Propensity score matching (PSM) was used to examine the effect of health insurance coverage on catastrophic health expenditure, and impoverishment.

Results

Over two-thirds of the TB cases are seen in the economically productive age group (14-59 years). Substantial OOPE and its impact on HCB, CHE, and poverty impact observed among 15-35 age group across all three rounds. Illiterate patients and those availing private hospitals for TB treatment had higher OOPE, HCB, hardship financing, CHE, and poverty impact. 38.5% (2014) and 33.2% (2018) are covered with any kind of public healthcare coverage, PSM analysis shows households with health insurance have lower incidence of CHE and impoverishment effects due to TB hospitalisation expenditure.

Conclusions

The current study aids in comprehending the patterns in the financial burden of TB on tribal households during the previous 15 years and gives policy makers information for efficient resource allocation management for TB among Indian tribal communities.

Rural‒urban disparities in household catastrophic health expenditure in Bangladesh: a multivariate decomposition analysis

BACKGROUND

Rural‒urban disparity in catastrophic healthcare expenditure (CHE) is a well-documented challenge in low- and middle-income countries, including Bangladesh, limiting financial protection and hindering the achievement of the Universal Health Coverage target of the United Nations Sustainable Development Goals. However, the factors driving this divide remain poorly understood. Therefore, this study aims to identify the key determinants of the rural‒urban disparity in CHE incidence in Bangladesh and their changes over time.

METHODS

We used nationally representative data from the latest three rounds of the Bangladesh Household Income and Expenditure Survey (2005, 2010, and 2016). CHE incidence among households seeking healthcare was measured using the normative food, housing, and utilities method. To quantify covariate contributions to the rural‒urban CHE gap, we employed the Oaxaca-Blinder multivariate decomposition approach, adapted by Powers et al. for nonlinear response models.

RESULTS

CHE incidence among rural households increased persistently during the study period (2005: 24.85%, 2010: 25.74%, 2016: 27.91%) along with a significant (p-value ≤ 0.01) rural‒urban gap (2005: 9.74%-points, 2010: 13.94%-points, 2016: 12.90%-points). Despite declining over time, substantial proportions of CHE disparities (2005: 87.93%, 2010: 60.44%, 2016: 61.33%) are significantly (p-value ≤ 0.01) attributable to endowment differences between rural and urban households. The leading (three) covariate categories consistently contributing significantly (p-value ≤ 0.01) to the CHE gaps were composition disparities in the lowest consumption quintile (2005: 49.82%, 2010: 36.16%, 2016: 33.61%), highest consumption quintile (2005: 32.35%, 2010: 15.32%, 2016: 18.39%), and exclusive reliance on informal healthcare sources (2005: -36.46%, 2010: -10.17%, 2016: -12.58%). Distinctively, the presence of chronic illnesses in households emerged as a significant factor in 2016 (9.14%, p-value ≤ 0.01), superseding the contributions of composition differences in household heads with no education (4.40%, p-value ≤ 0.01) and secondary or higher education (7.44%, p-value ≤ 0.01), which were the fourth and fifth significant contributors in 2005 and 2010.

CONCLUSIONS

Rural‒urban differences in household economic status, educational attainment of household heads, and healthcare sources were the key contributors to the rural‒urban CHE disparity between 2005 and 2016 in Bangladesh, with chronic illness emerging as a significant factor in the latest period. Closing the rural‒urban CHE gap necessitates strategies that carefully address rural‒urban variations in the characteristics identified above.

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.

Cancer care and economic burden-A narrative review

Cancer care poses a significant economic burden in India, where noncommunicable diseases contribute to a large number of deaths and disability-adjusted life-years. Despite economic growth, equitable wealth distribution remains a challenge, leading to inequalities in healthcare access. India's healthcare system is primarily privatized, financed through out-of-pocket expenditure (OOPE), and lacks coverage for a majority of the population. As a result, individuals without financial means face catastrophic health consequences when seeking necessary healthcare. OOPE in India's healthcare system is a major concern, with medicines accounting for a significant portion of expenses, followed by diagnostic tests and consultation fees. Nonmedical expenses also contribute to the financial burden. Cancer care specifically faces substantial financial challenges, with high treatment costs, reduced workforce participation, and the need for distress financing. Cancer-related OOPE is predominantly borne by patients and their families, leading to significant financial strain. The lack of comprehensive health insurance coverage and limited access to publicly funded healthcare services exacerbate the problem. Catastrophic health expenditure (CHE) in cancer care is prevalent, pushing households into financial distress and potentially impoverishment. Efforts have been made to address this issue, such as increasing public spending on healthcare and implementing health insurance schemes. However, challenges remain in ensuring their effectiveness and reach. The role of family care physicians is crucial in supporting patients and their families during catastrophic health expenditures related to cancer-related palliative care. They coordinate care, provide advocacy, emotional support, symptom management, and facilitate end-of-life discussions. Comprehensive measures are needed to strengthen healthcare infrastructure, improve access to affordable cancer care, enhance health insurance coverage, and implement supportive measures for cancer patients. Additionally, promoting preventive measures and early detection can help reduce the need for expensive treatments and decrease the risk of catastrophic health expenditures.

