The SNOMED DICOM microglossary: controlled terminology resource for data interchange in biomedical imaging.
This paper describes an authoritative, non-proprietary information resource that provides an efficient mechanism for embedding specialized clinical knowledge into the design of healthcare telecommunications systems. The resource marries two types of data interchange standards, a message/electronic-document standard and a terminology standard. In technical terms, it is part protocol and part database. Industry, academia, professional specialty societies, and the federal government participated in its development. The development of multi-specialty content has broadly engaged biomedical domain experts to an unprecedented degree in voluntary, non-proprietary message/document-standards development. The resource is the SNOMED DICOM Microglossary (SDM), a message-terminology (or document-content) mapping resource. The message/electronic-document standard is DICOM (Digital Imaging and Communications in Medicine). The terminology standard is SNOMED, (Systematized Nomenclature of Human and Veterinary Medicine). The SDM specifies the mapping of multi-specialty imaging terminology from SNOMED to DICOM data elements. DICOM provides semantic constraints and a framework for discourse that are lacking in SNOMED. Thus the message standard and the computer-based terminology both depend upon and complete each other. The combination is synergistic. By substitution of different templates of specialty terminology from the SDM, a generic message template, such as the DICOM Visible Light (Color Diagnostic) Image or the DICOM Structured Reporting specification can be reconfigured for diverse applications. Professional societies, with technical assistance from the College of American Pathologists, contribute and maintain their portions of the terminology, and can use SDM templates and term lists in clinical practice guidelines for the structure and content of computer-based patient records.
Bidgood
W D
WD
Center for Outcomes Measurement, Duke University Medical Center, Durham, NC, USA. bidgood@nlm.nih.gov
D001185:Artificial Intelligence; D003625:Data Collection; D006801:Humans; D008491:Medical Informatics Applications; D016347:Medical Records Systems, Computerized; D008511:Medicine; D012984:Software; D013038:Specialization; D019112:Teleradiology; D018875:Vocabulary, Controlled