Format

Send to

Choose Destination
J Biomed Inform. 2014 Dec;52:231-42. doi: 10.1016/j.jbi.2014.07.006. Epub 2014 Jul 19.

Modular design, application architecture, and usage of a self-service model for enterprise data delivery: the Duke Enterprise Data Unified Content Explorer (DEDUCE).

Author information

1
Duke Health Technology Solutions, Duke University Health System, Durham, NC, United States. Electronic address: monica.horvath@duke.edu.
2
Duke Translational Medicine Institute, Duke University School of Medicine, Durham, NC, United States.
3
Duke Health Technology Solutions, Duke University Health System, Durham, NC, United States.
4
Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, United States.
5
Duke Health Technology Solutions, Duke University Health System, Durham, NC, United States; Department of Pediatrics, Duke University School of Medicine, Durham, NC, United States.

Abstract

PURPOSE:

Data generated in the care of patients are widely used to support clinical research and quality improvement, which has hastened the development of self-service query tools. User interface design for such tools, execution of query activity, and underlying application architecture have not been widely reported, and existing tools reflect a wide heterogeneity of methods and technical frameworks. We describe the design, application architecture, and use of a self-service model for enterprise data delivery within Duke Medicine.

METHODS:

Our query platform, the Duke Enterprise Data Unified Content Explorer (DEDUCE), supports enhanced data exploration, cohort identification, and data extraction from our enterprise data warehouse (EDW) using a series of modular environments that interact with a central keystone module, Cohort Manager (CM). A data-driven application architecture is implemented through three components: an application data dictionary, the concept of "smart dimensions", and dynamically-generated user interfaces.

RESULTS:

DEDUCE CM allows flexible hierarchies of EDW queries within a grid-like workspace. A cohort "join" functionality allows switching between filters based on criteria occurring within or across patient encounters. To date, 674 users have been trained and activated in DEDUCE, and logon activity shows a steady increase, with variability between months. A comparison of filter conditions and export criteria shows that these activities have different patterns of usage across subject areas.

CONCLUSIONS:

Organizations with sophisticated EDWs may find that users benefit from development of advanced query functionality, complimentary to the user interfaces and infrastructure used in other well-published models. Driven by its EDW context, the DEDUCE application architecture was also designed to be responsive to source data and to allow modification through alterations in metadata rather than programming, allowing an agile response to source system changes.

KEYWORDS:

Application development; Cohort definition; Information systems; Medical informatics applications; Research query tool; System design and architecture

PMID:
25051403
PMCID:
PMC4335712
DOI:
10.1016/j.jbi.2014.07.006
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center