Visualization of Key Factor Relation in Clinical Pathway | Zendy

Takanori Yamashita | Zendy; Brendan Flanagan | Zendy; Yoshifumi Wakata | Zendy; Satoshi Hamai | Zendy; Yasuharu Nakashima | Zendy; Yukihide Iwamoto | Zendy; Naoki Nakashima | Zendy; Sachio Hirokawa | Zendy

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Visualization of Key Factor Relation in Clinical Pathway

Author(s) -

Takanori Yamashita,

Brendan Flanagan,

Yoshifumi Wakata,

Satoshi Hamai,

Yasuharu Nakashima,

Yukihide Iwamoto,

Naoki Nakashima,

Sachio Hirokawa

Publication year - 2015

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2015.08.139

Subject(s) - computer science , clinical pathway , relation (database) , visualization , variance (accounting) , factor (programming language) , key (lock) , process (computing) , tree (set theory) , medical record , path (computing) , data mining , data science , medicine , computer security , surgery , mathematical analysis , nursing , accounting , mathematics , business , programming language , operating system

The secondary use of medical data to improve medical care is gaining much attention. We have analyzed electronic clinical pathways for improving the medical process. The analysis of clinical pathways so far has used statistics analysis models, however as issue remains that the order, and multistory spatial and time relations of the each factor could not be analyzed. We constructed an Outcome tree system that shows the greatest significant relation for each factor. The Hip replacement arthroplasty clinical pathway was analyzed by the system, and the outcome variance of the clinical pathway was visualized. The results indicate the path of patient's who have a long hospitalization stay and extracted four critical indicators

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