Addressing data and methodological limitations in estimating catastrophic health spending and impoverishment in India, 2004\u201318

Sanjay K Mohanty,Laxmi Kant Dwivedi

doi:10.1186/s12939-021-01421-6

Abstract

BackgroundEstimates of catastrophic health expenditure (CHE) are counterintuitive to researchers, policy makers, and developmental partners due to data and methodological limitation. While inferences drawn from use of capacity-to-pay (CTP) and budget share (BS) approaches are inconsistent, the non-availability of data on food expenditure in the health survey in India is an added limitation.MethodsUsing data from the health and consumption surveys of National Sample Surveys over 14 years, we have overcome these limitations and estimated the incidence and intensity of CHE and impoverishment using the CTP approach.ResultsThe incidence of CHE for health services in India was 12.5% in 2004, 13.4% in 2014 and 9.1% by 2018. Among those households incurring CHE, they spent 1.25 times of their capacity to pay in 2004 (intensity of CHE), 1.71 times in 2014 and 1.31 times by 2018. The impoverishment due to health spending was 4.8% in 2004, 5.1% in 2014 and 3.3% in 2018. The state variations in incidence and intensity of CHE and incidence of impoverishment is large. The concentration index (CI) of CHE was − 0.16 in 2004, − 0.18 in 2014 and − 0.22 in 2018 suggesting increasing inequality over time. The concentration curves based on CTP approach suggests that the CHE was concentrated among poor. The odds of incurring CHE were lowest among the richest households [OR 0.22; 95% CI: 0.21, 0.24], households with elderly members [OR 1.20; 95% CI:1.12, 1.18] and households using both inpatient and outpatient services [OR 2.80, 95% CI 2.66, 2.95]. Access to health insurance reduced the chance of CHE and impoverishment among the richest households. The pattern of impoverishment was similar to that of CHE.ConclusionIn the last 14 years, the CHE and impoverishment in India has declined while inequality in CHE has increased.

Highlights

Estimates of catastrophic health expenditure (CHE) are counterintuitive to researchers, policy makers, and developmental partners due to data and methodological limitation
We demonstrate how to overcome these constraints by estimating CHE and impoverishment using a unique approach and appropriate data source in the Indian context
About one-third of households availed the out-patient care in 15 days reference period and it was higher in consumption surveys

Summary

Introduction

Estimates of catastrophic health expenditure (CHE) are counterintuitive to researchers, policy makers, and developmental partners due to data and methodological limitation. While inferences drawn from use of capacity-to-pay (CTP) and budget share (BS) approaches are inconsistent, the non-availability of data on food expenditure in the health survey in India is an added limitation. Estimates based on capacity to pay (CTP) are pro-poor, take into account equity concerns, and are recommended by the WHO This is because loss of welfare due to OOP payments for health care is higher among the poor than among the rich, as poor households resort to borrowing and selling assets, underutilise or do not seek health care due to lack of resources while rich people meet OOP payment through income or savings. Literature suggests that households without health insurance, poor households, elderly households, large households, households in rural areas and households with chronically sick members are more likely to incur CHE [7, 9]

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Results

Conclusion