A Harmonized Data Quality Assessment Terminology and Framework for the Secondary Use of Electronic Health Record Data

University of Colorado Anschutz Medical Campus · Kaiser Permanente · +16 more institutions

PubMed
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Abstract

Objective

Harmonized data quality (DQ) assessment terms, methods, and reporting practices can establish a common understanding of the strengths and limitations of electronic health record (EHR) data for operational analytics, quality improvement, and research. Existing published DQ terms were harmonized to a comprehensive unified terminology with definitions and examples and organized into a conceptual framework to support a common approach to defining whether EHR data is 'fit' for specific uses.

Materials And Methods

DQ publications, informatics and analytics experts, managers of established DQ programs, and operational manuals from several mature EHR-based research networks were reviewed to identify potential DQ terms and categories. Two face-to-face stakeholder meetings were used to vet an initial set of DQ terms and definitions that were grouped into an overall conceptual framework. Feedback received from data producers and users was used to construct a draft set of harmonized DQ terms and categories. Multiple rounds of iterative refinement resulted in a set of terms and organizing framework consisting of DQ categories, subcategories, terms, definitions, and examples. The harmonized terminology and logical framework's inclusiveness was evaluated against ten published DQ terminologies.

Citation impact

597
total citations
FWCI
58.35
Percentile
100%
References
66
Citations per year

Authors

20

Topics & keywords

Keywords
  • Terminology
  • Computer science
  • Context (archaeology)
  • Data science
  • Set (abstract data type)
  • Data quality
  • Quality (philosophy)
  • Completeness (order theory)
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Funding