Sun Xingzhi, Zhao Wei, Zuo Lei, Dumitriu Alexandra, Lee Chuang-Chung, Cui Nan, Liao Xiyang, Zhao Tingting, Jiang Xuehan, Xu Zhuoyang, Hu Gang, Xie Guotong, Wu Hong, Huang Yahua
Ping An Health Technology, Beijing, China.
Sanofi, Cambridge, Massachusetts, U.S.A.
AMIA Annu Symp Proc. 2020 Mar 4;2019:838-847. eCollection 2019.
Clinical decision support system (CDSS) plays a significant role nowadays and it assists physicians in making decisions for treatment. Generally based on clinical guideline, the principles of the recommendation are provided and may suggest several candidate medications for similar patient group with certain clinical conditions. However, it is challenging to prioritize these candidates and even refine the guideline to a finer level for patient-specific recommendation. Here we propose a method and system to integrate the clinical knowledge and real-world evidence (RWE) for type 2 diabetes treatment, to enable both standardized and personalized medication recommendation. The RWE is generated by medication effectiveness analysis and subgroup analysis. The knowledge model has been verified by clinical experts from the advanced hospitals. The data verification results show that the medications that are consistent with the method recommendation can lead to better clinical outcome in terms of glycemic control, compared to those inconsistent.
临床决策支持系统(CDSS)如今发挥着重要作用,它协助医生做出治疗决策。一般基于临床指南,提供推荐原则,并可能针对具有特定临床状况的相似患者群体推荐几种候选药物。然而,对这些候选药物进行优先级排序,甚至将指南细化到针对特定患者的更精细水平具有挑战性。在此,我们提出一种方法和系统,用于整合2型糖尿病治疗的临床知识和真实世界证据(RWE),以实现标准化和个性化的药物推荐。RWE通过药物疗效分析和亚组分析生成。该知识模型已得到高级医院临床专家的验证。数据验证结果表明,与那些不一致的药物相比,与该方法推荐一致的药物在血糖控制方面可带来更好的临床结果。