Borchert Florian, Wullenweber Paul, Oeser Annika, Kreuzberger Nina, Karge Torsten, Langer Thomas, Skoetz Nicole, Wieler Lothar H, Schapranow Matthieu-P, Arnrich Bert
Hasso Plattner Institute for Digital Engineering, University of Potsdam, Potsdam, Germany.
Institute of Public Health, Medical Faculty and University Hospital Cologne, University of Cologne, Cologne, Germany.
NPJ Digit Med. 2025 Apr 27;8(1):227. doi: 10.1038/s41746-025-01648-5.
Delays in translating new medical evidence into clinical practice hinder patient access to the best available treatments. Our data reveals an average delay of nine years from the initiation of human research to its adoption in clinical guidelines, with 1.7-3.0 years lost between trial publication and guideline updates. A substantial part of these delays stems from slow, manual processes in updating clinical guidelines, which rely on time-intensive evidence synthesis workflows. The Next Generation Evidence (NGE) system addresses this challenge by harnessing state-of-the-art biomedical Natural Language Processing (NLP) methods. This novel system integrates diverse evidence sources, such as clinical trial reports and digital guidelines, enabling automated, data-driven analyses of the time it takes for research findings to inform clinical practice. Moreover, the NGE system provides precision-focused literature search filters tailored specifically for guideline maintenance. In benchmarking against two German oncology guidelines, these filters demonstrate exceptional precision in identifying pivotal publications for guideline updates.
将新的医学证据转化为临床实践的延迟阻碍了患者获得最佳可用治疗。我们的数据显示,从人体研究开始到其被纳入临床指南平均延迟九年,在试验发表和指南更新之间损失1.7至3.0年。这些延迟的很大一部分源于更新临床指南的缓慢手动过程,这依赖于耗时的证据综合工作流程。下一代证据(NGE)系统通过利用最先进的生物医学自然语言处理(NLP)方法应对这一挑战。这个新颖的系统整合了多种证据来源,如临床试验报告和数字指南,能够对研究结果为临床实践提供信息所需的时间进行自动化、数据驱动的分析。此外,NGE系统提供专门为指南维护量身定制的精准文献搜索过滤器。在与两项德国肿瘤学指南的基准测试中,这些过滤器在识别指南更新的关键出版物方面表现出卓越的精准度。