· Identify a policy that is not usually intended to be a health policy but that you think may have important health implications.
A policy such as which neighborhoods to place refugees could have major health implications such as the one described in the attached article. The authors found that diabetes risk increased depending on the level of resource deprivation in the neighborhood to which refugees were randomly assigned. Given this, one could assume that a policy that places refugees on the basis of language or country of origin would have significant health implications.
· Describe why an evaluation of that policy is informative (e.g., determining effects of the policy, or primarily a test of hypothesized mediators).
Evaluating policies on the placement of refugees and immigrants can inform us about what factors drive health disparities, such as the one exemplified in the aforementioned article. It can also inform us on future policy decisions.
· Specify the outcomes and populations you think most affected or least affected by the policy.
The populations most affected by refugee placement policies are most likely the refugees, as they have little control over their new environment. The least affected group is the native population, though it could be argued that their access to medical resources are also impacted.
· Propose a study design to evaluate the policy.
The attached article uses a quasi-natural experimental design, which has the advantage of true randomization and large sample size. Because refugee resettlement in the United States is based on “biographical data” of the refugees (https://www.cfr.org/backgrounder/how-does-us-refugee-system-work), evaluating the effect of this strategy on health may require other techniques such as propensity scoring or matching. For example, if we matched refugees with similar health predispositions (age, weight, chronic diseases, education, etc.) between two different geographical locations, we could assess the effects of geography on health.
· Describe biggest challenge to implementing and drawing inferences about the impact of the policy on health.
Results from such studies are often very sensitive to model specifications. Details of the intervention may affect the outcomes. For example, perhaps refugees tend to be settled in more urban areas of one state and more rural areas of another complicating the comparison between two states. Moreover, the sheer number of variables when assessing health policy can be staggering, increasing the difficulty of designing an unbiased study. Finally, it is often difficult to recruit participants for studies on health policy because these data are not often recorded, limiting statistical power.