Question

U.S. citizens are eligible for Medicare, a national health insurance system for the elderly, the day they turn 65 years old. Many believe that people with health insurance are less likely to die prematurely because they will be more likely to seek treatment and doctors will be more willing to conduct tests and procedures for them.

Explain how you could use regression discontinuity in this setting to estimate the relationship between health insurance coverage and premature death. Be sure to define all of the variables in your model. Is your design one of “sharp” or “fuzzy” discontinuity?

Answer 1

Health insurance is a scheme is an assistance provided for the citizens to cover the risk of financial difficlties fully or partially due to health related issues. The main objective of health insurance is to provide timely medical assistance to the people whe are in need without considering medical expenses. Hospital charges, ambulance charges, etc. comes under this package.

The following are the benefits of health insurance.

1. coverage against medical expenses

2.coverage against critical illness

3. Cashless claim benefit

4.Additional protection over and above emplyee cover.

5. Tax benefits

6. In addition to the above benefits people who are above the age of 65 used get certain other types of health insurance benefits.

Regression implies a reversion backwards. On the other hand discontinuity describes an unnatural jump or shift to a continuous process. Hence the term regression-discontinuity stands for determining whether the treatment is effective. The key feature of this design is assignment based on a cut of value.  

The intrepretation of the result of regression-discontinuity design is that we should know who the exact group who receive the total benefit. Inshort the strength of theRD design is mostly depended on two major facors -

1. The assumption that there is no discontinity in the pre-post relationship which coincides with the cut off point.

2. the degree to which can understand and correctly model the pre post relationship.

In the sharp condition the probability of people who gets heath insurance coverage is 0 - 1 %. But on the other hand in fuzzy situations the probability of treatment is discontinuous. Even those group of people who did not even take part the test also may have chance to come into the list.

Hence we can conclude that under this sharp two - way test system premature death can be avoided maximum by providing better treatment at the right time, providing ambulance facilities and other life support instruments and there by we can save time and increase peoples' life span. In most cases money what matters. But in the case of people those who are under health insurance coverage  are in safe zone.