Qualitative assessment of annotations using SNOMED CT
نویسندگان
چکیده
Motivation: SNOMED CT provides about 300,000 codes with fine-grained definitions to support interoperability of health data. However, even experienced human coders tend to disagree about which codes to choose for expressing clinical content. Results: 20 short clinical text fragments were independently annotated with SNOMED CT codes by two terminology experts. We analysed each disagreement instance and classified disagreements into eight categories, for which representative examples are presented. Conclusion: For each disagreement category measures to improve the terminology and to support guidelines for human and machine annotation are proposed and discussed.
منابع مشابه
بررسی تطبیقی سیر تکامل و ساختار سیستم های نامگذاری نظام یافته پزشکی SNOMED در کشورهای آمریکا ، انگلستان و استرالیا 86-85
Background and Aim: Systematized Nomenclature of Medicine systems are the important supportive for electronic health record in registration and retrieval of data. Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) is the most comprehensive language and then the consistency of exchanged data across health care providers and finally the high effectiveness of health care. Material...
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