Development of an electronic health records datamart to support clinical and population health research.

Journal Article (Journal Article)

INTRODUCTION: Electronic health record (EHR) data have emerged as an important resource for population health and clinical research. There have been significant efforts to leverage EHR data for research; however, given data security concerns and the complexity of the data, EHR data are frequently difficult to access and use for clinical studies. We describe the development of a Clinical Research Datamart (CRDM) that was developed to provide well-curated and easily accessible EHR data to Duke University investigators. METHODS: The CRDM was designed to (1) contain most of the patient-level data elements needed for research studies; (2) be directly accessible by individuals conducting statistical analyses (including Biostatistics, Epidemiology, and Research Design (BERD) core members); (3) be queried via a code-based system to promote reproducibility and consistency across studies; and (4) utilize a secure protected analytic workspace in which sensitive EHR data can be stored and analyzed. The CRDM utilizes data transformed for the PCORnet data network, and was augmented with additional data tables containing site-specific data elements to provide additional contextual information. RESULTS: We provide descriptions of ideal use cases and discuss dissemination and evaluation methods, including future work to expand the user base and track the use and impact of this data resource. CONCLUSIONS: The CRDM utilizes resources developed as part of the Clinical and Translational Science Awards (CTSAs) program and could be replicated by other institutions with CTSAs.

Full Text

Duke Authors

Cited Authors

  • Hurst, JH; Liu, Y; Maxson, PJ; Permar, SR; Boulware, LE; Goldstein, BA

Published Date

  • June 23, 2020

Published In

Volume / Issue

  • 5 / 1

Start / End Page

  • e13 -

PubMed ID

  • 33948239

Pubmed Central ID

  • PMC8057430

Electronic International Standard Serial Number (EISSN)

  • 2059-8661

Digital Object Identifier (DOI)

  • 10.1017/cts.2020.499


  • eng

Conference Location

  • England