Predicting the length of hospital stay of psychiatry patients using signal detection analysis

Fase Badriah, Takeru Abe, Yoshihiro Nabeshima, Kouji Ikeda, Kenji Kuroda, Akihito Hagihara*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

In Japan, the length of hospital stay (LOS) at psychiatric institutions often exceeds a year, and factors related to such stays have been identified. However, we do not know how multiple patient, hospital, and physician factors interact to determine LOS. Patient data were collected from a psychiatric hospital in Osaka, Japan. We developed subgroups, which were determined by interactions related to LOS using signal detection theory. In acute or emergency wards, five factors related to LOS were identified, and subjects were categorized into six subgroups. The indices obtained by the five factors ranged 2.49-3.47 for odds ratio, 0.47-0.84 for sensitivity, 0.40-0.76 for specificity, and 0.52-0.71 for positive predictive value. In general wards, five factors related to LOS were identified, and subjects were categorized into six subgroups. The indices obtained by the five factors ranged 3.02-5.36 for odds ratio, 0.58-0.86 for sensitivity, 0.37-0.68 for specificity, and 0.85-0.92 for positive predictive value. Psychiatrists who have been practicing longer in acute or emergency wards appear to have significantly longer stay of patients, and older or more severe patients tend to be in need of longer inpatient care. Our results provide findings that may be helpful in decreasing LOS at psychiatric hospitals.

Original languageEnglish
Pages (from-to)1211-1218
Number of pages8
JournalPsychiatry Research
Volume210
Issue number3
DOIs
Publication statusPublished - 2013 Dec 30

Keywords

  • Outcome
  • Prediction
  • Signal detection analysis

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Biological Psychiatry

Fingerprint

Dive into the research topics of 'Predicting the length of hospital stay of psychiatry patients using signal detection analysis'. Together they form a unique fingerprint.

Cite this