Examining socioeconomic health disparities using a rank-dependent R\'{e}nyi index

TL;DR

This paper introduces a new two-parameter health disparity index, the rank-dependent Rényi index, which better captures socioeconomic health inequalities and is robust to distributional changes, with applications to U.S. health data.

Contribution

The paper develops and evaluates a novel rank-dependent Rényi index for measuring health disparities that accounts for socioeconomic rank and is more robust than existing indices.

Findings

The rank-dependent RI is more robust to distributional changes.

Methodology is validated using U.S. health survey and registry data.

The index can inform policy prioritization based on socioeconomic health disparities.

Abstract

The R\'{e}nyi index (RI) is a one-parameter class of indices that summarize health disparities among population groups by measuring divergence between the distributions of disease burden and population shares of these groups. The rank-dependent RI introduced in this paper is a two-parameter class of health disparity indices that also accounts for the association between socioeconomic rank and health; it may be derived from a rank-dependent social welfare function. Two competing classes are discussed and the rank-dependent RI is shown to be more robust to changes in the distribution of either socioeconomic rank or health. The standard error and sampling distribution of the rank-dependent RI are evaluated using linearization and resampling techniques, and the methodology is illustrated using health survey data from the U.S. National Health and Nutrition Examination Survey and registry data from the U.S. Surveillance, Epidemiology and End Results Program. Such data underlie many population-based objectives within the U.S. Healthy People 2020 initiative. The rank-dependent RI provides a unified mathematical framework for eliciting various societal positions with regards to the policies that are tied to such wide-reaching public health initiatives. For example, if population groups with lower socioeconomic position were ascertained to be more likely to utilize costly public programs, then the parameters of the RI could be selected to reflect prioritizing those population groups for intervention or treatment.