Title :
Modeling evidence-based medicine applications with provenance data in pathways
Author :
Ustun Yildiz;Khalid Belhajjame;Daniela Grigori
Author_Institution :
Agency of Health Informatics, Mithatpasa Caddesi No: 3, Sihhiye/Ankara 06100, Turkey
fDate :
5/1/2015 12:00:00 AM
Abstract :
Clinical Pathway Management Systems have emerged as promising methods and tools in clinical care automation as analogous to workflow management tools in business process management. Nevertheless, they are not fully appropriate yet to model and express the complex and non-deterministic clinical phenomena in which clinicians are interested. In this paper, our overall goal is to contribute to the automation of clinical pathways with the use data provenance methods and tools. In contrast to commonly developed methods for clinical pathways, we claim that the specification and execution of pathways should include not only a description of structural aspects, but also a description of what a clinician needs to know about the execution when the outcome is produced. Consequently, this requires clinicians to communicate their knowledge, ideas and requirements on data provenance at the modeling phase or execution of a clinical pathway. With this recognition of clinician participation in development, we will develop a new conceptual modeling process for clinical pathways in which clinicians can express their data provenance expectations.
Keywords :
"Medical diagnostic imaging","Automation","Genetics","Drugs","Data models","Guidelines"
Conference_Titel :
Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2015 9th International Conference on
Print_ISBN :
978-1-63190-045-7
Electronic_ISBN :
2153-1641
DOI :
10.4108/icst.pervasivehealth.2015.260251