Literature DB >> 18258674

A method to map heterogeneity between near but non-equivalent semantic attributes in multiple health data registries.

Nadine Schuurman1, Agnieszka Leszczynski.   

Abstract

Health registries from multiple jurisdictions often include terms that are assumed to be semantically equivalent (e.g. fetal death and stillbirth). Closer examination reveals that such attributes have near--but non-equivalent--semantics. Thus their degree of semantic heterogeneity is an important indicator of uncertainty associated with data integration between registries. We build an OWL-encoded ontology which formalizes the relationships between similar perinatal concepts found in different databases. We also introduce the concept of ontology-based metadata as a means of contextualizing such terms and linking context to the attribute data. This extended metadata are exported as XML from the health registries, and it--along with the OWL ontology--is interfaced via a web-based GUI accessible to health researchers. The GUI mapping serves as the basis for making ad hoc comparison and integration decisions. Uncertainty is addressed by precisely mapping semantic heterogeneity between fields.

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Year:  2008        PMID: 18258674     DOI: 10.1177/1460458207086333

Source DB:  PubMed          Journal:  Health Informatics J        ISSN: 1460-4582            Impact factor:   2.681


  3 in total

1.  SMASH: A Data-driven Informatics Method to Assist Experts in Characterizing Semantic Heterogeneity among Data Elements.

Authors:  William Brown; Chunhua Weng; David K Vawdrey; Alex Carballo-Diéguez; Suzanne Bakken
Journal:  AMIA Annu Symp Proc       Date:  2017-02-10

2.  Conducting research using the electronic health record across multi-hospital systems: semantic harmonization implications for administrators.

Authors:  Kathryn H Bowles; Sheryl Potashnik; Sarah J Ratcliffe; Melissa Rosenberg; Nai-Wei Shih; Maxim Topaz; John H Holmes; Mary D Naylor
Journal:  J Nurs Adm       Date:  2013-06       Impact factor: 1.737

Review 3.  Common data elements of breast cancer for research databases: A systematic review.

Authors:  Esmat Mirbagheri; Maryam Ahmadi; Soraya Salmanian
Journal:  J Family Med Prim Care       Date:  2020-03-26
  3 in total

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