Association for Public Policy Analysis & Management

A persistent question for economists and policymakers is how to allocate resources in order obtain both equity and efficiency in the benefits distribution. A traditional approach is a social welfare function to analyze the trade-off between maximizing benefits and obtaining an equitable distribution, but one of the main problems with this is how to measure the value of individual preferences.

Right to health litigation (RHL) refers to individuals suing the government because their right to health –minimum standard of health to which all individuals are entitled- is not being satisfied and can offer insight into said preferences. If we accept that resources are limited and that healthcare systems plan strategically how to use them, a court that decides on these cases will be imposing a different use for resources or will not change anything if they deny the claim.

The court becomes a resource-allocation mechanism and I will focus on understanding the implications of this, first is the new allocation increasing welfare (in terms of the benefits distribution and costs)? Second, if court decisions facilitate increased consumption of healthcare (by ordering the government to provide care) could this be interpreted as moral hazard (defined as increased healthcare consumption due to costs being paid by the government not the individual)?

I use the case of RHL in Costa Rica. The country has a universal tax-funded health care system which has since 1941 provided health care via the Costa Rican Social Security System (CCSS) and has consistently kept the country having some of the best health indicators of the region. I build a database using all the RHL cases where a drug was requested to treat cancer from 1991 to 2016.

From the cases I observe the individual’s characteristics, their current treatment and diagnosis, the drug requested, and the defense components. To construct variables for expected benefits (median time to disease progression, survival time, expected number of doses) I reviewed medical reference standards. Last, I use the acquisition contracts from the CCSS were they buy drugs to know the price they paid per dose after the court decision, and calculate the cost of treatment for each case.

I expect variation at a drug-case level and set up a probit model with the court decision as the binary dependent variable. The explanatory variables will be expected benefits and costs, with case characteristics and year dummies as controls. From these regressions I expect to find which factors explain the court’s decision. Using the probability of approval for each case-drug I can calculate an estimate of the expected benefits gained and costs incurred.

Also, I examine the subset of drugs that were not part of the List of Official Medications (LOM) of the CCSS at the time of the court case. The LOM consists of drugs deemed cost-effective and which are provided to patients at no cost based on physician discretion. If a requested drug was later added to these lists any moral hazard from their increased consumption would not be a loss in welfare.