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.
|Number of pages||10|
|Journal||Procedia Computer Science|
|Publication status||Published - Jan 1 2015|
|Event||19th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, KES 2015 - , Singapore|
Duration: Sep 7 2015 → Sep 9 2015
All Science Journal Classification (ASJC) codes
- Computer Science(all)