You are here

The registry case finding engine: an automated tool to identify cancer cases from unstructured, free-text pathology reports and clinical notes.

TitleThe registry case finding engine: an automated tool to identify cancer cases from unstructured, free-text pathology reports and clinical notes.
Publication TypeJournal Article
Year of Publication2007
AuthorsHanauer, DA, Miela, G, Chinnaiyan, AM, Chang, AE, Blayney, DW
JournalJ Am Coll Surg
Volume205
Issue5
Pagination690-7
Date Published2007 Nov
ISSN1879-1190
KeywordsForms and Records Control, Humans, Medical Records Systems, Computerized, Neoplasms, Registries
Abstract

BACKGROUND: The American College of Surgeons mandates the maintenance of a cancer registry for hospitals seeking accreditation. At the University of Michigan Health System, more than 90% of all registry patients are identified by manual review, a method common to many institutions. We hypothesized that an automated computer system could accurately perform this time- and labor-intensive task. We created a tool to automatically scan free-text medical documents for terms relevant to cancer.STUDY DESIGN: We developed custom-made lists containing approximately 2,500 terms and phrases and 800 SNOMED codes. Text is processed by the Case Finding Engine (CaFE), and relevant terms are highlighted for review by a registrar and used to populate the registry database. We tested our system by comparing results from the CaFE to those by trained registrars who read through 2,200 pathology reports and marked relevant cases for the registry. The clinical documentation (eg, electronic chart notes) of an additional 476 patients was also reviewed by registrars and compared with the automated process by the CaFE.RESULTS: For pathology reports, the sensitivity for automated case identification was 100%, but specificity was 85.0%. For clinical documentation, sensitivity was 100% and specificity was 73.7%. Types of errors made by the CaFE were categorized to direct additional improvements. Use of the CaFE has resulted in a considerable increase in the number of cases added to the registry each month.CONCLUSIONS: The system has been well accepted by our registrars. CaFE can improve the accuracy and efficiency of tumor registry personnel and helps ensure that cancer cases are not overlooked.

DOI10.1016/j.jamcollsurg.2007.05.014
Alternate JournalJ. Am. Coll. Surg.
PubMed ID17964445
Grant List5 P30 CA46592 / CA / NCI NIH HHS / United States
People: 
David Hanauer
University of Michigan Rogel Cancer Center at North Campus Research Complex
1600 Huron Parkway, Bldg 100, Rm 1004 
Mailing Address: 2800 Plymouth Rd, NCRC 100-1004
Ann Arbor, MI 48109-2800 
Ph. (734) 764-8848 Fax. (734) 615-0507

Research reported in this publication was supported by the National Cancer Institutes of
Health under Award Number P30CA046592. The content is solely the responsibility
of the authors and does not necessarily represent the official views of the
National Institutes of Health.

Research reported in this publication was supported by the National Cancer Institutes of
Health under Award Number P30CA046592 by the use of the following Cancer Center
Shared Resource(s): Biostatistics, Analytics & Bioinformatics; Flow Cytometry;
Transgenic Animal Models; Tissue and Molecular Pathology; Structure & Drug
Screening; Cell & Tissue Imaging; Experimental Irradiation; Preclinical
Imaging & Computational Analysis; Health Communications; Immune Monitoring;
Pharmacokinetics)

Copyright © Cancer Center Informatics-2011 Regents of the University of Michigan