An Approach for Generating Realistic Australian Synthetic Healthcare Data

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Author(s)
Diouf, Ibrahima
Grimes, John
O'Brien, Mitchell J
Hassanzadeh, Hamed
Truran, Donna
Ngo, Hoa
Raniga, Parnesh
Lawley, Michael
Bauer, Denis C
Hansen, David
Khanna, Sankalp
Reguant, Roc
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Bichel-Findlay, J

Otero, P

Scott, P

Huesing, E

Date
2024
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Sydney, Australia

Abstract

Healthcare data is a scarce resource and access is often cumbersome. While medical software development would benefit from real datasets, the privacy of the patients is held at a higher priority. Realistic synthetic healthcare data can fill this gap by providing a dataset for quality control while at the same time preserving the patient’s anonymity and privacy. Existing methods focus on American or European patient healthcare data but none is exclusively focused on the Australian population. Australia is a highly diverse country that has a unique healthcare system. To overcome this problem, we used a popular publicly available tool, Synthea, to generate disease progressions based on the Australian population. With this approach, we were able to generate 100,000 patients following Queensland (Australia) demographics.

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MEDINFO 2023 — The Future Is Accessible: Proceedings of the 19th World Congress on Medical and Health Informatics

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310

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© 2024 International Medical Informatics Association (IMIA) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0)

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Diouf, I; Grimes, J; O'Brien, MJ; Hassanzadeh, H; Truran, D; Ngo, H; Raniga, P; Lawley, M; Bauer, DC; Hansen, D; Khanna, S; Reguant, R, An Approach for Generating Realistic Australian Synthetic Healthcare Data, MEDINFO 2023 — The Future Is Accessible: Proceedings of the 19th World Congress on Medical and Health Informatics, 2024, 310, pp. 820-824