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<p>Clinical evidence underpins informed healthcare decisions, yet integrating it into real-time practice remains challenging due to intensive workloads, complex procedures, and time constraints. This study presents Quicker, an LLM-powered system that automates evidence synthesis and generates clinical recommendations following standard guideline development workflows. Quicker delivers an end-to-end pipeline from clinical questions to recommendations and supports customized decision-making through integrated tools and interactive interfaces. To evaluate how closely Quicker can reproduce guideline development processes, we constructed Q2CRBench-3, a benchmark derived from guideline development records for three diseases. Experiments show that Quicker produces precise question decomposition, expert-aligned retrieval, and near-comprehensive screening. Quicker assistance improved the accuracy of extracted study data, and its recommendations were more comprehensive and coherent than clinician-written ones. In system-level testing, Quicker working with one participant reduced recommendation development to 20–40 min. Overall, the findings demonstrate Quicker’s potential to enhance the speed and reliability of evidence-based clinical decision-making.</p>

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Streamlining evidence based clinical recommendations with large language models

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月22日

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  • Dubai Li,
  • Nan Jiang,
  • Kangping Huang,
  • Ruiqi Tu,
  • Shuyu Ouyang,
  • Huayu Yu,
  • Lin Qiao,
  • Chen Yu,
  • Tianshu Zhou,
  • Danyang Tong,
  • Qian Wang,
  • Mengtao Li,
  • Xiaofeng Zeng,
  • Yu Tian,
  • Xinping Tian,
  • Jingsong Li

摘要

Clinical evidence underpins informed healthcare decisions, yet integrating it into real-time practice remains challenging due to intensive workloads, complex procedures, and time constraints. This study presents Quicker, an LLM-powered system that automates evidence synthesis and generates clinical recommendations following standard guideline development workflows. Quicker delivers an end-to-end pipeline from clinical questions to recommendations and supports customized decision-making through integrated tools and interactive interfaces. To evaluate how closely Quicker can reproduce guideline development processes, we constructed Q2CRBench-3, a benchmark derived from guideline development records for three diseases. Experiments show that Quicker produces precise question decomposition, expert-aligned retrieval, and near-comprehensive screening. Quicker assistance improved the accuracy of extracted study data, and its recommendations were more comprehensive and coherent than clinician-written ones. In system-level testing, Quicker working with one participant reduced recommendation development to 20–40 min. Overall, the findings demonstrate Quicker’s potential to enhance the speed and reliability of evidence-based clinical decision-making.