Catastrophic health expenditure and its association with socioeconomic status in China: evidence from the 2011-2018 China Health and Retirement Longitudinal Study

BACKGROUND

An increase in healthcare utilization in response to universal health coverage may leave massive economic burden on individuals and households. Identifying catastrophic health expenditure helps us understand such burden. This study aims to examine the incidence of catastrophic health expenditure at various thresholds, explore its trend over years, and investigate whether it varies across socioeconomic status (SES).

METHODS

Data used in this study were from four waves of the China Health and Retirement Longitudinal Study (CHARLS): 2011, 2013, 2015, and 2018. SES was measured by annual per-capita household expenditure, which was then divided into quintiles (Quintile 1 (Q1): the poorest - Quintile 5 (Q5): the wealthiest). Catastrophic health expenditure was measured at both a fixed threshold (40%) and a set of variable thresholds, where the thresholds for other quintiles were estimated by multiplying 40% by the ratio of average food expenditure in certain quintile to that in the index quintile. Multilevel mixed-effects logistic regression models were used to analyze the determinants of catastrophic health expenditure at various thresholds.

RESULTS

A total of 6,953 households were included in our study. The incidence of catastrophic health expenditure varied across the thresholds set. At a fixed threshold, 10.90%, 9.46%, 13.23%, or 24.75% of households incurred catastrophic health expenditure in 2011, 2013, 2015, and 2018, respectively, which were generally lower than those at variable thresholds. Catastrophic health expenditure often decreased from 2011 to 2013, and an increasing trend occurred afterwards. Compared to households in Q5, those in lower quintiles were more likely to suffer catastrophic health expenditure, irrespective of the thresholds set. Similarly, having chronic diseases and healthcare utilization increased the odds of catastrophic health expenditure.

CONCLUSIONS

The financial protection against catastrophic health expenditure shocks remains a challenge in China, especially for the low-SES and those with chronic diseases. Concerted efforts are needed to further expand health insurance coverage across breadth, depth, and height, optimize health financing mechanism, redesign cost-sharing arrangements and provider payment methods, and develop more efficient expenditure control strategies.

Overview of the main methods used for estimating catastrophic health expenditure

Out-of-pocket payments are expenditures borne directly by an individual/household for health services that are not reimbursed by any third-party. Households can experience financial hardship when the burden of such out-of-pocket payments is significant. This financial hardship is commonly measured using the "catastrophic health expenditure" (CHE) metric. CHE has been applied as an indicator in several health sectors and health policies. However, despite its importance, the methods used to measure the incidence of CHE vary across different studies and the terminology used can be inconsistent. In this paper, we introduce and raise awareness of the main approaches used to calculate CHE and discuss critical areas of methodological variation in a global health context. We outline the key features, foundation and differences between the two main methods used for estimating CHE: the budget share and the capacity-to-pay approach. We discuss key sources of variation within CHE calculation and using data from Ethiopia as a case study, illustrate how different approaches can lead to notably different CHE estimates. This variation could lead to challenges when decisionmakers and policymakers need to compare different studies' CHE estimates. This overview is intended to better understand how to interpret and compare CHE estimates and the potential variation across different studies.

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.

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.

Out-of-pocket expenditure on medicines in Bangladesh: An analysis of the national household income and expenditure survey 2016–17

Background and objectives

High out-of-pocket expenditures (OOPE) increases the probability that households will become impoverished or will forgo needed care. The aim of this paper is to study household medicines expenditure and its associated determining factors to develop policies to protect households from financial hardship.

Methods

The present cross-sectional and population-level study used the Bangladesh 2016–17 National Household Income and Expenditure Survey (HIES). The final sample size was 46,080 households. We analyzed the probability of OOPE for medicines, the share of total OOPE due to medicines out of total OOPE in health (reported as a ratio between zero and one), the OOPE amount for medicines reported (in United States Dollars), and the share of OOPE amount on medicines out of total household expenditure (reported as a ratio between zero and one). Predictors of analyzed outcomes were identified using three regression models.

