在加拿大安大略省,根据国家编码任务,使用卫生行政数据识别无家可归者:一个验证研究
Lucie Richard1, Brooke Carter2, Rosane Nisenbaum1
1MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, Ontario, Canada.
Journal of clinical epidemiology
|June 16, 2024
概括
在安大略省卫生数据中验证无家可归病例定义显示,在国家编码任务后,敏感性得到改善. 这增强了对无家可归者健康需求的研究.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
背景情况:
- 对无家可归者的长度健康研究面临识别挑战.
- 安大略省卫生行政数据对于无家可归研究的有效性在2018年政策变化后是未知的.
- 一项国家任务现在要求在医院数据库中编码无家可归者.
研究的目的:
- 在安大略省卫生行政数据中验证用于识别无家可归者的案例定义.
- 评估国家无家可归者编码任务对数据准确性的影响.
- 优化在卫生数据库中识别无家可归者的方法.
主要方法:
- 使用多伦多 (2018-2022) 的数据评估了42个案例定义.
- 包括无家可归者 (n=640) 和有住所的人 (n=128,000) 的样本.
- 评估了灵敏度,特异性和预测值,以确定最佳定义.
主要成果:
- 最佳定义 (无家可归指标是在医院遇到的180天内) 显示了52.9%的灵敏度和99.5%的特异性.
- 对于那些在无家可归期间遇到医疗保健的人来说,敏感性提高到75.1%,特异性为98.5%.
- 假阳性表明数据库中可能存在过时的无家可归身份信息.
结论:
- 在安大略省,无家可归者的病例定义在健康数据中提供了中等到极佳的准确性.
- 敏感度显著改善后国家编码任务.
- 强制收集无家可归者数据对于了解和解决该人口的健康需求至关重要.
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