The implications of using adjusted versus unadjusted methods to measure health care disparities at the practice level

Abstract

Reducing disparities in care requires that health care providers identify populations at risk for suboptimal quality of care. Stratified analyses are often used to examine disparities (eg, by race or sex). However, stratified analyses can be misleading if the variables are confounded. The authors examined disparities in quality within a large ambulatory care practice using both unadjusted and adjusted methods for 18 measures. In unadjusted analyses, differences in quality were identified for 9 measures by race. However, in analyses adjusted simultaneously for race, sex, age, socioeconomic status, and chronic medical conditions, racial differences were apparent for only 4 measures. Women received lower quality care for 4 measures in both unadjusted and adjusted analyses. The pattern of observed disparities can differ significantly based on whether unadjusted or adjusted methods are applied. Health care organizations should consider the routine use of adjusted methods to measure disparities in order to better inform disparity reduction initiatives.