Results

Out of those households who spent on healthcare, the probability of having any OOPE on medicines was 87.9%. Of those who spent on medicines, the median monthly expenditure was US$3.03. The poorest households spent 9.97% of their total household expenditure as OOPE on medicines, nearly double that of the wealthiest households (5.86%). The characteristic which showed the most significant correlation to a high OOPE on medicines was the presence of chronic diseases, especially cancer. Twenty six percent of all surveyed households spend more than 10% of their OOPE on medicines.

Conclusions

Our study shows that financial protection should be targeted at the poorest quintiles and such protection should include enrollment of rural households. Further, outpatient medicines benefits should include those for non-communicable diseases (NCDs).

What fragile factors hinder the pace of China's alleviation efforts of the poverty-stricken population? A study from the perspective of impoverishment caused by medical expenses

OBJECTIVE

China has made remarkable achievements in poverty alleviation. However, with the change in economic development and age structure, the population stricken by poverty due to medical expenses and disability accounted for 42.3 and 14.4% of the total poverty-stricken population, respectively. Accordingly, it is crucial to accurately pinpoint the characteristics of people who are about to become poor due to illness. In this study, we analyzed the incidence of impoverishment by medical expense at the provincial, family, and different medical insurance scheme levels to identify the precise groups that are vulnerable to medical-related poverty.

METHOD

Data were extracted from the Fifth National Health Service Survey in China in 2013 through a multi-stage, stratified, and random sampling method, leaving 93,570 households (273,626 people) for the final sample. The method recommended by World Health Organization (WHO) was adopted to calculate impoverishment by medical expense, and logistic regression was adopted to evaluate its determinants.

RESULTS

The poverty and impoverishment rate in China were 16.2 and 6.3% respectively. The poverty rate in western region was much higher than that of central and eastern regions. The rate of impoverishment by medical expense (IME) was higher in the western region (7.2%) than that in the central (6.5%) and eastern (5.1%) regions. The New Cooperative Medical Scheme (NCMS) was associated with the highest rate (9.1%) of IME cases. The top three diseases associated with IME were malignant tumor, congenital heart disease, and mental disease. Households with non-communicable disease members or hospitalized members had a higher risk on IME. NCMS-enrolled, poorer households were more likely to suffer from IME.

CONCLUSION

The joint roles of economic development, health service utilization, and welfare policies result in medical impoverishment for different regions. Poverty and health service utilization are indicative of households with high incidence of medical impoverishment. Chronic diseases lead to medical impoverishment. The inequity existing in different medical insurance schemes leads to different degrees of risk of IME. A combined strategy to precise target multiple vulnerabilities of poor population would be more effective.

Financial risk protection from out-of-pocket health spending in low- and middle-income countries: a scoping review of the literature

Background

Financial risk protection (FRP), defined as households’ access to needed healthcare services without experiencing undue financial hardship, is a critical health systems target, particularly in low- and middle-income countries (LMICs). Given the remarkable growth in FRP literature in recent times, we conducted a scoping review of the literature on FRP from out-of-pocket (OOP) health spending in LMICs. The objective was to review current knowledge, identify evidence gaps and propose future research directions.

Methods

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines to conduct this scoping review. We systematically searched PubMed, Scopus, ProQuest and Web of Science in July 2021 for literature published since 1 January 2015. We included empirical studies that used nationally representative data from household surveys to measure the incidence of at least one of the following indicators: catastrophic health expenditure (CHE), impoverishment, adoption of strategies to cope with OOP expenses, and forgone care for financial reasons. Our review covered 155 studies and analysed the geographical focus, data sources, methods and analytical rigour of the studies. We also examined the level of FRP by disease categories (all diseases, chronic illnesses, communicable diseases) and the effect of health insurance on FRP.

Results

The extant literature primarily focused on India and China as research settings. Notably, no FRP study was available on chronic illness in any low-income country (LIC) or on communicable diseases in an upper-middle-income country (UMIC). Only one study comprehensively measured FRP by examining all four indicators. Most studies assessed (lack of) FRP as CHE incidence alone (37.4%) or as CHE and impoverishment incidence (39.4%). However, the LMIC literature did not incorporate the recent methodological advances to measure CHE and impoverishment that address the limitations of conventional methods. There were also gaps in utilizing available panel data to determine the length of the lack of FRP (e.g. duration of poverty caused by OOP expenses). The current estimates of FRP varied substantially among the LMICs, with some of the poorest countries in the world experiencing similar or even lower rates of CHE and impoverishment compared with the UMICs. Also, health insurance in LMICs did not consistently offer a higher degree of FRP.

