Development of query strategies to identify a histologic lymphoma subtype in a large linked database system

Cancer Informatics

Volumn 3, Issue , 2007, Pages 149-158

  Graiser, Michael ^a   Moore, Susan G ^a   Victor, Rochelle ^a   Hilliard, Ashley ^a   Hill, Leroy ^a   Keehan, Michael S ^b   Flowers, Christopher R ^a,c,d  

^a EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b NuTec Health Systems   (United States)

^c Oncology Data Center

^d EMORY UNIVERSITY   (United States)

Author keywords

Cancer epidemiology; Cancer outcomes research; Cancer registry; Large linked database

Indexed keywords

ARTICLE; CANCER PATIENT; CANCER REGISTRY; CANCER RESEARCH; COMPUTER SYSTEM; CONTROLLED STUDY; ELECTRONIC MEDICAL RECORD; FOLLICULAR LYMPHOMA; HISTOPATHOLOGY; HUMAN; MEDICAL INFORMATION SYSTEM; PATIENT IDENTIFICATION; PHARMACY; SENSITIVITY AND SPECIFICITY; DATA BASE; HISTOLOGY; ICD-9; INTERNATIONAL CLASSIFICATION OF DISEASES FOR ONCOLOGY; LARGE LINKED DATABASE;

EID: 49649091963     PISSN: 11769351     EISSN: 11769351     Source Type: Journal    
DOI: 10.1177/117693510700300017     Document Type: Article

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