Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Australia.
Macquarie University, Department of Biomedical Sciences, Faculty of Medicine and Health Science, Macquarie Park, Australia.
Stud Health Technol Inform. 2024 Jan 25;310:820-824. doi: 10.3233/SHTI231079.
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.
医疗保健数据是一种稀缺资源,获取往往很麻烦。虽然医疗软件开发可以从真实数据集受益,但患者的隐私被置于更高的优先级。现实的合成医疗保健数据可以通过提供数据集来进行质量控制,同时保护患者的匿名性和隐私,从而填补这一空白。现有的方法侧重于美国或欧洲的患者医疗保健数据,但没有专门针对澳大利亚人口的方法。澳大利亚是一个高度多样化的国家,拥有独特的医疗保健系统。为了克服这个问题,我们使用了一个流行的公开可用工具 Synthea,根据澳大利亚人口生成疾病进展。通过这种方法,我们能够根据昆士兰州(澳大利亚)的人口统计数据生成 10 万名患者。