title: Changes in monthly unemployment rates may predict changes in the number of psychiatric presentations to emergency services in South Australia.
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.
authors.affiliation: Mental Health Informatics Unit, Country Health SA, Flinders University, School of Medicine, Lvl 1, 22 King William Street, Adelaide, SA, 5000, Australia. niranjan.bidargaddi@flinders.edu.au.
authors.forename: Niranjan
authors.initials: N
authors.lastname: Bidargaddi
authors.affiliation: Flinders University, School of Medicine-Discipline of Psychiatry, Adelaide, Australia. Tarun.Bastiampillai@sa.gov.au.
authors.forename: Tarun
authors.initials: T
authors.lastname: Bastiampillai
authors.affiliation: Mental Health Informatics Unit, Country Health SA, Adelaide, SA, 5000, Australia. geoffrey.schrader@adelaide.edu.au.
authors.forename: Geoffrey
authors.initials: G
authors.lastname: Schrader
authors.affiliation: The Queen Elizabeth Hospital, University of Adelaide, School of Medicine-Discipline of Medicine, Adelaide, SA, Australia. robert.adams@adelaide.edu.au.
authors.forename: Robert
authors.initials: R
authors.lastname: Adams
authors.affiliation: The Queen Elizabeth Hospital, University of Adelaide, School of Medicine-Discipline of Medicine, Adelaide, SA, Australia. cynthia.piantadosi@health.sa.gov.au.
authors.forename: Cynthia
authors.initials: C
authors.lastname: Piantadosi
authors.affiliation: Mental Health Observatory Research Unit, Country Health SA, Adelaide, SA, 5000, Australia. Jorg.Strobel@sa.gov.au.
authors.forename: Jörg
authors.initials: J
authors.lastname: Strobel
authors.affiliation: Epidemiology Branch, SA Department for Health and Ageing, School of Medicine-University of Adelaide, Adelaide, Australia. Graeme.Tucker@sa.gov.au.
authors.forename: Graeme
authors.initials: G
authors.lastname: Tucker
authors.affiliation: Flinders University, School of Medicine-Discipline of Psychiatry, Adelaide, Australia. stephen.allison@flinders.edu.au.
authors.forename: Stephen
authors.initials: S
authors.lastname: Allison
mesh_terms: D004637:Emergency Services, Psychiatric / Q000706:statistics & numerical data* / Q000639:trends; D005260:Female; D006779:Hospitals, Public / Q000706:statistics & numerical data / Q000639:trends; D006801:Humans; D008297:Male; D001523:Mental Disorders / Q000453:epidemiology / Q000209:etiology*; D015233:Models, Statistical; D012307:Risk Factors; D012621:Seasons; D012737:Sex Factors; D013021:South Australia / Q000453:epidemiology; D014478:Unemployment / Q000706:statistics & numerical data / Q000639:trends*