Description
The execution of data transformations for reporting on an enterprise level data source can be resource intensive. In addition, target patient cohorts are at greater risk for inconsistencies across reports when multiple developers mine data directly from large enterprise systems. We developed a Geriatric Scholars Data Repository (GSDR) using a nontraditional extract, load, transform (ELT) process to further isolate a population of data so that it can be mined more efficiently while improving cohort consistency across reports.
Describe the new knowledge and additional skills the participant will gain after attending your presentation.: This abstract is intended to be submitted as a poster submission. The audience will learn about the difference between a traditional ETL vs. non-traditional ELT approach to setting up a clinical data repository (CDR) for reporting needs. More specifically, the advantages to using an ELT will be highlighted, most notably how the design supports a staging table architecture that allows for incremental data extraction. This abstract submission will help other teams learn about ways in which they could optimize there data management workflows that they have developed in support of clinical decision making and quality improvement activities.
Authors:
Zachary Burningham (Presenter)
Veterans Affairs / University of Utah
Brian Sauer, Veterans Affairs / University of Utah
Jianwei Leng, Veterans Affairs / University of Utah
Shardool Patel, Veterans Affairs / University of Utah
Ahmad Halwani, Veterans Affairs / University of Utah
Regina Richter, VA Greater Los Angeles Healthcare System
Tina Huynh, Veterans Affairs / University of Utah
Betty Kramer, VA Greater Los Angeles Healthcare System
Presentation Materials: