在中等保健环境中针对性开发和验证临床预测模型:电子健康记录数据的机遇和挑战
I S van Maurik1, H J Doodeman1, B W Veeger-Nuijens1
1Northwest Academy, Northwest Clinics Alkmaar, Pr Julianalaan 14, Alkmaar, 1815JE, Netherlands, 31 0880853821.
JMIR medical informatics
|October 24, 2024
概括
对临床预测模型 (CPM) 的有针对性的验证对于二级护理至关重要. 使用电子健康记录 (EHR) 数据与专家参与和严格的检查可以弥合CPM的验证差距.
科学领域:
- 医疗信息学 医疗信息学
- 临床流行病学 临床流行病学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 临床预测模型 (CPM) 需要在部署之前在预期的使用人群中进行验证.
- 由于稀缺的高质量数据,对二级护理机构的CPM验证存在重大差距.
- 电子健康记录 (EHR) 提供了生成数据的潜力,但需要仔细评估质量.
研究的目的:
- 强调针对中等护理中CPM的有针对性的验证的重要性.
- 探索使用电子健康记录数据来克服CPM验证差距.
- 提出实际步骤,以提高EHR数据质量,用于CPM开发和验证.
主要方法:
- 审查在二级护理环境中验证CPM所面临的挑战.
- 讨论使用EHR数据用于CPM验证的潜力和局限性.
- 建议采取三个实际步骤来提高电子健康记录数据质量:让当地电子健康记录专家参与,执行数据集有效性检查,并提供元数据.
主要成果:
- 当使用文本挖掘软件处理EHR数据时,可以生成大型结构化数据集.
- 电子健康记录数据的缺陷需要强大的验证策略.
- 涉及EHR专家,执行有效性检查和提供元数据提高了EHR数据集的质量.
结论:
- 针对性验证CPM对于在二级护理中有效的临床实施至关重要.
- 利用EHR数据,并提出质量改进,可以弥合验证差距.
- 这种方法有助于为二级护理机构开发和验证统计学上强大,高质量和可复制的CPM.
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