Conclusion

The literature to date is unable to provide a reliable representation of the actual level of protection enjoyed by the LMIC population because of the lack of comprehensive measurement of FRP indicators coupled with the use of dated methodologies. Future research in LMICs should address the shortcomings identified in this review.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12961-022-00886-3.

Financial risk protection in health care in Bangladesh in the era of Universal Health Coverage

BACKGROUND

Ensuring financial risk protection in health care and achieving universal health coverage (UHC) by 2030 is one of the crucial Sustainable Development Goals (SDGs) targets for many low- and middle-income countries (LMICs), including Bangladesh. We examined the critical trajectory of financial risk protection against out-of-pocket (OOP) health expenditure in Bangladesh.

METHODS

Using Bangladesh Household Income and Expenditure Survey data from 2005, 2010, and 2016, we examined the levels and distributions of catastrophic health expenditure (CHE) and impoverishment incidences. We used the normative food, housing, and utilities method, refining it by categorizing households with zero OOP expenses by reasons.

RESULTS

OOP expenditure doubled between 2005 and 2016 (USD 115.6 in 2005, USD 162.1 in 2010, USD 242.9 in 2016), accompanied by rising CHE (11.5% in 2005, 11.9% in 2010, 16.6% in 2016) and impoverishment incidence (1.5% in 2005, 1.6% in 2010, 2.3% in 2016). While further impoverishment of the poor households due to OOP expenditure (3.6% in 2005, 4.1% in 2010, 3.9% in 2016) was a more severe problem than impoverishment of the non-poor, around 5.5% of non-poor households were always at risk of impoverishment. The poorest households were the least financially protected throughout the study period (lowest vs. highest quintile CHE: 29.5% vs. 7.6%, 33.2% vs. 7.2%, and 37.6% vs. 13.0% in 2005, 2010, and 2016, respectively). The disparity in CHE among households with and without chronic illness was also remarkable in 2016 (25.0% vs. 9.1%).

CONCLUSION

Financial risk protection in Bangladesh exhibits a deteriorated trajectory from 2005 to 2016, posing a significant challenge to achieving UHC and, thus, the SDGs by 2030. The poorest and chronically ill households disproportionately lacked financial protection. Reversing the worsening trends of CHE and impoverishment and addressing the inequities in their distributions calls for implementing UHC and thus providing financial protection against illness.

Components of Out-of-Pocket Expenditure and Their Relative Contribution to Economic Burden of Diseases in India

Importance

High out-of-pocket expenditure (OOPE) on health in India may limit achieving universal health coverage. A clear insight on the components of health expenditure may be necessary to make allocative decisions to reduce OOPE, and such details by sociodemographic group and state have not been studied in India.

Objective

To analyze the relative contribution of drugs, diagnostic tests, doctor and surgeon fees, and expenditure on other medical services and nonmedical health-related services, such as transport, lodging, and food, by sociodemographic characteristics of patients, geography, and type of illness.

Design, Setting, and Participants

A population-based cross-sectional health consumption survey conducted by the National Sample Survey Organisation in 2018 was analyzed in this cross-sectional study. Respondents who provided complete information on costs of medicine, doctors, diagnostics tests, other medical costs, and nonmedical costs were selected. Data were analyzed from August through September 2021.

Main Outcomes and Measures

Mean and median share of components (ie, medicine, diagnostic tests, doctor fees, other medical costs, and nonmedical costs) in total health care expenditure and income were calculated. Bivariate survey-weighted mean (with 95% CI) and median (IQR) expenditures were calculated for each component across sociodemographic characteristics. The proportion of total expenditure and income contributed by each cost was calculated for each individual. Mean and median were then used to summarize such proportions at the population level. The association between state net domestic product per capita and component share of each health care service was graphically explored.

