Outcome management and morphologic variance analysis using psychomsTM for patient care in psychiatric hospitals

In 2003, the Japanese government set an approximate goal of 72,000 social hospitalization in-patients being discharged in 10 years from psychiatric hospitals to the community. To meet this challenge, the clinical pathway (CP) is a useful model for managing the team's progress in providing health care services. High quality discharge planning for patients requires continuous refinement of CP including the collection and analysis of variance data, i.e., information not listed in the CP model. The purpose of this study is to analyze variance data gathered using Psychoms
^TM
to find unidentified issues with keyword sorting (keyword variance analyses system) and text-mining (text mining variance analyses system). Using morphological analysis to detect word occurrences in variance data, it may be possible to identify problems needing solution by developing automatic rankings to analysis outcomes. To achieve this, however, specialized experience is required for variance analysis. Also, there must be high congruence between the results of text mining variance analyses and keyword variance analyses systems.