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

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

Resultado de la investigación: Chapter

10 Citas (Scopus)

Resumen

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.

Idioma originalEnglish (US)
Título de la publicación alojadaImproving Usability, Safety and Patient Outcomes with Health Information Technology
Subtítulo de la publicación alojadaFrom Research to Practice
EditoresAlex Mu-Hsing Kuo, Andre Kushniruk, Francis Lau, Elizabeth M. Borycki, Gerry Bliss, Helen Monkman, Abdul Vahabpour Roudsari, John A. Bartle-Clar, Karen L. Courtney
EditorialIOS Press
Páginas460-467
Número de páginas8
ISBN (versión digital)9781614999508
DOI
EstadoPublished - 2019

Serie de la publicación

NombreStudies in Health Technology and Informatics
Volumen257
ISSN (versión impresa)0926-9630
ISSN (versión digital)1879-8365

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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