Predictive Model for Measuring Health Literacy

A Part of the Q-DART Toolset

A RAND project currently underway in Missouri is developing a predictive model of health literacy to estimate levels of health literacy in small geographic areas (census tracts) using the Q-DART GIS mapping and indirect estimation tools.

Low health literacy remains a formidable barrier to reducing gaps in quality and improving outcomes of care. According to the recent National Assessment of Health Literacy, 36 percent of American adults have health literacy levels rated at "basic or below," and only 12 percent are "proficient." Although low health literacy is common, it tends to be more prevalent in certain minority groups–the elderly, and those with low income and education. Consequently, low-health literacy is thought to play a key role in racial/ethnic and socioeconomic health and health care disparities. The estimates of health literacy generated by the RAND predictive model are based on data from the National Assessment of Adult Literacy, census-derived variables describing the population, and other characteristics of each census tract. RAND will also develop interactive maps to display the results.