Rule-based data quality assessment and monitoring system in healthcare facilities

Zhan Wang, Serhan Dagtas, John Talburt, Ahmad Baghal, Meredith Zozus

Research output: Chapter in Book/Report/Conference proceedingChapter

13 Scopus citations


Measuring and managing data quality in healthcare has remained largely uncharted territory with few notable exceptions. A rules-based approach to data error identification was explored through compilation of over 6,000 data quality rules used with healthcare data. The rules were categorized based on topic and logic yielding twenty-two rule templates and associated knowledge tables used by the rule templates. This work provides a scalable framework with which data quality rules can be organized, shared among facilities and reused. The ten most frequent data quality problems based on the initial rules results are identified. While there is significant additional work to be done in this area, the exploration of the rule template and associated knowledge tables approach here shows rules-based data quality assessment and monitoring to be possible and scalable.

Original languageEnglish (US)
Title of host publicationImproving Usability, Safety and Patient Outcomes with Health Information Technology
Subtitle of host publicationFrom Research to Practice
EditorsAlex Mu-Hsing Kuo, Andre Kushniruk, Francis Lau, Elizabeth M. Borycki, Gerry Bliss, Helen Monkman, Abdul Vahabpour Roudsari, John A. Bartle-Clar, Karen L. Courtney
PublisherIOS Press
Number of pages8
ISBN (Electronic)9781614999508
StatePublished - 2019

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


  • Electronic health records
  • data quality
  • data quality assessment

ASJC Scopus subject areas

  • Health Information Management
  • Health Informatics
  • Biomedical Engineering


Dive into the research topics of 'Rule-based data quality assessment and monitoring system in healthcare facilities'. Together they form a unique fingerprint.

Cite this