OUT-OF-POCKET CATASTROPHIC HEALTH EXPENDITURE ATTRIBUTABLE TO CANCER CARE IN INDIA: A NATIONALLY REPRESENTATIVE HOUSEHOLD-LEVEL ANALYSIS OF THE NSS 75TH ROUND HEALTH SURVEY
Author(s)
Rishabh Dev Pandey, PhD1, Prabhakar Pandey, M.Pharm, MBA2, Gurunag Kaushik, MSc2, Kandluru Sashank Reddy, MSc2.
1SEREXIA CONSULTANCY PVT LTD, BENGALURU, India, 2SEREXIA CONSULTANCY PVT LTD, Bengaluru, India.
1SEREXIA CONSULTANCY PVT LTD, BENGALURU, India, 2SEREXIA CONSULTANCY PVT LTD, Bengaluru, India.
OBJECTIVES: To estimate the incidence of catastrophic health expenditure (CHE) and medical impoverishment attributable to cancer-related out-of-pocket (OOP) payments among Indian households, and to identify socioeconomic determinants of financial hardship and inequity in burden distribution.
METHODS: A cross-sectional analysis was conducted using the National Sample Survey 75th Round on Health (2017-18; n=113,823 households), supplemented by NFHS-5 state-level insurance coverage data and National Cancer Registry Programme incidence rates. Cancer-affected households were identified via NSS ailment codes 36 and 37. CHE was defined at WHO thresholds of 10% and 25% of annual household consumption; impoverishment was assessed against World Bank poverty lines of $1.90 and $3.20 (PPP)/day. Determinants of CHE were examined using survey-weighted binary logistic regression. Equity was assessed through Wagstaff concentration indices. Sensitivity analyses were performed across alternative expenditure thresholds.
RESULTS: Cancer-affected households (n=3,601; 3.16% of sample; ~6.25 million nationally) exhibited CHE-10 incidence of 8.7%, compared with 5.7% among non-cancer households. Cancer OOP alone exceeded 10% of consumption in 2.2% of cancer households. Median inpatient OOP was 4.5-fold higher in private versus public facilities (Rs 11,000 vs Rs 2,460). Cancer OOP rendered 1.05% of affected households newly impoverished at the $3.20 threshold. The concentration index for CHE-10 was −0.063, indicating pro-poor inequity in relative burden despite a positive index (+0.143) for absolute OOP. Weighted logistic regression identified household consumption (OR 0.80; p<0.001) and household size (p<0.001) as significant protective determinants; insurance coverage was directionally protective but non-significant, likely reflecting limited statistical power.
CONCLUSIONS: Cancer care imposes substantial catastrophic and impoverishing financial burdens on Indian households, disproportionately affecting lower-wealth quintiles. The divergence between absolute and relative concentration indices highlights a critical inequity in financial protection. Expansion of targeted insurance coverage and strengthening of public oncology capacity, particularly for medicines represent evidence-based priorities for reducing cancer-attributable financial hardship in India.
METHODS: A cross-sectional analysis was conducted using the National Sample Survey 75th Round on Health (2017-18; n=113,823 households), supplemented by NFHS-5 state-level insurance coverage data and National Cancer Registry Programme incidence rates. Cancer-affected households were identified via NSS ailment codes 36 and 37. CHE was defined at WHO thresholds of 10% and 25% of annual household consumption; impoverishment was assessed against World Bank poverty lines of $1.90 and $3.20 (PPP)/day. Determinants of CHE were examined using survey-weighted binary logistic regression. Equity was assessed through Wagstaff concentration indices. Sensitivity analyses were performed across alternative expenditure thresholds.
RESULTS: Cancer-affected households (n=3,601; 3.16% of sample; ~6.25 million nationally) exhibited CHE-10 incidence of 8.7%, compared with 5.7% among non-cancer households. Cancer OOP alone exceeded 10% of consumption in 2.2% of cancer households. Median inpatient OOP was 4.5-fold higher in private versus public facilities (Rs 11,000 vs Rs 2,460). Cancer OOP rendered 1.05% of affected households newly impoverished at the $3.20 threshold. The concentration index for CHE-10 was −0.063, indicating pro-poor inequity in relative burden despite a positive index (+0.143) for absolute OOP. Weighted logistic regression identified household consumption (OR 0.80; p<0.001) and household size (p<0.001) as significant protective determinants; insurance coverage was directionally protective but non-significant, likely reflecting limited statistical power.
CONCLUSIONS: Cancer care imposes substantial catastrophic and impoverishing financial burdens on Indian households, disproportionately affecting lower-wealth quintiles. The divergence between absolute and relative concentration indices highlights a critical inequity in financial protection. Expansion of targeted insurance coverage and strengthening of public oncology capacity, particularly for medicines represent evidence-based priorities for reducing cancer-attributable financial hardship in India.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EE396
Topic
Economic Evaluation, Epidemiology & Public Health, Real World Data & Information Systems
Topic Subcategory
Cost/Cost of Illness/Resource Use Studies
Disease
Oncology