2014
DOI: 10.4258/hir.2014.20.4.295
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Clinical Data Element Ontology for Unified Indexing and Retrieval of Data Elements across Multiple Metadata Registries

Abstract: ObjectivesClassification of data elements (DEs), which is used in clinical documents is challenging, even in across ISO/IEC 11179 compliant clinical metadata registries (MDRs) due to no existence of reliable standard for identifying DEs. We suggest the Clinical Data Element Ontology (CDEO) for unified indexing and retrieval of DEs across MDRs.MethodsThe CDEO was developed through harmonization of existing clinical document models and empirical analysis of MDRs. For specific classification as using data element… Show more

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Cited by 6 publications
(3 citation statements)
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“…Many of these challenges are common to meta-analysis and other data pooling efforts. 20, 21 Some of the key lessons during this process included: anticipating and planning common studies across sites upfront; using common protocols and data collection instruments with standardized variables across sites when possible (e.g., Clinical Data Interchange Standards Consortium 20 ); employing data management best practices at all sites to minimize errors in data submitted for harmonization; and, allowing time and resources during the lifetime of the Program for talent exchange and targeted resource support to foster high quality outputs and collaboration between groups.…”
Section: High Level Collaboration: Development Of a Program Wide Harmmentioning
confidence: 99%
“…Many of these challenges are common to meta-analysis and other data pooling efforts. 20, 21 Some of the key lessons during this process included: anticipating and planning common studies across sites upfront; using common protocols and data collection instruments with standardized variables across sites when possible (e.g., Clinical Data Interchange Standards Consortium 20 ); employing data management best practices at all sites to minimize errors in data submitted for harmonization; and, allowing time and resources during the lifetime of the Program for talent exchange and targeted resource support to foster high quality outputs and collaboration between groups.…”
Section: High Level Collaboration: Development Of a Program Wide Harmmentioning
confidence: 99%
“…Fortunately, the information was often machine-actionable, and therefore, automatic processing, especially matching and mapping, was possible. However, our literature review revealed known hurdles even before the metadata could be processed: heterogeneous metadata interfaces caused a siloization [ 72 ], which resulted in the impediment of metadata acquisition and reuse. If the information could be accessed, the processing also had problems: automatic matching from a broader to a more detailed level was nearly impossible [ 20 ], and if the matching results were promising, an automated mapping without human interaction was complicated or rather infeasible [ 16 , 24 ].…”
Section: Resultsmentioning
confidence: 99%
“…For this purpose ISO/IEC 11179 provides a classification scheme (CS) structure for the conceptual classification and identification of data elements. Thus, when constructing an MDR or registering designed CDEs into an MDR, it is also necessary to select or design the contents of the CS using controlled vocabularies [20, 21]. However, most MDRs do not fully utilize or register a CS, and some MDRs support only two or three concept items in each CS for classifying their own metadata.…”
Section: Introductionmentioning
confidence: 99%