• DocumentCode
    3706464
  • 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
  • fYear
    2015
  • fDate
    5/1/2015 12:00:00 AM
  • Firstpage
    337
  • Lastpage
    338
  • 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"
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2015 9th International Conference on
  • Print_ISBN
    978-1-63190-045-7
  • Electronic_ISBN
    2153-1641
  • Type

    conf

  • DOI
    10.4108/icst.pervasivehealth.2015.260251
  • Filename
    7349429