An Analysis of Intermediate DISH Outcomes using EMR Data Abstraction and HLM Trajectory Analysis
The burden of diabetes on the American health care system is apparent to all who participate in the care and management of ill and injured people. The monetary and social cost attributed to diabetes is massive, and the conditions in Philadelphia are worse than national averages. The diabetes group medical visit was designed as one method to efficiently counter the deleterious effects of diabetes as well as teach and empower patients to self-manage their conditions. At Jefferson Family Medicine Associates, a group visit program named Diabetes Information and Support for your Health (DISH) was founded in order to incorporate group visits into the division’s medical practice. A study was conducted by Reitz, et. al. analyzing DISH’s efficacy in improving clinical outcomes over an intermediately long time scale. An additional, extensive literature review was conducted on group visits models. The current study’s purpose was validate the results of the Reitz study and to determine if the DISH program improved diabetes related clinical outcomes over the long-term. The primary outcome measures evaluated were patient HbA1c, LDL, BMI, and blood pressure. This was conducted through a retrospective analysis, utilizing algorithmic data abstraction from the health system’s electronic medical record system, and analyzing said data with hierarchical linear modeling (HLM). Both data abstraction and HLM were proposed as innovative, robust, and efficient means of conducting longitudinal, retrospective data analysis. The study found that the only outcome that significantly improved and was explained, to some degree, by DISH attendance was HbA1c. LDL was excluded from analysis due to flawed data. Even with marginally successful evaluation of outcomes, the study did, however, provide a precedent for more robust reevaluation techniques.
Presentation: 30 minutes
Recommended CitationPatel, Viraj, "An Analysis of Intermediate DISH Outcomes using EMR Data Abstraction and HLM Trajectory Analysis" (2013). Master of Public Health Thesis and Capstone Presentations. Presentation 107.