Clinical Data Element Ontology for Unified Indexing and Retrieval of Data Elements across Multiple Metadata Registries / 대한의료정보학회지
Healthcare Informatics Research
;
: 295-303, 2014.
Article
in English
| WPRIM
| ID: wpr-222042
ABSTRACT
OBJECTIVES:
Classification 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.METHODS:
The CDEO was developed through harmonization of existing clinical document models and empirical analysis of MDRs. For specific classification as using data element concept (DEC), The Simple Knowledge Organization System was chosen to represent and organize the DECs. Six basic requirements also were set that the CDEO must meet, including indexing target to be a DEC, organizing DECs using their semantic relationships. For evaluation of the CDEO, three indexers mapped 400 DECs to more than 1 CDEO term in order to determine whether the CDEO produces a consistent index to a given DEC. The level of agreement among the indexers was determined by calculating the intraclass correlation coefficient (ICC).RESULTS:
We developed CDEO with 578 concepts. Through two application use-case scenarios, usability of the CDEO is evaluated and it fully met all of the considered requirements. The ICC among the three indexers was estimated to be 0.59 (95% confidence interval, 0.52-0.66).CONCLUSIONS:
The CDEO organizes DECs originating from different MDRs into a single unified conceptual structure. It enables highly selective search and retrieval of relevant DEs from multiple MDRs for clinical documentation and clinical research data aggregation.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Semantics
/
Registries
/
Data Collection
/
Information Storage and Retrieval
/
Classification
/
Information Dissemination
/
Abstracting and Indexing
Language:
English
Journal:
Healthcare Informatics Research
Year:
2014
Type:
Article
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