Relationships among interventions and health literacy outcomes for sub-populations: A data-driven approach

Objectives: The goals of this study were to examine relationships among health literacy and outcomes for sub-populations identified within a large, multi-dimensional Omaha System dataset. Specific aims were to extract sub-populations from the data using Latent Class Analysis (LCA); and quantify the change in knowledge score from pre- to post-intervention for common sub-populations. Design: Data-driven retrospective study using statistical modeling methods. Sample: A set of admission and discharge cases, captured in the Omaha System, representing 65,468 cases from various health care providers. Measures: Demographic information and the Omaha System terms including problems, signs/symptoms, and interventions were used as the features describing cases used for this study. Development of a mapping of demographics across health care systems enabled the integration of data from these different systems. Results: Knowledge scores increased for all five sub-populations identified by latent class analysis. Effect sizes of interventions related to health literacy outcomes varied from low to high, with the greatest effect size in populations of young at-risk adults. The most significant knowledge gains were seen for problems including Pregnancy, Postpartum, Family planning, Mental health, and Substance use. Conclusions: This is the first study to demonstrate positive relationships between interventions and health literacy outcomes for a very large sample. A deeper analysis of the results, focusing on specific problems and relevant interventions and their impact on health literacy is required to guide resource allocation in community-based care. As such, future work will focus on determining correlations between interventions for specific problems and knowledge change post-intervention.