A new bottom-up method for the standard analysis and comparison of workforce capacity in mental healthcare planning: Demonstration study in the Australian Capital Territory

Mary Anne Furst, Jose A. Salinas-Perez, Mencia R. Gutiérrez-Colosia, Luis Salvador-Carulla

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
48 Downloads (Pure)

Abstract

The aims of this study are to evaluate and describe mental health workforce and capacity, and to describe the relationship between workforce capacity and patterns of care in local areas. We conducted a comparative demonstration study of the applicability of an internationally validated standardised service classification instrument—the Description and Evaluation of Services and Directories—DESDE-LTC) using the emerging mental health ecosystems research (MHESR) approach. Using DESDE-LTC as the framework, and drawing from international occupation classifications, the workforce was classified according to characteristics including the type of care provided and professional background. Our reference area was the Australian Capital Territory, which we compared with two other urban districts in Australia (Sydney and South East Sydney) and three benchmark international health districts (Helsinki-Uusima (Finland), Verona (Italy) and Gipuzkoa (Spain)). We also compared our data with national level data where available. The Australian and Finnish regions had a larger and more highly skilled workforce than the southern European regions. The pattern of workforce availability and profile varied, even within the same country, at the local level. We found significant differences between regional rates of identified rates of psychiatrists and psychologists, and national averages. Using a standardised classification instrument at the local level, and our occupational groupings, we were able to assess the available workforce and provide information relevant to planners about the actual capacity of the system. Data obtained at local level is critical to providing planners with reliable data to inform their decision making.

Original languageEnglish
Article numbere0255350
Pages (from-to)1-22
Number of pages22
JournalPLoS One
Volume16
Issue number7 July
DOIs
Publication statusPublished - Jul 2021
Externally publishedYes

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