Health insurance doesn’t provide financial risk protection to poor, says study2 min read . Updated: 27 Mar 2019, 03:40 PM IST
- The study comprehensively reviewed the past health schemes of the government for achieving the universal health coverage that has become a policy goal in most developing economies
- Centre last year launched the AB-PMJAY that aims to cover bottom 40% of the population, based on socio economic caste census
New Delhi: There is a need for government’s ambitious scheme Ayushman Bharat- Prime Minister’s Jan Aarogya Yojana (AB-PMJAY) to re-engineer the data systems for a more robust implication as health insurance schemes have not been fruitful in giving financial risk protection to poor families in the past, a latest study has pointed out.
The study titled--Role of insurance in determining utilization of healthcare and financial risk protection in India—published in the latest issue of PLOS ONE journal has concluded that “Health insurance in its present form does not seem to provide requisite improvement in access to care or financial risk protection."
The study done by School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, Health Policy Research Unit, Institute of Economic Growth, and Indian Institute of Public Health has comprehensively reviewed the past health schemes of the government for achieving the universal health coverage that has become a policy goal in most developing economies.
The researchers assessed the association of health insurance schemes in general, and RSBY (Rashtriya Swasthya Bima Yojana) (National Health Insurance Scheme) in particular, on extent and pattern of healthcare utilization. Researchers also assessed the relationship of health insurance and RSBY on out-of-pocket (OOP) expenditures and financial risk protection (FRP). The researchers analyzed 12134 households and 62335 individuals in Haryana, Gujarat and Uttar Pradesh state.
“We found a statistically significant difference among the insured and non-insured; as well as among the RSBY enrolled and non-RSBY enrolled bottom 2 poorest quintiles–in terms of either rates of reporting illness, hospitalization or the extent to which public sector was used for hospitalization. Surprisingly, those enrolled under RSBY had a significantly higher odds of facing catastrophic health expenditures," said Shankar Prinja, author of the study.
Mean OOP expenditures for outpatient care among insured and uninsured were ₹961 and ₹840 and ₹32573 and ₹24788 for an episode of hospitalization respectively. According to the study findings, the prevalence of catastrophic health expenditure for hospitalization was 28% and 26% among the insured and uninsured population respectively.
“Moving over the rhetoric for the need for universal health coverage, several policy discourses in India currently focus on ‘how’ to achieve this. The question of whether to go via the supply-side funded public sector route or using demand side financing mechanisms such as recently introduced publicly financed health insurance schemes becomes inevitable," said Prinja.
Researchers argued that it is imperative to evaluate the existing schemes in terms of their impact on increasing access to healthcare utilization and providing financial risk protection to targeted groups. The extent of evidence so far, especially for financial risk protection, is inadequate. Moreover, the direction of findings is ambiguous, the study said.
Centre last year launched the AB-PMJAY that aims to cover bottom 40% of the population, based on socio economic caste census, with an insurance coverage of ₹up to ₹5 lakh for hospitalization. The scheme is being looked as a tool to achieve the universal health coverage.
“Our study findings hold significant importance for future research which may be done in the context of Government of India’s Ayushman Bharat Prime Minister’s Jan Aarogya Yojana. As the scheme is still in its early implementation phase, there is a need to re-engineer the data systems such that such indications of self-selection are derived from routine enrolment data," said Prinja.
“Further, researchers involved in doing interim and end-term impact evaluations should consider introducing designs such that more robust control population is selected so that causal implications are more robust," he said.