Varghese, Julian, Holz, Christian, Neuhaus, Phillip et al. (14 more authors) (2017) Key Data Elements in Myeloid Leukemia. In: Exploring Complexity in Health: An Interdisciplinary Systems Approach. Studies in Health Technology and Informatics . IOS Press , pp. 282-286.
Abstract
Data standards consisting of key data elements for clinical routine and trial documentation harmonize documentation within and across different health care institutions making documentation more efficient and improving scientific data analysis. This work focusses on the field of myeloid leukemia (ML), where a semantic core of common data elements (CDEs) in routine and trial documentation is established by automatic UMLS-based form analysis of existing documentation models. These CDEs (n=227) were initially reviewed and commented by leukemia experts before they were systematically surveyed by an international voting process through seven hematologists of four countries. The total agreement score was 86%. 116 elements (51%) of these share an agreement score of 100%. This work generated CDEs with language-independent semantic codes and international clinical expert review to build a first approach towards an international data standard for ML. A first version of the CDE list is implemented in the data standard Operational Data Model and additional other data formats for reuse in different medical information systems.
Metadata
Item Type: | Book Section |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Publisher Copyright: © 2016 European Federation for Medical Informatics (EFMI) and IOS Press. |
Keywords: | AML,CML,Common data elements,Data standards,MDS,UMLS |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Health Sciences (York) |
Depositing User: | Pure (York) |
Date Deposited: | 09 Sep 2016 09:56 |
Last Modified: | 16 Oct 2024 10:49 |
Published Version: | https://doi.org/10.3233/978-1-61499-678-1-282 |
Status: | Published |
Publisher: | IOS Press |
Series Name: | Studies in Health Technology and Informatics |
Identification Number: | 10.3233/978-1-61499-678-1-282 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:104527 |