Supporting a community-based domestic, family and sexual violence consortium to build evidence of service recommendations using de-identified linked administrative data.

ObjectiveTo support a South Australian community-based service consortium to test assumptions about individuals and families experiencing domestic, family and sexual violence (DFSV) accessing their services, to build evidence to support recommendations of a submission to a Royal Commission, using de-identified linked administrative data. MethodsThe Better Evidence Better Outcomes Linked Data platform (BEBOLD) was used to construct a base population of individuals who had accessed DFSV consortium services within a selected timeframe, and a comparison group of individuals who had accessed similar-funded services outside of the consortium in the same timeframe. De-identified system contact information for the two populations was then explored to understand differences or similarities in demographic and other characteristics, as well as system service usage pattens. De-identified linked datasets related to specialist homelessness services, child protection, hospital admissions and emergency department presentations were used. ResultsUsing de-identified system contact information in the BEBOLD platform, we were able to demonstrate that the two groups had both similarities and differences in their demographics, presenting needs, service-system usage patterns and relevant associated system outcomes (such as child removals by child protection). These findings were able to evidence some of the key recommendations that the consortium had written in their Royal Commission submission. This provided quantitative data to support their suggestions of key issues, and the changes required within the DFSV system landscape. We were also able to show similarities and differences between populations accessing services in metropolitan and regional/rural areas to explore whether geographical location had an impact on service system usage, outcomes and population characteristics. ConclusionUsing de-identified linked data, we assisted a community-based consortium supporting people experiencing DFSV to test their assumptions about key issues affecting their client population. This evidence was then used to support consortium recommendations to the Royal Commission on DFSV regarding how systems can better support people experiencing DFSV in South Australia.

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Publication Details

Journal
International Journal for Population Data Science
Published
2025-08-28
DOI
https://doi.org/10.23889/ijpds.v10i4.3213
Primary Topic
Community Health and Development
Type
article
Field-Weighted Citation Impact
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article

Supporting a community-based domestic, family and sexual violence consortium to build evidence of service recommendations using de-identified linked administrative data.

Jessica Dobrovic, Nadia Di Girolamo
International Journal for Population Data Science
Community Health and Development
article

Supporting a community-based domestic, family and sexual violence consortium to build evidence of service recommendations using de-identified linked administrative data.

Jessica Dobrovic, Nadia Di Girolamo
article en

Abstract

ObjectiveTo support a South Australian community-based service consortium to test assumptions about individuals and families experiencing domestic, family and sexual violence (DFSV) accessing their services, to build evidence to support recommendations of a submission to a Royal Commission, using de-identified linked administrative data. MethodsThe Better Evidence Better Outcomes Linked Data platform (BEBOLD) was used to construct a base population of individuals who had accessed DFSV consortium services within a selected timeframe, and a comparison group of individuals who had accessed similar-funded services outside of the consortium in the same timeframe. De-identified system contact information for the two populations was then explored to understand differences or similarities in demographic and other characteristics, as well as system service usage pattens. De-identified linked datasets related to specialist homelessness services, child protection, hospital admissions and emergency department presentations were used. ResultsUsing de-identified system contact information in the BEBOLD platform, we were able to demonstrate that the two groups had both similarities and differences in their demographics, presenting needs, service-system usage patterns and relevant associated system outcomes (such as child removals by child protection). These findings were able to evidence some of the key recommendations that the consortium had written in their Royal Commission submission. This provided quantitative data to support their suggestions of key issues, and the changes required within the DFSV system landscape. We were also able to show similarities and differences between populations accessing services in metropolitan and regional/rural areas to explore whether geographical location had an impact on service system usage, outcomes and population characteristics. ConclusionUsing de-identified linked data, we assisted a community-based consortium supporting people experiencing DFSV to test their assumptions about key issues affecting their client population. This evidence was then used to support consortium recommendations to the Royal Commission on DFSV regarding how systems can better support people experiencing DFSV in South Australia.

International Journal for Population Data ScienceVol. 10(4)
The University of Adelaide (AU)
Openalex Percentile: Top 64%
Community Health and Development
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