Is headspace making a difference to young people’s lives?

Appendix B
A data driven approach to access, demand and capacity
Key messages
• A data driven approach, using available survey and geographic data, was used to
develop a model which maximised youth access to centre services.
• Centre allocation was prioritised based on the predicted risk of mental health disorder
at the small area level (SA1).
• This alternative model would be likely to result in a large number of additional centres.
This would include infill of existing SA4 and SA3 areas that already contain one
headspace centre.
• Pragmatic decisions are needed to achieve agreement on the smallest region size, in
terms of youth population, that would be viable to support creation of new centres.
• Prohibitive costs may be incurred if areas containing very small youth populations are
provided with full-service headspace centres, as this will result in a dramatic expansion
of centre locations. For example, areas with fewer than 1,000 young people living
within an agreed distance of a potential centre location may be serviced more costeffectively
under a different access model.
• Additional data relating to centre capacity, the smallest region size which can support
a headspace centre, and existence of competing and complementary services in
potential in-scope geographies, is required to establish the number and cost of
additional centres.
Rationale
One of the identified weaknesses of the current model of allocation is the assumption that a single
headspace centre within an SA3 in non-metropolitan areas or SA4 in metropolitan areas will provide
access to all young people within the area. Due to the large population size within some metropolitan
SA4 areas, and the vast geographic areas of some regional SA3s, this definition is unlikely to result
in equitable access to services for all young people. In addition, need for service is not evenly
distributed across Australia. While the current model acknowledges this through weights which are
applied based on socio-economic status of areas and remoteness, additional factors that impact on
likely service need were identified, including income, family type, Indigenous status, housing tenure,
language spoken at home and place of birth.
Instead of using administrative ASGS boundaries to define centre areas for centre allocation, the
proposed model of centre allocation described below makes use of a data-driven approach to the
issue of access. This model develops service catchment areas which correspond with the likely
travel distance to obtain services. Allocation is prioritised based on the predicted population of youth
mental health need within a small area. Finally, estimated capacity of centres is incorporated in the
model in an effort to maximise equitable access to mental health services.
Defining catchment areas
Mental health service catchment areas could be developed to provide an alternative to the ASGS
boundaries. Analysis of YMM data (see Figure B6, Figure B7 and Figure B8) indicates that
knowledge and use of headspace services decline substantially beyond 10 km travel distance,
with further decrements beyond 30 km. Therefore, catchment areas in metropolitan areas could be
designed with a maximum radius of 10 km. In non-metropolitan areas, service catchment areas with
a maximum radius of 30 km may reduce geographic barriers to access whilst balancing practical
limitations such as small population sizes within a single catchment area.
Allocation of additional centres
Centre allocation could be given priority based on anticipated population need. For example, the
small area estimates of youth at risk of mental health disorder within each catchment area could
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headspace Evaluation Final Report
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