Validation of Case Finding Algorithms for Hepatocellular Cancer From Administrative Data and Electronic Health Records Using Natural Language Processing.

Journal: Medical care

PMID: 23929403

Abstract

BACKGROUND: Accurate identification of hepatocellular cancer (HCC) cases from automated data is needed for efficient and valid quality improvement initiatives and research. We validated HCC International Classification of Diseases, 9th Revision (ICD-9) codes, and evaluated whether natural language processing by the Automated Retrieval Console (ARC) for document classification improves HCC identification.

Authors

Yvonne Sada

*Michael E. DeBakey Veterans Administration Medical Center and Baylor College of Medicine †Health Services Research and Development Section Departments of ‡Oncology §Gastroenterology, Baylor College of Medicine, Houston, TX.
Jason Hou

Division of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, Texas, USA.
Peter Richardson
Hashem El-Serag
Jessica Davila

Keywords

Aged Algorithms Databases, Factual Electronic Health Records Female Humans Information Storage and Retrieval International Classification of Diseases Liver Neoplasms Male Middle Aged Natural Language Processing Sensitivity and Specificity Socioeconomic Factors United States United States Department of Veterans Affairs

External Resources

View on PubMed Access via DOI PubMed (23929403)

Validation of Case Finding Algorithms for Hepatocellular Cancer From Administrative Data and Electronic Health Records Using Natural Language Processing.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals