Suppr超能文献

证明临床试验中常规收集的医疗保健系统数据的数据完整性(DEDICaTe):概念验证研究。

Demonstrating the data integrity of routinely collected healthcare systems data for clinical trials (DEDICaTe): A proof-of-concept study.

机构信息

MRC Clinical Trials Unit at UCL (MRC CTU), Institute of Clinical Trials and Methodology, UCL, London, UK.

Health Data Research UK (HDR UK), London, UK.

出版信息

Health Informatics J. 2024 Jul-Sep;30(3):14604582241276969. doi: 10.1177/14604582241276969.

Abstract

Healthcare systems data (also known as real-world or routinely collected health data) could transform the conduct of clinical trials. Demonstrating integrity and provenance of these data is critical for clinical trials, to enable their use where appropriate and avoid duplication using scarce trial resources. Building on previous work, this proof-of-concept study used a data intelligence tool, the "Central Metastore," to provide metadata and lineage information of nationally held data. The feasibility of NHS England's Central Metastore to capture detailed records of the origins, processes, and methods that produce four datasets was assessed. These were England's Hospital Episode Statistics (Admitted Patient Care, Outpatients, Critical Care) and the Civil Registration of Deaths (England and Wales). The process comprised: information gathering; information ingestion using the tool; and auto-generation of lineage diagrams/content to show data integrity. A guidance document to standardise this process was developed. The tool can ingest, store and display data provenance in sufficient detail to support trust and transparency in using these datasets for trials. The slowest step was information gathering from multiple sources, so consistency in record-keeping is essential.

摘要

医疗保健系统数据(也称为真实世界或常规收集的健康数据)可以改变临床试验的进行方式。为了使临床试验能够在适当的情况下使用这些数据,并避免使用稀缺的试验资源进行重复,证明这些数据的完整性和来源至关重要。本概念验证研究在前人的工作基础上,使用数据智能工具“中央元数据存储库”来提供全国性数据的元数据和沿袭信息。评估了英国国家医疗服务体系(NHS England)中央元数据存储库捕获四个数据集的起源、过程和方法的详细记录的可行性。这些数据集包括英格兰的医院入院统计数据(住院病人护理、门诊病人、重症监护)和死亡民事登记数据(英格兰和威尔士)。该过程包括:信息收集;使用工具进行信息摄取;以及自动生成沿袭图/内容以显示数据完整性。制定了一份标准化该过程的指南文件。该工具可以详细摄取、存储和显示数据来源,以支持在临床试验中使用这些数据集的信任和透明度。最慢的步骤是从多个来源收集信息,因此记录的一致性至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/38be/7617287/a49e90afdead/EMS201282-f001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验