Ontological modeling of electronic health information exchange

被引:9
|
作者
McMurray, J. [1 ,3 ]
Zhu, L. [1 ]
McKillop, I. [1 ,2 ]
Chen, H. [1 ,2 ]
机构
[1] Univ Waterloo, Sch Publ Hlth & Hlth Syst, Waterloo, ON N2L 3G1, Canada
[2] Univ Waterloo, David R Cheriton Sch Comp Sci, Waterloo, ON N2L 3G1, Canada
[3] Wilfrid Laurier Univ, Sch Business & Econ Hlth Studies, Waterloo, ON N2L 3C5, Canada
关键词
Ontological model; Data quality; Health information exchange; Interoperability; Health system performance; BIOMEDICAL ONTOLOGIES; PERFORMANCE; DESIDERATA;
D O I
10.1016/j.jbi.2015.05.020
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Introduction: Investments of resources to purposively improve the movement of information between health system providers are currently made with imperfect information. No inventories of system -level electronic health information flows currently exist, nor do measures of inter-organizational electronic information exchange. Methods: Using Protege 4, an open-source OWL Web ontology language editor and knowledge-based framework, we formalized a model that decomposes inter-organizational electronic health information flow into derivative concepts such as diversity, breadth, volume, structure, standardization and connectivity. Results: The ontology was populated with data from a regional health system and the flows were measured. Individual instance's properties were inferred from their class associations as determined by their data and object property rules. It was also possible to visualize interoperability activity for regional analysis and planning purposes. A property called Impact was created from the total number of patients or clients that a health entity in the region served in a year, and the total number of health service providers or organizations with whom it exchanged information in support of clinical decision-making, diagnosis or treatment. Identifying providers with a high Impact but low Interoperability score could assist planners and policy-makers to optimize technology investments intended to electronically share patient information across the continuum of care. Finally, we demonstrated how linked ontologies were used to identify logical inconsistencies in self-reported data for the study. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:169 / 178
页数:10
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