High-precision information retrieval for rapid clinical guideline updates.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 40289217.
- Also identified by DOI 10.1038/s41746-025-01648-5 and PMC identifier 12034796.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
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.