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1.
Arch Pathol Lab Med ; 139(5): 587-93, 2015 May.
Article in English | MEDLINE | ID: mdl-25275812

ABSTRACT

CONTEXT: The College of American Pathologists has been producing cancer protocols since 1986 to aid pathologists in the diagnosis and reporting of cancer cases. Many pathologists use the included cancer case summaries as templates for dictation/data entry into the final pathology report. These summaries are now available in a computer-readable format with structured data elements for interoperability, packaged as "electronic cancer checklists." Most major vendors of anatomic pathology reporting software support this model. OBJECTIVES: To outline the development and advantages of structured electronic cancer reporting using the electronic cancer checklist model, and to describe its extension to cancer biomarkers and other aspects of cancer reporting. DATA SOURCES: Peer-reviewed literature and internal records of the College of American Pathologists. CONCLUSIONS: Accurate and usable cancer biomarker data reporting will increasingly depend on initial capture of this information as structured data. This process will support the standardization of data elements and biomarker terminology, enabling the meaningful use of these datasets by pathologists, clinicians, tumor registries, and patients.


Subject(s)
Biomarkers, Tumor/analysis , Electronic Health Records/standards , Neoplasms/pathology , Pathology, Clinical/standards , Checklist , Humans , Narration , Research Design , Societies, Medical , United States
2.
AMIA Annu Symp Proc ; : 1036, 2008 Nov 06.
Article in English | MEDLINE | ID: mdl-18998960

ABSTRACT

Structured data entry systems have been used to facilitate detailed categorical entries which may be subsequently used for computer-assisted decision support. While these highly organized entry systems may encourage providers to document clinical findings more precisely, the detailed nature of these entries may prove more time consuming than traditional data collection systems. We retrospectively examine results entered in our structured entry system in this study for pre-coordination opportunities as a potential enhancement to the system.


Subject(s)
Ambulatory Care , Cardiology , Medical History Taking/methods , Medical Records Systems, Computerized , Natural Language Processing , Pattern Recognition, Automated/methods , Terminology as Topic , Artificial Intelligence , Tennessee
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