• DocumentCode
    2691578
  • Title

    Bridging encounter forms and electronic medical record databases: Annotation, mapping, and integration

  • Author

    An, Yuan ; Khare, Ritu ; Hu, Xiaohua ; Song, Il-Yeol

  • fYear
    2012
  • fDate
    4-7 Oct. 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Forms are a major source of input for getting data into the underlying medical databases of electronic health/medical record (EHR/EMR) systems. Standardizing encounter forms and integrating data collected from different forms into a single database would greatly reduce heterogeneity. In this paper, we describe a framework, the fEHR-plus system, that annotates, maps, and integrates user-specified encounter forms into a single database. The development of the framework incorporates machine learning, standard medical terminology, and the principles of database design. We conduct an empirical study with 52 forms collected from 6 medical institutions for evaluating the performance of the fEHR-plus system. The overall results show that the system is promising towards improving interoperability among electronic health record systems.
  • Keywords
    biomedical engineering; data integration; document handling; information storage; knowledge management; learning (artificial intelligence); medical information systems; data annotation; data integration; data mapping; database design; electronic health records; electronic medical record databases; encounter forms; fEHR-plus system; machine learning; medical databases; medical terminology; Corporate acquisitions; Databases; Merging; Optimization; Pragmatics; Semantics; Terminology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2012 IEEE International Conference on
  • Conference_Location
    Philadelphia, PA
  • Print_ISBN
    978-1-4673-2559-2
  • Electronic_ISBN
    978-1-4673-2558-5
  • Type

    conf

  • DOI
    10.1109/BIBM.2012.6392709
  • Filename
    6392709