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
Abstract
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.
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
- FWCI
- 58.35
- Percentile
- 100%
- References
- 66
Authors
20Topics & keywords
- Terminology
- Computer science
- Context (archaeology)
- Data science
- Set (abstract data type)
- Data quality
- Quality (philosophy)
- Completeness (order theory)