Bridging the gap between health insurance eligibility and uptake: A multistate quantitative analysis of entitlement-based verification patterns under India’s PM-JAY Scheme
5 affiliations
- 1Heidelberg Institute of Global Health, Medical Faculty and University Hospital, Heidelberg University, Heidelberg, Germany
- 2University of Cambridge, School of Clinical Medicine, Addenbrooke’s Hospital, Cambridge, United Kingdom
- 3Economic and Social Systems, German Institute of Development and Sustainability (IDOS), Bonn, Germany
- 4Department of Population Health Sciences, School of Life Course and Population Sciences, King’s College London, King’s College London, London, United Kingdom
- 5Asian Development Bank, Mandaluyong City, Metro Manila, Philippines
Abstract
Publicly-funded health insurance schemes, wherein governments subsidize insurance contributions for disadvantaged groups, are a key strategy under universal health coverage. India’s Pradhan Mantri Jan Arogya Yojana (PM-JAY) uses an entitlement-based approach whereby approximately 700 million beneficiaries are automatically eligible for scheme benefits, subject to a simplified identity verification procedure instead of enrolment. This study investigates the determinants of undergoing verification among PM-JAY’s target population to identify underserved groups and inform strategies to expand coverage. We used cross-sectional survey data from 2019-2020, covering 50,002 individuals across five states. We examined individual and household characteristics associated with verification using logistic regression models with district-level random effects, and beneficiary experiences with the verification process. About one-fifth of eligible individuals had verified their status within a year of launch. Verification was more likely among older adults, with those ≥60years having higher odds than those 0–15 years of age (adjusted Odd Ratio [AOR] 2.339; 95% CI 2.071-2.641). Those with higher education had higher odds than those with no formal education (AOR 2.303; 95% CI 2.048-2.590), those with prior PFHI enrolment had higher odds compared to those not enrolled (AOR 1.947; 95% CI 1.827-2.075), and those with chronic illness had higher odds than those without (AOR 1.175; 95% CI 1.071-1.289). Women and household members other than spouses were less likely to verify. Disadvantaged castes and minority religions demonstrated relatively higher verification rates. District-level factors explained nearly one-third of variability, indicating that infrastructure and implementation capacity differences influence uptake. Many beneficiaries reported long wait times, varying documentation demands, and informal payments during verification. Addressing these barriers requires gender-sensitive outreach, streamlined household-wide verification, and strengthened local health system capacity. Policy reforms that simplify verification, ensure equitable access, and strengthen health infrastructure are vital to advancing effective universal health coverage for India’s most vulnerable populations.
Related
- Eligibility criteria for the UK Winter Fuel Payment: are we targeting the right people?
- Probabilistic Streamflow Forecasts for Mississippi River Navigation Risk and Parametric Insurance
- On CO2 sequestration in concrete aggregate via carbonation: simulation and experimental verification
- High-resolution 3D turbulence measurements with different quadcopter uncrewed aerial systems: verification and validation for single- and multi-vehicle measurements
- Near-real-time, meter-scale 3D urban wind modeling for low-altitude micrometeorology: numerical verification of a GPU-accelerated lattice Boltzmann framework
BibTeX
@article{srivastava2026bridging,
title = {{Bridging the gap between health insurance eligibility and uptake: A multistate quantitative analysis of entitlement-based verification patterns under India’s PM-JAY Scheme}},
author = {Swati Srivastava and Tads Ciecierski-Holmes and Christoph Strupat and Divya Parmar and Nishant Jain and Manuela De Allegri},
journal = {PLOS Global Public Health},
year = {2026},
month = oct,
doi = {10.1371/journal.pgph.0007451},
url = {https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0007451},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Bridging the gap between health insurance eligibility and uptake: A multistate quantitative analysis of entitlement-based verification patterns under India’s PM-JAY Scheme
AU - Swati Srivastava
AU - Tads Ciecierski-Holmes
AU - Christoph Strupat
AU - Divya Parmar
AU - Nishant Jain
AU - Manuela De Allegri
PY - 2026
DA - 2026/10/13
JO - PLOS Global Public Health
DO - 10.1371/journal.pgph.0007451
UR - https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0007451
AB - Publicly-funded health insurance schemes, wherein governments subsidize insurance contributions for disadvantaged groups, are a key strategy under universal health coverage. India’s Pradhan Mantri Jan Arogya Yojana (PM-JAY) uses an entitlement-based approach whereby approximately 700 million beneficiaries are automatically eligible for scheme benefits, subject to a simplified identity verification procedure instead of enrolment. This study investigates the determinants of undergoing verification among PM-JAY’s target population to identify underserved groups and inform strategies to expand coverage. We used cross-sectional survey data from 2019-2020, covering 50,002 individuals across five states. We examined individual and household characteristics associated with verification using logistic regression models with district-level random effects, and beneficiary experiences with the verification process. About one-fifth of eligible individuals had verified their status within a year of launch. Verification was more likely among older adults, with those ≥60years having higher odds than those 0–15 years of age (adjusted Odd Ratio [AOR] 2.339; 95% CI 2.071-2.641). Those with higher education had higher odds than those with no formal education (AOR 2.303; 95% CI 2.048-2.590), those with prior PFHI enrolment had higher odds compared to those not enrolled (AOR 1.947; 95% CI 1.827-2.075), and those with chronic illness had higher odds than those without (AOR 1.175; 95% CI 1.071-1.289). Women and household members other than spouses were less likely to verify. Disadvantaged castes and minority religions demonstrated relatively higher verification rates. District-level factors explained nearly one-third of variability, indicating that infrastructure and implementation capacity differences influence uptake. Many beneficiaries reported long wait times, varying documentation demands, and informal payments during verification. Addressing these barriers requires gender-sensitive outreach, streamlined household-wide verification, and strengthened local health system capacity. Policy reforms that simplify verification, ensure equitable access, and strengthen health infrastructure are vital to advancing effective universal health coverage for India’s most vulnerable populations.
SN - 2767-3375
ER -