A SNOMED analysis of three years' accessioned cases (40,124) of a surgical pathology department: implications for pathology-based demographic studies.
Pathology departments devote considerable energy toward indexing diagnoses. To date, there have been no detailed tabulations of the results of these efforts. We have thoroughly analyzed three years' surgical pathology reports (40,124) generated for 29,127 different patients from the University of Florida at Gainesville between Jan 1, 1990, and December 31, 1992. 64,921 SNOMED code entries (averaging 1.6 codes per specimen and 1.4 specimens per patient) were accounted for by 1,998 distinct SNOMED morphologies. A mere 21 entities accounted for 50% of the morphology code occurrences. 265 entities accounted for 90% of the morphology code occurrences, indicating that the diagnostic efforts of pathology departments are contained within a small fraction of the many thousands of morphologic entities available in the SNOMED nomenclature. One of the key problems in using SNOMED data collected from surgical pathology reports is the redundancy of lesions reported for single patients (i.e., a patient's disease may be coded on more than one specimen from the patient, leading to false conclusions regarding the incidence of disease in the population). In this study, redundant SNOMED data was removed by eliminating repeat morphology/topography pairs whenever they occur for a single patient. SNOMED data can be stratified on the basis of age and sex (data fields included on every surgical pathology report). This analysis represents the first published analysis of SNOMED data from a large pathology service, and demonstrates how SNOMED data can be compiled in a form that preserves patient privacy.
Berman
J J
JJ
Veterans Administration Medical Center, Baltimore, MD.
Moore
G W
GW
Donnelly
W H
WH
Massey
J K
JK
Craig
B
B
D000328:Adult; D002648:Child; D002984:Clinical Laboratory Information Systems; D016208:Databases, Factual; D003710:Demography; D003953:Diagnosis-Related Groups; D006801:Humans; D010340:Pathology, Surgical / Q000145:classification / Q000706:statistics & numerical data*; D013358:Subject Headings; D009626:Terminology as Topic