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

Access and barriers to genomic classifiers for breast cancer and prostate cancer in India

The incidence of cancer in general, including breast and prostate cancer specifically, is increasing in India. Breast and prostate cancers have genomic classifiers developed to guide therapy decisions. However, these genomic classifiers are often inaccessible in India due to high cost. These classifiers may also be less suitable to the Indian population, as data primarily from patients in wealthy Western countries were used in developing these genomic classifiers. In addition to the limitations in using these existing genomic classifiers, developing and validating new genomic classifiers for breast and prostate cancer in India is challenging due to the heterogeneity in the Indian population. However, there are steps that can be taken to address the various barriers that currently exist for accurate, accessible genomic classifiers for cancer in India.

Examining the Effectiveness of Financial Protection Schemes in Reducing Health Inequality

Health protection schemes such as health insurance and financial assistance provide immense help and support to access health care services, especially to the poor and marginalized section of society. India is witness to low health-related expenditure, and the society's socioeconomic and demographic structure further drops health care access to the new bottom. Consequently, inequality in health care access is highly observed across many socioeconomic attributes. The condition of Bihar, the poorest state of India, is more alarming. The analysis suggests that financial support in terms of universal health insurance coverage considerably reduces out-of-pocket expenditure and thus health inequality. Further, the low health insurance coverage is not solely due to a lack of institutional commitment and implementation process; the cognitive behavior and attitude of people are equally responsible for low health care access. An intensive awareness program to show the benefit of the health insurance scheme and sensitization of people against the social stigma is important to provide better health care access and reduce health inequality.

Is Artificial Intelligence the Cost-Saving Lens to Diabetic Retinopathy Screening in Low- and Middle-Income Countries?

Diabetes is a rapidly growing global health crisis disproportionately affecting low- and middle-income countries (LMICs). The emergence of diabetes as a global pandemic is one of the major challenges to human health, as long-term microvascular complications such as diabetic retinopathy (DR) can lead to irreversible blindness. Leveraging artificial intelligence (AI) technology may improve the diagnostic accuracy, efficiency, and accessibility of DR screenings across LMICs. However, there is a gap between the potential of AI technology and its implementation in clinical practice. The main objective of this systematic review is to summarize the currently available literature on the health economic assessments of AI implementation for DR screening in LMICs. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We conducted an extensive systematic search of PubMed/MEDLINE, Scopus, and the Web of Science on July 15, 2023. Our review included full-text English-language articles from any publication year. The Joanna Briggs Institute's (JBI) critical appraisal checklist for economic evaluations was used to rate the quality and rigor of the selected articles. The initial search generated 1,423 records and was narrowed to five full-text articles through comprehensive inclusion and exclusion criteria. Of the five articles included in our systematic review, two used a cost-effectiveness analysis, two used a cost-utility analysis, and one used both a cost-effectiveness analysis and a cost-utility analysis. Across the five articles, LMICs such as China, Thailand, and Brazil were represented in the economic evaluations and models. Overall, three out of the five articles concluded that AI-based DR screening was more cost-effective in comparison to standard-of-care screening methods. Our systematic review highlights the need for more primary health economic analyses that carefully evaluate the economic implications of adopting AI technology for DR screening in LMICs. We hope this systematic review will offer valuable guidance to healthcare providers, scientists, and legislators to support appropriate decision-making regarding the implementation of AI algorithms for DR screening in healthcare workflows.

Out-of-pocket expenditure and its correlates for institutional deliveries in private and public healthcare sectors in India: findings from NFHS 5

BACKGROUND

Increased coverage for institutional delivery (ID) is one of the essential factors for improved maternal and child health (MCH). Though, ID increased over time, out-of-pocket expenditure (OOPE) for the care-seeking families had been found to be growing, parallelly. Hence, we estimated OOPE in public and private health centres for ID, along with their sources and attributing factors and compared state and union territory-wise, so that financial risk protection can be improved for MCH related services.

