more to help educate people about how to take their medicines, why they are taking them, and how to be adherent. The investment resulted in a seven-to-one return in a short time period. The important thing is to think about how to focus limited resources in the most effective way.

When problems are identified in particular geographic areas, one must look carefully at what is going on in that community. For example, the National Health Plan Collaborative has data on Los Angeles, where Hispanic/Latino enrollees identified low quality of care for diabetes. The first idea for intervention was to send a letter with low-literacy levels of information in Spanish and English to thousands of members who had diabetes and Spanish surnames. But after looking at other variables, it was decided to focus the intervention on the linguistically isolated areas. In developing interventions, Lurie said, one must think much more comprehensively about the underlying drivers for health care and outcomes.

Another participant said the two presenters have both developed predictive models using demographics. Hanchate benchmarked his model to the TOFHLA, and Lurie used the NAAL. How might one decide which model would be more useful to use in certain situations? If one desires a health literacy measurement for a community, what results might be obtained using the different models? What would make one choose one model over the other?

Hanchate said the DAHL was an attempt to achieve balance between making the model as rich as possible without making it so complicated that it could not be replicated with other datasets being used for comparison.

Lurie said if one wants to look at the contribution of predictive health literacy to outcomes available in a secondary dataset, one is limited to data that exist in those datasets. The set of variables used in the RAND project is used in most datasets. The set of variables used in the DAHL is a smaller set and is available in the NHIS and others.

Dr. Angela Mickalide of the Home Safety Council said the project on health literacy mapping has implications for injury prevention as well. In Montgomery County, MD, for example, the fire department worked with literacy teachers to develop a map of literacy in the county. They overlaid that map with a map of the fire incidents, deaths, and injuries and found nearly a one-to-one perfect match, thereby identifying where efforts should be targeted. The Home Safety Council developed a home safety literacy project in which literacy teachers are provided with tools to teach students to read by using materials on fire safety, disaster preparedness, and poisoning prevention.