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Social Health and Rural Populations

The effect of social health insurance is often thought to be universally positive. The results, however, are mixed at best.
Social Health and Rural Populations

A recent paper about social health insurance and rural populations in the European Journal of Health Economics gives a nice analysis on the effect top-down insurance can have on rural populations. The authors, Green, Hollingsworth and Yang, look at how the roll-out of health insurance by the State has gone in China. The reason they chose his particular scheme is because it forms a natural experiment. Since it was voluntary, counties were not mandated to opt into it, and thus they did so unevenly. This makes it possible to compare data both temporally (how an area did before and after the scheme was adopted) as well as spatially (how did the experiences of areas which had adopted this scheme differ from those which had not at a given moment in time).


China historically relied on the Rural Cooperative Medical System (RCMS). This was a system built upon peasant communes and was financed by communal welfare funds. However, the late 1970s saw China transition into the Household Responsibility System leading to a collapse of the communes and the RCMS leaving 90% of all peasants uninsured. This led to sky-high medical costs. There were attempts to reestablish these kinds of systems by townships and villages individually, but they did not survive for long.

Thus, the New Cooperative Medical Scheme (NCMS), a public health insurance scheme in China aimed at rural areas, was established in 2003 with the aim of reducing catastrophic health spending among the peasantry. To quote from You and Kobayashi (2009):

In 2003, 96% of rural households in China lacked medical insurance, 38% of the sick did not seek medical attention, and medical debt forced many households to reduce food consumption. The ability to pay became an important determinant of access to health care. Large negative health shocks reduced annual income in rural China by an estimated 12.4%. Health care expenses caused 2.5% of households to fall below the poverty line in 1995, and 22% of poor households attributed their poverty to illness or injury in 1998. Illness has become a leading cause of poverty in rural areas. Urban–rural differences in financing and access to health care have also risen sharply.

This scheme was voluntary because by this time, the Chinese had become wary of government taxes and public trust in governmental intentions had been running low. The scheme was created to operate on a county level rather than village or township level and all management costs are paid by the central government. The enrolled households in participating counties are taxed at a flat rate (with allowances for poorer households).

Many studies have been conducted on this programme over the past years. In general, they have shown that while access to healthcare has improved tremendously, the average out of pocket cost and the risk of catastrophic medical expenditure has not reduced. However, Green, Hollingsworth and Yang have stated that most such studies have looked at the first few years of policy implementation and have not performed any follow-up, thus it might be informative to look at how the programme has done after a wider roll-out has been implemented.

Available data indicate that this programme has gone from covering around 10% of the rural population in 2003 to to 90% in 2008 to 99% in 2014. Since it is voluntary, however, that does not guarantee that everyone covered by this scheme is enrolled into it. While the reimbursement rate varies from county to county, on average, the reimbursement rate was targeted at 50% in 2009, increased to 70% in 2011, and then to 75% in 2015. It primarily aims to push people towards primary healthcare centres in rural areas, because travel costs associated with travelling to cities for to tertiary healthcare sites was found to be fairly high. It does this by providing more generous reimbursement for getting treated at primary healthcare centres. Government expenditure was directed towards improving the rural healthcare system, training more healthcare practitioners in rural healthcare, and staffing these healthcare centres better.


The authors get their data from the China Health and Nutrition Survey (CHNS). The key variable which they looked at was the kind of health insurance a person has. The authors compared people in counties which had not implemented NCMS with people enrolled in NCMS in order to reduce selection bias (e.g. someone deciding to not get NCMS-based insurance because they believe they are healthy enough to not need insurance or because they are too poor to afford the cess).

The authors use a logit model to estimate the effect of participating in the NCMS on medical care utilisation and out of pocket payments. The probability of out of pocket payments is modelled using a logit model and the amount paid is modelled using a generalised linear model. Unobserved confounding variables are accounted for using an Instrumental Variables approach. To quote the authors:

Following previous literature on impact evaluation of the NRCMS, insurance availability at the county level is used to derive an instrument for individual enrolment into the NRCMS. This is considered an appropriate IV because it satisfies the two requirements of validity: (1) there is a high correlation between the county NRCMS status and household insurance enrolment status, as shown in Tables 1, 2 where the coefficients of county NRMCS status in the first-stage regression are very large, and as we show later, these pass standard thresholds for detecting weak instruments; (2) the roll-out of the NRCMS across counties and over time can be treated as good as random conditional on community characteristics.

In order to integrate both spatial and temporal data, the authors look at province fixed events and time fixed events. This is able to capture differences between provinces as well as common events which affected all of them in a given year. The adoption of the NCMS by a county is used as an exogenous variable, because it has no effect on individual healthcare utilisation or expenses except through the means of the insurance. A 2-stage linear regression model is then used to evaluate the impact of insurance on the outcomes the authors are interested in, looking at different counties one at a time.

The Long-Term Effects of Expanding Social Insurance

The authors agree with previous studies which showed that there is little impact of this insurance scheme on out-of-pocket payments by patients. However, it was found that there is a marked increase in the use of village primary health centres as well as a reduction in patient load in city hospitals (which, as the authors note, just missed being statistically significant). This tells us that insurance does have the potential to change patterns of healthcare use in rural areas.

A more nuanced look at the results shows that the reduction in patient load at city hospitals tends to be driven by rich households, whose members actually had the option of going to city hospitals in the absence of insurance. These patients now seem to go towards township health centres, which are secondary-care centres. Poorer patients are the ones who seem to go towards primary care centres in villages through the NCMS. The authors also show that there is a reduction in out of pocket payments for poor households (though it is judged to be insignificant), and that people from more deprived provinces in the west seem to utilise village clinics more than those from richer provinces in the east.

While the results of this paper are in line with results from previous studies, it was found that aggregate results tend to mask effects on different slivers of the population. NCMS may have contributed towards correcting distortions int he rural healthcare system by directing people towards primary rural healthcare systems and reducing the usage of specialty tertiary care centres. However, it is not possible to verify whether this is happening due to the relative poverty of those who go to village clinics or due to an increase in quality among them. A clue that it may be the former comes from the fact that richer people tend to still go towards township secondary health centres, which seems to suggest that they are unwilling to compromise on the quality of healthcare.

It was also seen that the probability of incurring out of pocket payments did not go down as a result of this scheme. This may be because inpatient care, which is much more expensive than outpatient care, is only provided in tertiary hospitals, and thus the reimbursements provided by this scheme might be very low.

Policy recommendations

While the scheme has had an effect on reducing the number of people going for informal medical care to traditional doctors or self-medicating, it has not been a universal success in reducing out of pocket costs or changing healthcare utilisation. This, and the other results presented above may be of use in implementing policies in developing countries such as India:

  1. In order to keep reimbursement costs manageable, it is recommended to keep a tiered reimbursement structure which incentivises visiting primary health centres over tertiary care hospitals in order to reduce congestion at the latter
  2. Inpatient care needs to be subsidised in order to reduce average out of pocket payments
  3. Quality of healthcare at primary care centres needs to be increased in order to make sure that people continue visiting them and that the policy actually has a positive effect