Document Detail

An ontological knowledge framework for adaptive medical workflow.
MedLine Citation:
PMID:  18602872     Owner:  NLM     Status:  MEDLINE    
As emerging technologies, semantic Web and SOA (Service-Oriented Architecture) allow BPMS (Business Process Management System) to automate business processes that can be described as services, which in turn can be used to wrap existing enterprise applications. BPMS provides tools and methodologies to compose Web services that can be executed as business processes and monitored by BPM (Business Process Management) consoles. Ontologies are a formal declarative knowledge representation model. It provides a foundation upon which machine understandable knowledge can be obtained, and as a result, it makes machine intelligence possible. Healthcare systems can adopt these technologies to make them ubiquitous, adaptive, and intelligent, and then serve patients better. This paper presents an ontological knowledge framework that covers healthcare domains that a hospital encompasses-from the medical or administrative tasks, to hospital assets, medical insurances, patient records, drugs, and regulations. Therefore, our ontology makes our vision of personalized healthcare possible by capturing all necessary knowledge for a complex personalized healthcare scenario involving patient care, insurance policies, and drug prescriptions, and compliances. For example, our ontology facilitates a workflow management system to allow users, from physicians to administrative assistants, to manage, even create context-aware new medical workflows and execute them on-the-fly.
Jiangbo Dang; Amir Hedayati; Ken Hampel; Candemir Toklu
Publication Detail:
Type:  Journal Article     Date:  2008-06-20
Journal Detail:
Title:  Journal of biomedical informatics     Volume:  41     ISSN:  1532-0480     ISO Abbreviation:  J Biomed Inform     Publication Date:  2008 Oct 
Date Detail:
Created Date:  2008-10-17     Completed Date:  2008-12-18     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100970413     Medline TA:  J Biomed Inform     Country:  United States    
Other Details:
Languages:  eng     Pagination:  829-36     Citation Subset:  IM    
Knowledge Management, Siemens Corporate Research, 755 College Road East, Princeton, NJ 08540, USA.
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MeSH Terms
Artificial Intelligence
Computer Communication Networks
Database Management Systems*
Hospital Information Systems / organization & administration*
Information Storage and Retrieval / methods
Integrated Advanced Information Management Systems
Medical Informatics Computing*
Systems Integration
User-Computer Interface*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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