在大型临床数据集中创建API调用,用于手术研究成果研究成果
Brian Yuen1, Rachel L Wolansky2, Joseph A Sujka2
1University of Central Florida, Orlando, FL, USA.
The American surgeon
|October 25, 2025
概括
应用程序编程接口 (API) 简化了临床研究数据的访问. 使用NIH和CMS数据集的API可以实现自动,可重复的数据提取和分析,提高研究效率.
科学领域:
- 医疗信息学 医疗信息学
- 临床研究信息学
- 在医疗保健中的数据科学.
背景情况:
- 应用程序编程接口 (API) 促进软件系统的互操作性和数据交换.
- API为临床研究提供了对大型数据集的高效访问,支持可重复的工作流.
- 自动数据提取和分析对于现代健康研究至关重要.
研究的目的:
- 展示API对于访问和分析大规模临床和研究数据集的实用性.
- 用Python和公开可用的健康数据展示可复制的数据提取方法.
- 突出API驱动工作流程的潜力,以提高研究效率.
主要方法:
- 构建了Python脚本以通过API查询NIH RePORTER和CMS医疗保险数据集.
- 使用JSON有效载荷用于NIH API调用以检索项目资金数据.
- 使用CMS API调用的URL参数来过医疗保险入学数据根据州和年份.
- 在多年内自动收集数据,并以CSV格式保存输出.
主要成果:
- 成功地从NIH RePORTER中提取了项目级资金数据.
- 从CMS数据集中检索过的医疗保险入学数据.
- 使用API调用证明了数据收集的可扩展性和自动化.
- 以CSV格式生成数据,适合进一步分析.
结论:
- 基于API的数据提取为临床研究提供了可扩展和可重复的方法.
- 从NIH和CMS等来源利用API可以实现自动数据检索和定制过.
- 广泛采用API工作流可以显著提高医疗保健中的数据可访问性和研究效率.
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