在行政患者登记册中验证前臂骨折诊断
Tone Kristin Omsland1, Lene B Solberg2, Åshild Bjørnerem3,4,5
1Department of Community Medicine and Global Health, Institute of Health and Society, University of Oslo, Blindern, Po box 1130, 0318, Oslo, Norway. t.k.omsland@medisin.uio.no.
Archives of osteoporosis
|August 24, 2023
概括
在挪威患者登记 (NPR) 数据中的前臂骨折诊断显示出高准确性. 定义前臂骨折的最佳算法取决于具体的研究目的.
科学领域:
- 整形外科 整形外科 整形外科
- 医疗信息学 医疗信息学
- 流行病学 流行病学
背景情况:
- 前臂骨折通常在挪威患者登记册 (NPR) 中记录.
- 这些行政数据的验证对于准确的流行病学研究至关重要.
- 患者管理系统 (PAS) 数据是NPR注册的来源.
研究的目的:
- 为了验证在行政数据中记录的前臂骨折诊断.
- 评估洗期的实用性,后续代码和定义意外前臂骨折的程序代码.
主要方法:
- 一项基于医院的验证研究,涉及年龄≥19岁的前臂骨折患者.
- 审查了五家挪威医院的行政数据 (ICD-10代码S52) 和医疗记录.
- 使用图像报告和医疗记录作为黄金标准计算灵敏度和积极预测值 (PPV).
主要成果:
- 在PAS中,前臂骨折诊断的灵敏度为90.4%.
- 积极预测值 (PPV) 从73.9%提高到90.5%,有6个月的洗期.
- 整合程序和后续代码增加了PPV至94.0%,但降低了敏感度至69.0%.
结论:
- 在PAS的前臂骨折诊断表明相对较高的灵敏度.
- 在行政数据中定义前臂骨折的算法选择应该与研究目标保持一致.
- 这些发现为利用行政病例登记册进行骨折诊断提供了有价值的见解.
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