Rules based data quality assessment on claims database

Mary A. Gadde, Zhan Wang, Meredith Zozus, John B. Talburt, Melody L. Greer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Data quality problems in coded clinical and administrative data have persisted ever since diagnoses and procedures were first coded and used for healthcare billing. These data are used in clinical decision-making introducing a route for iatrogenesis. As we share data on regional Health Information Exchanges (HIEs) and include them in electronic health records the potential for harm may be increased. To study this problem we applied rules-based data quality checks that have been previously tested on Electronic Health Records (EHR) data on a limited set of aggregated claims data. Medicaid claims data was used exclusively. CMS has clear guidelines for claims submitted for Medicaid patients and penalties are incurred for erroneous claims, which should ensure a high quality data source, however reports of low and varying sensitivity, specificity, positive and negative predictive value of coded diagnoses are common. To identify data quality defects in claims data in a state All Payer Claims Dataset (APCD) we applied and evaluated a recently developed rules-based data quality assessment and monitoring system for Electronic Health Record (EHR) data to test effectiveness in claims data. These rules, that are feasible for 'All Payer Claims data' and Medicaid data are identified, applied and the Data Quality issue results are produced.

Original languageEnglish (US)
Title of host publicationTHE IMPORTANCE OF HEALTH INFORMATICS IN PUBLIC HEALTH DURING A PANDEMIC
EditorsJohn Mantas, Arie Hasman, Mowafa S. Househ, Parisis Gallos, Emmanouil Zoulias
PublisherIOS Press
Pages350-353
Number of pages4
ISBN (Electronic)9781643680927
DOIs
StatePublished - 2020

Publication series

NameStudies in Health Technology and Informatics
Volume272
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Keywords

  • Data quality
  • Healthcare Rules

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Fingerprint Dive into the research topics of 'Rules based data quality assessment on claims database'. Together they form a unique fingerprint.

Cite this