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Statistical approaches for identifying heavy users of inpatient mental health services.
- Source :
- Journal of Mental Health; Oct2016, Vol. 25 Issue 5, p455-460, 6p, 2 Charts, 1 Graph
- Publication Year :
- 2016
-
Abstract
- Background: A lack of consensus exists concerning how to identify "heavy users" of inpatient mental health services. Aim: To identify a statistical approach that captures, in a clinically meaningful way, "heavy" users of inpatient services using number of admissions and total time spent in hospital. Methods: "Simple" statistical methods (e.g. top 2%) and data driven methods (e.g. the Poisson mixture distribution) were applied to admissions made to adult acute services of a London mental health trust. Results: The Poisson mixture distribution distinguished "frequent users" of inpatient services, defined as having 4 + admissions in the study period. It also distinguished "high users" of inpatient services, defined as having 52 + occupied bed days. Together "frequent" and "high" users were classified as "heavy users". Conclusions: Data driven criteria such as the Poisson mixture distribution can identify "heavy" users of inpatient services. The needs of this group require particular attention. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09638237
- Volume :
- 25
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Journal of Mental Health
- Publication Type :
- Academic Journal
- Accession number :
- 119616087
- Full Text :
- https://doi.org/10.1080/09638237.2016.1207221