Results

Health expenditure details were analyzed for 43 781 individuals for inpatient costs (27 272 [64.3%] women; 26 830 individuals aged 25-64 years [59.9%]) and 8914 individuals for outpatient costs (4176 [48.2%] women; 4901 individuals aged 25-64 years [54.2%]); most individuals were rural residents (24 106 inpatients [67.0]; 4591 outpatients [63.9%]). Medicines accounted for a mean of 29.1% (95% CI, 28.9%-29.2%) of OOPE among inpatients and 60.3% (95% CI, 59.7%-60.9%) of OOPE among outpatients. Doctor consultation charges were a mean of 15.3% (95% CI, 15.1%-15.4%) of OOPE among inpatients and 12.4% (95% CI, 12.1%-12.6%) of OOPE among outpatients. Diagnostic tests accounted for a mean of 12.3% (95% CI, 12.2%-12.4%) of OOPE for inpatient and 9.2% (95% CI, 8.9%-9.5%) of OOPE for outpatient services. Nonmedical costs accounted for a mean of 23.6% (95% CI, 23.3%-23.8%) of OOPE among inpatients and 14.6% (95% CI, 14.1%-15.1%) of OOPE among outpatients. Mean share of OOPE from doctor consultations and diagnostic test charges increased with socioeconomic status. For example, for the lowest vs highest monthly per capita income quintile among inpatients, doctor consultations accounted for 11.5% (95% CI, 11.1%-11.8%) vs 21.2% (95% CI, 20.8%-21.6%), and diagnostic test charges accounted for 10.9% (95% CI, 10.6%-11.1%) vs 14.3% (95% CI, 14.0%-14.5%). The proportion of mean annual health expenditure from mean annual income was $299 of $1918 (15.6%) for inpatient and $391 of $1788 (21.9%) for outpatient services.

Conclusions and Relevance

This study found that nonmedical costs were significant, share of total health care OOPE from doctor consultation and diagnostic test charges increased with socioeconomic status, and annual cost as a proportion of annual income was lower for inpatient than outpatient services.

Prevalence and factors associated with catastrophic health expenditure among slum and non-slum dwellers undergoing emergency surgery in a metropolitan area of South Western Nigeria

BACKGROUND

Out of Pocket (OOP) payment continues to persist as the major mode of payment for healthcare in Nigeria despite the introduction of the National Health Insurance Scheme (NHIS). Although the burden of health expenditure has been examined in some populations, the impact of OOP among slum dwellers in Nigeria when undergoing emergencies, is under-researched. This study sought to examine the prevalence, factors and predictors of catastrophic health expenditure amongst selected slum and non-slum communities undergoing emergency surgery in Southwestern Nigeria.

METHODS

The study utilised a descriptive cross-sectional survey design to recruit 450 households through a multistage sampling technique. Data were collected using pre-tested semi-structured questionnaires in 2017. Factors considered for analysis relating to the payer were age, sex, relationship of payer to patient, educational status, marital status, ethnicity, occupation, income and health insurance coverage. Variables factored into analysis for the patient were indication for surgery, grade of hospital, and type of hospital. Households were classified as incurring catastrophic health expenditure (CHE), if their OOP expenditure exceeded 5% of payers' household budget. Analysis of the data took into account the multistage sampling design.

RESULTS

Overall, 65.6% (95% CI: 55.6-74.5) of the total population that were admitted for emergency surgery, experienced catastrophic expenditure. The prevalence of catastrophic expenditure at 5% threshold, among the population scheduled for emergency surgeries, was significantly higher for slum dwellers (74.1%) than for non-slum dwellers (47.7%) (F = 8.59; p = 0.019). Multiple logistic regression models revealed the significant independent factors of catastrophic expenditure at the 5% CHE threshold to include setting of the payer (whether slum or non-slum dweller) (p = 0.019), and health insurance coverage of the payer (p = 0.012). Other variables were nonetheless significant in the bivariate analysis were age of the payer (p = 0.017), income (p<0.001) and marital status of the payer (p = 0.022).

CONCLUSION

Although catastrophic health expenditure was higher among the slum dwellers, substantial proportions of respondents incurred catastrophic health expenditure irrespective of whether they were slum or non-slum dwellers. Concerted efforts are required to implement protective measures against catastrophic health expenditure in Nigeria that also cater to slum dwellers.

Measuring catastrophe in paying for healthcare: A comparative methodological approach by using National Sample Survey, India

Healthcare expenditure significantly varies among various segments of the population. The appropriate measures of catastrophic health expenditure (CHE) will help to unravel the real burden of spending among households. Present study provides a link between the theoretical insights from Grossman's model and various methodological approaches for the estimation of CHE by using data from the three rounds of nationally representative Consumer Expenditure Surveys, India. Statistical analysis has been carried out by using multivariate logistic regression to identify the major determinants of CHE. Findings indicate that the occurrence of CHE has increased during 1993-2012. Rural residents and households with varying age composition such as with higher numbers of children and elderly were at higher risk. Economic status is significantly associated with CHE and increased demand for healthcare. The measurements differ as per the methodological approaches of CHE and definition of household's capacity to pay. Approach-based variations in the results can be of key importance in determining trends and magnitude in CHE. Despite these variations in measurements, study finds a limited incidence of CHE among the disadvantaged segment of the population though a greater share was devoted to health expenditure in recent years. Better risk pooling mechanism is required to address the healthcare needs of the disadvantaged segment such as elderly, children, poor and rural population in India.