Title of article :
Creating personalised clinical pathways by semantic interoperability with electronic health records
Author/Authors :
Wang، نويسنده , , Hua-Qiong and Li، نويسنده , , Jing-Song and Zhang، نويسنده , , Yi-Fan and Suzuki، نويسنده , , Muneou and Araki، نويسنده , , Kenji، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Abstract :
Objective
is a growing realisation that clinical pathways (CPs) are vital for improving the treatment quality of healthcare organisations. However, treatment personalisation is one of the main challenges when implementing CPs, and the inadequate dynamic adaptability restricts the practicality of CPs. The purpose of this study is to improve the practicality of CPs using semantic interoperability between knowledge-based CPs and semantic electronic health records (EHRs).
s
protocol and resource description framework query language is used to gather patient information from semantic EHRs. The gathered patient information is entered into the CP ontology represented by web ontology language. Then, after reasoning over rules described by semantic web rule language in the Jena semantic framework, we adjust the standardised CPs to meet different patients’ practical needs.
s
or acute appendicitis is used as an example to illustrate how to achieve CP customisation based on the semantic interoperability between knowledge-based CPs and semantic EHRs. A personalised care plan is generated by comprehensively analysing the patientʹs personal allergy history and past medical history, which are stored in semantic EHRs. Additionally, by monitoring the patientʹs clinical information, an exception is recorded and handled during CP execution. According to execution results of the actual example, the solutions we present are shown to be technically feasible.
sion
tudy contributes towards improving the clinical personalised practicality of standardised CPs. In addition, this study establishes the foundation for future work on the research and development of an independent CP system.
Keywords :
Clinical pathway , Knowledge base , Electronic health record , semantic interoperability
Journal title :
Artificial Intelligence In Medicine
Journal title :
Artificial Intelligence In Medicine