Using Newly Linked Data to Assess Equity of Out-Of-Pocket Healthcare Costs in Australia
Introduction Describing out-of-pocket (OOP) healthcare costs in relation to ability to pay requires multiple linked data sources not previously available. Current estimates of the progressivity of OOP healthcare costs in Australia are based on self-report surveys. Using newly linked Census to admini...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Swansea University
2020-12-01
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| Series: | International Journal of Population Data Science |
| Online Access: | https://ijpds.org/article/view/1594 |
| _version_ | 1797430794435690496 |
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| author | Hsei Di Law Nicholas Biddle Emily Lancsar Jennifer Welsh Danielle Butler Rosemary J Korda |
| author_facet | Hsei Di Law Nicholas Biddle Emily Lancsar Jennifer Welsh Danielle Butler Rosemary J Korda |
| author_sort | Hsei Di Law |
| collection | DOAJ |
| description | Introduction
Describing out-of-pocket (OOP) healthcare costs in relation to ability to pay requires multiple linked data sources not previously available. Current estimates of the progressivity of OOP healthcare costs in Australia are based on self-report surveys. Using newly linked Census to administrative income and medical claims data, we aimed to quantify, for the first time, the progressivity of OOP costs for government-subsidised out-of-hospital healthcare in Australia.
Objectives and Approach
We used Australian Census 2011 linked to Personal Income Tax (PIT), Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) data compiled through the Multi-Agency Data Integration Project (MADIP). Personal disposable income was estimated using a combination of PIT data and Census self-reported income, and aggregated across the household to estimate equivalised household income. We estimated annual MBS (out-of-hospital only) and PBS OOP costs as a proportion of equivalised household income, and assessed progressivity by reporting this for each income decile and computing a Kakwani Index.
Results
We will present findings on progressivity overall, and separately by age, sex and location (incomplete at time of abstract submission).
Conclusion / Implications
Our study will present one measure regarding the equity of healthcare costs, and help to identify vulnerable or at-risk groups. These findings may inform policy changes on equity in the financing of healthcare. Newly linked data from the MADIP can be used to relate healthcare costs to ability to pay. |
| first_indexed | 2024-03-09T09:33:39Z |
| format | Article |
| id | doaj.art-3c32b9fd1a3d409599c78751cacc9740 |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T09:33:39Z |
| publishDate | 2020-12-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-3c32b9fd1a3d409599c78751cacc97402023-12-02T02:54:52ZengSwansea UniversityInternational Journal of Population Data Science2399-49082020-12-015510.23889/ijpds.v5i5.1594Using Newly Linked Data to Assess Equity of Out-Of-Pocket Healthcare Costs in AustraliaHsei Di Law0Nicholas Biddle1Emily Lancsar2Jennifer Welsh3Danielle Butler4Rosemary J Korda5Australian National UniversityAustralian National UniversityAustralian National UniversityAustralian National UniversityAustralian National UniversityAustralian National UniversityIntroduction Describing out-of-pocket (OOP) healthcare costs in relation to ability to pay requires multiple linked data sources not previously available. Current estimates of the progressivity of OOP healthcare costs in Australia are based on self-report surveys. Using newly linked Census to administrative income and medical claims data, we aimed to quantify, for the first time, the progressivity of OOP costs for government-subsidised out-of-hospital healthcare in Australia. Objectives and Approach We used Australian Census 2011 linked to Personal Income Tax (PIT), Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) data compiled through the Multi-Agency Data Integration Project (MADIP). Personal disposable income was estimated using a combination of PIT data and Census self-reported income, and aggregated across the household to estimate equivalised household income. We estimated annual MBS (out-of-hospital only) and PBS OOP costs as a proportion of equivalised household income, and assessed progressivity by reporting this for each income decile and computing a Kakwani Index. Results We will present findings on progressivity overall, and separately by age, sex and location (incomplete at time of abstract submission). Conclusion / Implications Our study will present one measure regarding the equity of healthcare costs, and help to identify vulnerable or at-risk groups. These findings may inform policy changes on equity in the financing of healthcare. Newly linked data from the MADIP can be used to relate healthcare costs to ability to pay.https://ijpds.org/article/view/1594 |
| spellingShingle | Hsei Di Law Nicholas Biddle Emily Lancsar Jennifer Welsh Danielle Butler Rosemary J Korda Using Newly Linked Data to Assess Equity of Out-Of-Pocket Healthcare Costs in Australia International Journal of Population Data Science |
| title | Using Newly Linked Data to Assess Equity of Out-Of-Pocket Healthcare Costs in Australia |
| title_full | Using Newly Linked Data to Assess Equity of Out-Of-Pocket Healthcare Costs in Australia |
| title_fullStr | Using Newly Linked Data to Assess Equity of Out-Of-Pocket Healthcare Costs in Australia |
| title_full_unstemmed | Using Newly Linked Data to Assess Equity of Out-Of-Pocket Healthcare Costs in Australia |
| title_short | Using Newly Linked Data to Assess Equity of Out-Of-Pocket Healthcare Costs in Australia |
| title_sort | using newly linked data to assess equity of out of pocket healthcare costs in australia |
| url | https://ijpds.org/article/view/1594 |
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