METHODS

We used women's data from the National Family Health Survey, 2019-2021 (NFHS-5). Reproductive aged women (15-49 years) delivering one live child in last 5 years (n = 145,386) in any public or private institutions, were included. Descriptive statistics were presented as frequency and proportions. OOPE, was summarized as median and interquartile range (IQR). To estimate the extent for each covariate's effect, linear regression model was conducted.

RESULTS

Overall median OOPE for ID was Rs. 4066 (median OOPE: private hospitals: Rs.25600, public hospitals: Rs.2067). Health insurance was not sufficient to slash OOPE down at private facilities. Factors associated significantly to high OOPE were mothers' education, elderly pregnancy, complicated delivery, birth order of the latest child etc. CONCLUSION: A standard norm for ID should be implemented as a component of overseeing and controlling inequality. Aiding the needy is probably just one side of the solution, while the focus is required to be shifted towards reducing disparity among the health facilities, so that the beneficiaries do not need to spend on essential services or during emergencies.

Progress on Sustainable Development Goal indicators in 707 districts of India: a quantitative mid-line assessment using the National Family Health Surveys, 2016 and 2021

Background

India has committed itself to accomplishing the Sustainable Development Goals (SDGs) by 2030. Meeting these goals would require prioritizing and targeting specific areas within India. We provide a mid-line assessment of the progress across 707 districts of India for 33 SDG indicators related to health and social determinants of health.

Methods

We used data collected on children and adults from two rounds of the National Family Health Survey (NFHS) conducted in 2016 and 2021. We identified 33 indicators that cover 9 of the 17 official SDGs. We used the goals and targets outlined by the Global Indicator Framework, Government of India and World Health Organization (WHO) to determine SDG targets to be met by 2030. Using precision-weighted multilevel models, we estimated district mean for 2016 and 2021, and using these values, computed the Annual Absolute Change (AAC) for each indicator. Using the AAC and targets, we classified India and each district as: Achieved-I, Achieved-II, On-Target and Off-Target. Further, when a district was Off-Target on a given indicator, we further identified the calendar year in which the target will be met post-2030.

Findings

India is not On-Target for 19 of the 33 SDGs indicators. The critical Off-Target indicators include Access to Basic Services, Wasting and Overweight Children, Anaemia, Child Marriage, Partner Violence, Tobacco Use, and Modern Contraceptive Use. For these indicators, more than 75% of the districts were Off-Target. Because of a worsening trend observed between 2016 and 2021, and assuming no course correction occurs, many districts will never meet the targets on the SDGs even well after 2030. These Off-Target districts are concentrated in the states of Madhya Pradesh, Chhattisgarh, Jharkhand, Bihar, and Odisha. Finally, it does not appear that Aspirational Districts, on average, are performing better in meeting the SDG targets than other districts on majority of the indicators.

Interpretation

A mid-line assessment of districts' progress on SDGs suggests an urgent need to increase the pace and momentum on four SDG goals: No Poverty (SDG 1), Zero Hunger (SDG 2), Good Health and Well-Being (SDG 3) and Gender Equality (SDG 5). Developing a strategic roadmap at this time will help India ensure success with regards to meeting the SDGs. India's emergence and sustenance as a leading economic power depends on meeting some of the more basic health and social determinants of health-related SDGs in an immediate and equitable manner.

Funding

This work was funded by the Bill and Melinda Gates Foundation, INV-002992.

Evaluating the status of the Lancet Commission on Global Surgery indicators for India

For universal surgical, obstetric, trauma, and anesthesia care by 2030, the Lancet Commission on Global Surgery (LCoGS) suggested tracking six indicators. We reviewed academic and policy literature to investigate the current state of LCoGS indicators in India. There was limited primary data for access to timely essential surgery, risk of impoverishing and catastrophic health expenditures due to surgery, though some modeled estimates are present. Surgical specialist workforce estimates are heterogeneous across different levels of care, urban and rural areas, and diverse health sectors. Surgical volumes differ widely across demographic, socio-economic, and geographic cohorts. Perioperative mortality rates vary across procedures, diagnoses, and follow-up time periods. Available data suggest India falls short of achieving global targets. This review highlights the evidence gap for India's surgical care planning. India needs a systematic subnational mapping of indicators and adaptation of targets as per the country's health needs for equitable and sustainable planning.

