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Approach to the Endogeneity of Health and Insurance Status

Approach to the Endogeneity of Health and Insurance Status

Most studies in the literature simply ignore the endogeneity of health insurance; some attempt to address it using a variety of techniques. We categorize the literature into three groups based on the extent to which they address this problem.

The first group, which we call “observational studies,” does little or nothing to acknowledge the endogeneity problem and contains by far the most studies. Most of these simply compare health outcomes for the insured to outcomes for the uninsured. 

Some use regression analyses to control for covariates such as income, age, gender, race, health behaviors like smoking, and comorbidities. We discuss these studies in Section IV. 

Our key finding is that such analyses – representing the vast majority of the studies of the association between health insurance and health – are confounded by both observable and unobservable difference between patients who do and do not have health insurance. 

This implies that these studies cannot provide much insight into the causal effect of health insurance on health. Moreover, the complexity of the underlying relationships makes it impossible to “sign” the bias that results from the omitted variables. 

The second group consists of “natural experiments,” also sometimes called “quasiexperiments.” These analyses rely on a policy change or some other exogenous event to introduce variation in health insurance coverage that is plausibly unrelated to health and other underlying determinants of health insurance coverage. 

These situations offer an opportunity to estimate the causal effect of insurance on health. Some natural experiments are quite small in scale: for example, the cancellation of veterans’ health care benefits for a small group of individuals. 

Small natural experiments are perhaps best thought of as case studies; we discuss several of these below. Other natural experiments are much broader in scale, such as the passage of Medicare in the U.S., or of Canada’s National Health Insurance plan. 

In Section V, we discuss in detail all of the quasi-experimental studies of which we are aware. The third group consists of true social experiments in which health insurance coverage is randomly assigned to individuals and subsequent health outcomes are compared across  experimental groups. 

This group corresponds to randomized clinical trials in the field of medicine, the gold standard of biomedical evidence. Only the RAND health insurance experiment falls into this category. We discuss it in Section VI. 

Which studies provide credible evidence that can be used to make inferences about the causal impact of health insurance on health? As we have mentioned, and explain in more detail below, we believe that only the quasi-experimental and experimental analyses offer any basis for making such inferences

Since these studies are far less numerous than observational studies, and their results are often quite different than those of the observational studies, this belief requires us to discount the stated conclusions of a great deal of published work. 

This belief does not mean that we think observational studies are uninteresting or without value. Quite the contrary: observational studies documenting differences in medical care use and health outcomes between insured and uninsured populations provide information that is essential both to researchers and to policymakers because they illustrate disparities health care utilization and health outcomes among identifiable groups that may suggest the need to better understand and ultimately address these disparities. 

But we do not always agree with the authors of these studies about whether inferences about the impact of insurance coverage on health outcomes that can be drawn from their findings. In the following discussion of these three groups of studies, we explain the reasons for our strong preference in favor of experimental and quasi-experimental evidence.
Bona Pasogit
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