Title :
Temporal Data Mining for Nursing Schedule Management
Author :
Tsumoto, Shusaku ; Hirano, Shoji ; Iwata, Haruko
Author_Institution :
Dept. of Med. Inf., Shimane Univ., Izumo, Japan
Abstract :
Since hospital data include temporal trends of clinical symptoms and medical services, we can discover not only knowledge about temporal evolution of disease, but also one about medical practice from hospital information system. This paper proposes temporal data mining process and applied the method to capture temporal knowledge about nursing practice. The results show that the reuse of stored data will give a powerful tool for management of nursing schedule and lead to improvement of hospital services.
Keywords :
data mining; diseases; medical information systems; patient care; scheduling; hospital data; hospital information system; knowledge discovery; medical practices; nursing practice; nursing schedule management; temporal clinical symptom trends; temporal data mining process; temporal disease evolution; temporal knowledge; temporal medical service trends; Data mining; Diseases; Hospitals; Information systems; Lungs; Pain; Clinical pathway Clustering; Hospital management; Multidimensional scaling; Temporal Data mining;
Conference_Titel :
Innovations in Bio-Inspired Computing and Applications (IBICA), 2012 Third International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4673-2838-8
DOI :
10.1109/IBICA.2012.64
