The goal of this IMLS-funded proposal was to create a workable model for generating patient-specific information prescriptions. The project integrated both health literacy levels and learning style preferences to improve the usefulness of condition-specific health information provided to patients during healthcare encounters. Central to this effort was the team's hypothesis that this combined approach would improve patients' ability to learn and retain their health information. Highly individualized information prescriptions guided by factors such as patient literacy levels and learning styles were created; prescriptions were generated dynamically via a web tool that maps patient attributes against hypertension and diabetes information to produce a customized information packet.
In our initial studies, which were conducted in the emergency department setting, we found that tailoring health information about hypertension to patients’ health literacy level improved their understanding of the material (Koonce et al., 2011). When the information was tailored to both health literacy and learning style preferences, patients demonstrated greater understanding of the material than when it was tailored to health literacy alone (Koonce et al., 2015; Giuse et al., 2012). We demonstrated the reusability of this model in the community clinic setting for other conditions, including diabetes, and additionally found evidence that receiving the tailored materials resulted in greater knowledge retention (Koonce et al., 2015).