Zihao Yan1, Ronilda Lacson1, Ivan Ip2, Vladimir Valtchinov1, Ali Raja3, David Osterbur4, Ramin Khorasani5. 1. Center for Evidence-Based Imaging, Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA. 2. Center for Evidence-Based Imaging, Brigham and Women's Hospital, Boston, MA; Department of Medicine, Brigham and Women's Hospital, MA; Harvard Medical School, Boston, MA. 3. Center for Evidence-Based Imaging, Brigham and Women's Hospital, Boston, MA; Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA; Harvard Medical School, Boston, MA. 4. Countway Medical Library, Boston, MA; Harvard Medical School, Boston, MA. 5. Center for Evidence-Based Imaging, Brigham and Women's Hospital, Boston, MA; Department of Radiology, Brigham and Women's Hospital, MA; Harvard Medical School, Boston, MA.
Abstract
Purpose: Clinical decision support tools provide recommendations based on decision rules. A fundamental challenge regarding decision rule-sharing involves inadequate expression using standard terminology. We aimed to evaluate the coverage of three standard terminologies for mapping imaging-related decision rules. Methods: 50 decision rules, randomly selected from an existing library, were mapped to Systemized Nomenclature of Medicine (SNOMED CT), Radiology Lexicon (RadLex) and International Classification of Disease (ICD-10-CM). Decision rule attributes and values were mapped to unique concepts, obtaining the best possible coverage with the fewest concepts. Manual and automated mapping using Clinical Text Analysis and Knowledge Extraction System (cTAKES) were performed. Results: Using manual mapping, SNOMED CT provided the greatest concept coverage (83%), compared to RadLex (36%) and ICD-10-CM (8%) (p<0.0001). Combined mapping had 86% concept coverage. Automated mapping achieved 85% mapping coverage vs. 94% with manual mapping (p<0.001). Conclusion: Although some gaps remain, standard terminologies provide ample coverage for mapping imaging- related evidence.
Purpose: Clinical decision support tools provide recommendations based on decision rules. A fundamental challenge regarding decision rule-sharing involves inadequate expression using standard terminology. We aimed to evaluate the coverage of three standard terminologies for mapping imaging-related decision rules. Methods: 50 decision rules, randomly selected from an existing library, were mapped to Systemized Nomenclature of Medicine (SNOMED CT), Radiology Lexicon (RadLex) and International Classification of Disease (ICD-10-CM). Decision rule attributes and values were mapped to unique concepts, obtaining the best possible coverage with the fewest concepts. Manual and automated mapping using Clinical Text Analysis and Knowledge Extraction System (cTAKES) were performed. Results: Using manual mapping, SNOMED CT provided the greatest concept coverage (83%), compared to RadLex (36%) and ICD-10-CM (8%) (p<0.0001). Combined mapping had 86% concept coverage. Automated mapping achieved 85% mapping coverage vs. 94% with manual mapping (p<0.001). Conclusion: Although some gaps remain, standard terminologies provide ample coverage for mapping imaging- related evidence.
Authors: Daniel I Rosenthal; Jeffrey B Weilburg; Thomas Schultz; Janet C Miller; Victoria Nixon; Keith J Dreyer; James H Thrall Journal: J Am Coll Radiol Date: 2006-10 Impact factor: 5.532
Authors: Ivan K Ip; Louise Schneider; Steven Seltzer; Allen Smith; Jessica Dudley; Andrew Menard; Ramin Khorasani Journal: Am J Med Date: 2013-06-17 Impact factor: 4.965
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