Using Equity Measures to Evaluate Health and Social Policies and Interventions on Health Equity

With the rising interest in health equity, equity measures first developed in other disciplines have been applied to health outcomes. The Concentration Curve and Concentration Index reveal the distribution of health outcomes as they relate to income.  The Kakwani progressivity index (KPI) can reveal how health inequality may be 'better' or 'worse' than income inequality.  These equity measures use the whole distribution of income to evaluate health equity.  Other measures, such as the absolute index of inequality or relative index of inequality, partition the upper and lower portions of the population to evaluate disparity between the 'haves' and 'have-nots'.   Evaluating change in equity over time, and between groups, such as exposed and unexposed treatment groups, introduces new complications to their use.  When these measures are applied to health equity, they can be impacted by factors not initially considered by investigators.  The application of Concentration measures in health frequently use dichotomous outcomes, and the prevalence of the health outcome can affect the degree of inequity that is possible, with highly prevalent outcomes showing very little divergence from the line of equity.  Comparing concentration measures  to the inequality indices can produce contradictory and seemingly incompatible results.  Sample selection that alters the distribution of income from the population can also change the apparent equity of health outcomes.  A brief description of these issues and an example (the evaluation of a health policy intervention, a nurse home visitors program for at-risk families) provide a cautionary tale for their use.