ISSN (Print) - 0012-9976 | ISSN (Online) - 2349-8846

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Experiences with Government-sponsored Health Insurance Schemes in Indian States

The implications of expanding government-sponsored health insurance schemes in India are analysed from a fiscal perspective. The experiences of two of the earliest and largest GSHI schemes of the country implemented in Andhra Pradesh and Tamil Nadu are examined. The results suggest that the expansion of the GSHI schemes may skew expenditure away from primary and secondary care towards tertiary care if the fiscal space is limited. A competitive public health system may help in containing costs and the corresponding fiscal burden. The effectiveness of public spending through such schemes is ambiguous.

 

Health Insurance in Private Hospitals

Private hospitals are expected to play a key role in the implementation of government-sponsored health insurance schemes in India. Examining the availability and spread of private hospitals in the country and an analysis of their empanelment in government-sponsored health insurance schemes reveal that in low-income states of the country, empanelment of private hospitals by insurance companies is low and concentrated in a few pockets. This may indicate differences in entry conditions or low willingness of private hospitals to participate in these schemes, which has implications for the access to healthcare and insurance for the poor.

Utilisation, Fund Flows and Public Financial Management under the National Health Mission

Since April 2014, funds for various centrally sponsored schemes, including the National Health Mission, are being transferred to implementing agencies through state treasuries. This has added an additional layer in the institutional structure for nhm fund flows. We analyse the utilisation of nhm funds in 29 states in two recent years, and the time taken for release of these funds from state treasuries to implementing agencies in three selected states: Bihar, Maharashtra, and Odisha. On average, only about 55% of funds allocated for nhm were utilised in 2015–16 and 2016–17. In Bihar and Maharashtra, this was partly due to significant delays in release of funds from state treasuries to implementing agencies. The delays were a result of complex administrative procedures associated with the release of nhm funds from state treasuries.

Estimating Public Spending on Health

The use of information on withdrawals by Drawing and Disbursing Officers for improving the estimates of public spending for National Health Accounts in India is illustrated. Using information from Karnataka and Rajasthan, the study highlights the advantages of combining DDO-level information with budgetary data. The significant benefits of using DDO-level information in India have implications for better estimates of public spending and health policy design.

Fourteenth Finance Commission

Preliminary evidence on the impact of the recommendations of the Fourteenth Finance Commission suggests that there has been an increase in central transfers and social sector expenditures in a number of states in 2015–16. This evidence is biased upwards due to two factors. First, much of the gains have been measured with respect to a low base year. Second, the inferences are affected by systematic differences between actuals, revised estimates, and budget estimates. Using a modified base and comparable estimates for 15 major states, it is seen that these are much smaller. Besides, in most states, social services have received a lower priority over economic services in 2015–16.

Potential Selectivity Bias in Data

A number of recent firm-level studies on Indian industry have used data available from Prowess, a database of Indian firms compiled by the Centre for Monitoring Indian Economy. This paper attempts to identify the extent and nature of potential selectivity biases in samples drawn from Prowess. The paper shows that the distributional properties of samples drawn from Prowess are not consistent over the years. Also, the distributional properties of a balanced panel extracted from the database are not consistent with those of the full sample in different years.

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