Socio-economic disadvantage and resource distribution for mental health care: a model proposal and example application for Victoria, Australia

Author:

Meadows Graham123ORCID,Shawyer Frances4,Dawadi Shrinkhala4ORCID,Inder Brett5,Enticott Joanne46

Affiliation:

1. Southern Synergy, Department of Psychiatry, School of Clinical Sciences at Monash Health, and School of Primary and Allied Health Care, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia

2. Centre for Mental Health, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia

3. Monash Health, Melbourne, VIC, Australia

4. Southern Synergy, Department of Psychiatry, School of Clinical Sciences at Monash Health, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia

5. Department of Econometrics and Business Statistics, Faculty of Business & Economics, Monash University, Melbourne, VIC, Australia

6. Monash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia

Abstract

Objective: A spreadsheet-based model for supporting equitable mental health resource distribution in Australia was developed, based on the Australian Health Survey (AHS) psychological distress findings associated with area socio-economic disadvantage (SED). An illustrative application is presented. Method: Stratum-specific psychological-distress rates for area SED quintiles are applied to local government areas, catchment areas and local health networks (LHNs). A case study applies the model to Victoria, including examining recommendations in the Royal Commission into Victoria’s Mental Health Services (RCVMHS) 2019 interim report for increases to bed stock in two LHNs. Results: Need-adjusted demand estimates considered as a ratio of raw population proportions for catchments range between 0.6 to 1.4 in Victoria. Applying the formula to the Royal Commission recommendations suggests the proposed distribution of beds is a reasonable correction for these two LHNs and indicates next expansion priorities for more equitable distribution to other LHNs. Conclusions: The spreadsheet, adaptable for other states and territories, could complement National Mental Health Services Planning Framework outputs and assist in evaluation, for instance, determining potential supply shortages in the tele-mental-health response to COVID-19. We outline research directions including consideration of the moral bases of value judgements and identification of other variables including their use in parameterisation and calibration.

Publisher

SAGE Publications

Subject

Psychiatry and Mental health

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