• DocumentCode
    2826554
  • Title

    Cluster Analysis of Care Assessment Data and Supporting for Care Planning

  • Author

    Eto, Kaoru ; Matsui, Tatsunori ; Mukuda, Minoru ; Kabasawa, Yasuo

  • Author_Institution
    Fac. of Eng., Nippon Inst. of Technol., Japan
  • fYear
    2009
  • fDate
    15-17 July 2009
  • Firstpage
    213
  • Lastpage
    214
  • Abstract
    Sharing know-how information for appropriately grasping care needs is an important factor to improve the quality of care service. Our know-how information sharing method highlights the differences between beginners and more skillful persons and brings them to the attention of the former. When a skillful person is given assessment data, first she roughly observes them based on a certain pattern that reflects her experience and then gradually notices the details. In this paper, we promote awareness by showing beginners this process. We classified assessment data using cluster analysis. With our results, which were verified by skillful persons, we verified that they basically agreed with the skillful person´s classification pattern. Therefore, a skillful person´s data observation process can be presented to beginners.
  • Keywords
    medical computing; pattern classification; pattern clustering; planning; quality of service; statistical analysis; assessment data classification; care assessment data; care planning support; care service quality; cluster analysis; know how information sharing methods; Appropriate technology; Cognition; Data analysis; Data engineering; Humans; Information analysis; Instruments; Process planning; Radar; Technology planning; Care Assessment Data; Cluster Analysis; Sharing know-how information; Supporting for Care Planning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Learning Technologies, 2009. ICALT 2009. Ninth IEEE International Conference on
  • Conference_Location
    Riga
  • Print_ISBN
    978-0-7695-3711-5
  • Electronic_ISBN
    978-0-7695-3711-5
  • Type

    conf

  • DOI
    10.1109/ICALT.2009.67
  • Filename
    5194205