Disparities in Cancer Prevention and Control

Much of the disparity in cancer outcome is a reflection of type, timeliness, and continuity of cancer care rather than the disease itself
Investigators:
Norman Daniels

Cancer is a leading cause of death in the United States although advancements in cancer risk stratification, chemoprevention, effective screening strategies, and improvements in cancer treatments all contribute to observed declines in cancer mortality in the United States. However, these advancements have a differential reach across Americans with the undesirable impact of increasing health disparities in cancer. Many ethnic minorities develop cancer more frequently than the majority of the US white population. African-American men, for example, develop cancer 15% more frequently than Caucasian men. Some specific forms of cancer affect other ethnic minority communities at rates up to several times higher than national averages. Many ethnic minorities also experience poorer cancer survival rates than whites. Much of the disparity in cancer outcome is a reflection of type, timeliness, and continuity of cancer care rather than the disease itself. Widespread national efforts have been underway to eliminate health disparities.

Traditionally, decision-analytic and cost-effectiveness models focus on maximizing the health of a population (possibly under resource constraints) and do not explicitly address distributional issues of who in the population receive the costs or benefits.  This project involves the development of a generalizable model that will serve as a framework for incorporating and evaluating disparities in decision-analytic policy models. Previously constructed colorectal, cervical and breast models are being modified to reflect differences in underlying biology, disease risk, access to preventive and therapeutic health services, and quality of care – stratified, where data will allow, by race. We are analyzing the ethical dimensions of health disparities that bear on cancer outcomes, developing a typology of disparities with different ethical import, and integrating the results of this analysis into a decision-analytic framework. Using an integrative approach of decision science and ethical analysis, these modified simulation models will be used to address socially relevant policy questions that disproportionately affect certain segments of the population.