PDF(Pubmed)
Abstract：
This ISPOR Good Practices report provides a framework for assessing the suitability of electronic health records data for use in health technology assessments (HTAs). Although electronic health record (EHR) data can fill evidence gaps and improve decisions, several important limitations can affect its validity and relevance. The ISPOR framework includes 2 components: data delineation and data fitness for purpose. Data delineation provides a complete understanding of the data and an assessment of its trustworthiness by describing (1) data characteristics; (2) data provenance; and (3) data governance. Fitness for purpose comprises (1) data reliability items, ie, how accurate and complete the estimates are for answering the question at hand and (2) data relevance items, which assess how well the data are suited to answer the particular question from a decision-making perspective. The report includes a checklist specific to EHR data reporting: the ISPOR SUITABILITY Checklist. It also provides recommendations for HTA agencies and policy makers to improve the use of EHR-derived data over time. The report concludes with a discussion of limitations and future directions in the field, including the potential impact from the substantial and rapid advances in the diffusion and capabilities of large language models and generative artificial intelligence. The report\'s immediate audiences are HTA evidence developers and users. We anticipate that it will also be useful to other stakeholders, particularly regulators and manufacturers, in the future.
摘要：
这份ISPOR良好实践报告提供了一个框架，用于评估电子健康记录数据是否适合用于卫生技术评估（HTA）。尽管电子健康记录（EHR）数据可以填补证据空白并改善决策，几个重要的局限性会影响其有效性和相关性。ISPOR框架包括2个组件：数据描绘和数据适合性。数据描绘通过描述(1)数据特征;(2)数据来源;和(3)数据治理来提供对数据的完整理解和对其可信度的评估。适用性包括(1)数据可靠性项目，ie,如何准确和完整的估计是回答手头的问题和（2）数据相关性项目，从决策的角度评估数据适合回答特定问题的程度。该报告包括特定于EHR数据报告的检查表：ISPOR适用性检查表。它还为HTA机构和政策制定者提供了建议，以随着时间的推移改善EHR衍生数据的使用。报告最后讨论了该领域的局限性和未来方向，包括大型语言模型和生成人工智能的扩散和能力的实质性和快速发展带来的潜在影响。该报告的直接受众是HTA证据开发人员和用户。我们预计它也将对其他利益相关者有用，特别是监管机构和制造商，在未来。
