Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/100595
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Type: Journal article
Title: Changes in monthly unemployment rates may predict changes in the number of psychiatric presentations to emergency services in South Australia
Author: Bidargaddi, N.
Bastiampillai, T.
Schrader, G.
Adams, R.
Piantadosi, C.
Strobel, J.
Tucker, G.
Allison, S.
Citation: BMC Emergency Medicine, 2015; 15(1):16-1-16-6
Publisher: BioMed Central
Issue Date: 2015
ISSN: 1471-227X
1471-227X
Statement of
Responsibility: 
Niranjan Bidargaddi, Tarun Bastiampillai, Geoffrey Schrader, Robert Adams, Cynthia Piantadosi, Jörg Strobel, Graeme Tucker, and Stephen Allison
Abstract: BACKGROUND To determine the extent to which variations in monthly Mental Health Emergency Department (MHED) presentations in South Australian Public Hospitals are associated with the Australian Bureau of Statistics (ABS) monthly unemployment rates. METHODS Times series modelling of relationships between monthly MHED presentations to South Australian Public Hospitals derived from the Integrated South Australian Activity Collection (ISAAC) data base and the ABS monthly unemployment rates in South Australia between January 2004–June 2011. RESULTS Time series modelling using monthly unemployment rates from ABS as a predictor variable explains 69 % of the variation in monthly MHED presentations across public hospitals in South Australia. Thirty-two percent of the variation in current month’s male MHED presentations can be predicted by using the 2 months’ prior male unemployment rate. Over 63 % of the variation in monthly female MHED presentations can be predicted by either male or female prior monthly unemployment rates. CONCLUSIONS The findings of this study highlight that even with the relatively favourable economic conditions, small shifts in monthly unemployment rates can predict variations in monthly MHED presentations, particularly for women. Monthly ABS unemployment rates may be a useful metric for predicting demand for emergency mental health services.
Keywords: Mental health; Times series modelling
Rights: © 2015 Bidargaddi et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http:// creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
RMID: 0030040433
DOI: 10.1186/s12873-015-0042-5
Appears in Collections:Medicine publications

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