Wealth Status and Health Insurance Enrollment in India: An Empirical Analysis

Since 2005, health insurance (HI) coverage in India has significantly increased, largely because of the introduction of government-funded pro-poor insurance programs. As a result, the determinants of HI enrollment and their relative importance may have changed. Using National Family Health Survey (NFHS)-4 data, collected in 2015-2016, and employing a Probit regression model, we re-examine the determinants of household HI enrollment. Then, using a multinomial logistic regression model, we estimate the relative risk ratio for enrollment in different HI schemes. In comparison to the results on the determinants of HI enrollment using the NFHS data collected in 2005-2006, we find a decrease in the wealth gap in public HI enrollment. Nonetheless, disparities in enrollment remain, with some changes in those patterns. Households with low assets have lower enrollments in private and community-based health insurance (CBHI) programs. Households with a higher number of dependents have a higher likelihood of HI enrollment, especially in rural areas. In rural areas, poor Scheduled Caste and Scheduled Tribe households are more likely to be enrolled in public HI than the general Caste households. In urban areas, Muslim households have a lower likelihood of enrollment in any HI. The educational attainment of household heads is positively associated with enrollment in private HI, but it is negatively associated with enrollment in public HI. Since 2005-2006, while HI coverage has improved, disparities across social groups remain.

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.

Out-of-pocket expenditures and catastrophic expenditures on inpatient care among households of an urban village in Delhi

Background

Out-of-pocket expenditure (OOPE) for inpatient care has been known to cause maximum impoverishment. It can have debilitating consequences for urban poor households. It is necessary to study inpatient care costs and the related factors among the households of an urban village to determine their vulnerability to catastrophic expenditure and to protect them from it.

Objective

The study aimed to calculate the mean OOPE on inpatient care, and catastrophic health expenditure among households of an urban village in Delhi.

Design

This was a cross-sectional study conducted over 18 months among urban village households of Delhi who have been residing for the last 1 year.

Methods

A sample size of 188 was calculated based on another study, and households were selected using systematic random sampling. A pre-designed, pre-tested, semi-structured, and interviewer-administered questionnaire in Hindi was used to elicit and record relevant information. Data were recorded and coded, and analysis was done using licensed SPSS v.26 software. Tables were generated for relevant data, and cross-tables were used to assess statistical association with chi-square or Fisher exact tests, as required. A p-value of 0.05 was considered statistically significant.

Results

The mean annual OOPE borne by a household on inpatient care was INR 6870.3 (SD ± 30,580.6), where 93.3% of OOPE was incurred while seeking treatment from public facilities. The OOPE on inpatient care had a statistically significant association with households having joint family, members from vulnerable population, and belonging to Delhi.

Conclusion

The households of an urban village of Aliganj, Delhi, have high OOPE on inpatient care (60.6%) and catastrophic health expenditure (75.6%).

Intrapulmonary mature cystic teratoma presenting with haemoptysis treated with right middle lobectomy in a low-resource setting

A teenage girl presented to our remote rural hospital with history of massive haemoptysis. A CT scan showed a spherical lesion in the right lung. Exploratory thoracotomy was performed with a provisional diagnosis of pulmonary hydatid cyst. Intraoperative findings were consistent with intrapulmonary teratoma and this was confirmed by a histopathological diagnosis of mature teratoma. Four years later, the patient presented again with recurrence of haemoptysis and a right middle lobectomy was performed. We present a report of successful management of this patient with 20-year follow-up since the first surgery, describe the pathology of this rare condition and the procedures used to treat it. We also discuss the social and economic factors that affect decision making in the management of rare conditions in remote rural areas among poor communities that are usually referred to tertiary hospitals and suggest modifications to protocols to provide effective treatment in spite of resource constraints.