第一个欧洲多中心对无家可归者癌症预防的队列研究的多源连贯性分析:数据质量研究
Antonio Blasco-Calafat1, Vicent Blanes-Selva1, Tobias Fragner2
1Biomedical Data Science Laboratory, Institute of Information and Communication Technologies, Universitat Politècnica de València, Valencia, Spain.
JMIR medical informatics
|November 14, 2025
概括
在对无家可归者的研究中,数据的一致性在欧洲各国有很大差异,因此需要对健康研究和政策进行特定国家的分析. 这凸显了这一群体内的异质性.
科学领域:
- 公共卫生 公共卫生
- 医疗保健服务研究 医疗服务研究
- 数据科学数据科学数据科学
背景情况:
- 确保跨多中心数据集的数据连贯性对于可靠的健康数据重复使用和防止偏见至关重要.
- 数据的异质性会导致研究结果的概括性不足.
- 该研究涉及欧洲多中心数据集的数据质量,该数据集涉及无家可归人口中癌症预防和早期检测.
研究的目的:
- 描述和标记欧洲无家可归者的多中心数据集中各站点数据的一致性.
- 使研究能够解决无家可归者面临的健康差异和医疗保健获取障碍.
- 在这个人群中适应和实施健康导航模型.
主要方法:
- 分析了一组数据集,包括来自奥地利,希腊,西班牙和英国的652个案例.
- 在基线,4周和干预结束时通过问卷收集纵向数据.
- 使用信息理论和几何方法评估数据变异性,以分析分布和完整性.
主要成果:
- 在总体分析和特定领域中,在4个试点国家中观察到大量的变化.
- 在医疗保健赋权,生活质量和人际沟通方面发现的最大差异.
- 西班牙显示出最明显的差异,在人际沟通和医疗保健服务使用方面缺失值很高.
结论:
- 健康数据可能是可比的,但在其他问卷领域的显著差异需要国家特定的分析.
- 这项研究强调了无家可归者之间的异质性.
- 强调对数据质量评估的关键需求,以指导未来在该领域的研究和政策.
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