Facilitating Clinical Outcomes Assessment through the Automated Identification of Quality Measures for Prostate Cancer Surgery | Zendy

Leonard W. D’Avolio | Zendy; Mark S. Litwin | Zendy; Scott O. Rogers | Zendy; Alex Bui | Zendy

Open Access

Facilitating Clinical Outcomes Assessment through the Automated Identification of Quality Measures for Prostate Cancer Surgery

Author(s) -

Leonard W. D’Avolio,

Mark S. Litwin,

Scott O. Rogers,

Alex Bui

Publication year - 2008

Publication title -

journal of the american medical informatics association

Language(s) - English

Resource type - Journals

eISSN - 1527-974X

pISSN - 1067-5027

DOI - 10.1197/jamia.m2649

Subject(s) - medicine , prostate cancer , categorization , margin (machine learning) , stage (stratigraphy) , quality assessment , medical physics , identification (biology) , cancer , pathology , artificial intelligence , computer science , paleontology , botany , machine learning , biology , external quality assessment

The College of American Pathologists (CAP) Category 1 quality measures, tumor stage, Gleason score, and surgical margin status, are used by physicians and cancer registrars to categorize patients into groups for clinical trials and treatment planning. This study was conducted to evaluate the effectiveness of an application designed to automatically extract these quality measures from the postoperative pathology reports of patients having undergone prostatectomies for treatment of prostate cancer.

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