Efficacy of clinical decision support systems: methods and estimates

O. Rebrova
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引用次数: 1

Abstract

Clinical decision support (CDS) systems are the medical technologies that go through their life cycle. Evaluation ofeffectiveness and safety should be carried out at its various stages at the development, in clinical trials, licensing, clinical and economic analysis, health technologies assessment. To date, the effectiveness and safety of CDS systems vary and are ambiguous there are both successes and failures. Hundreds of clinical trials are carried out, and more than a hundred of systematic reviews are published. When evaluating the efficacy and safety of CDS systems, two types of outcomes are usually estimated: indicators of medical care (volume, time, costs, etc.), and patient outcomes (clinical and surrogate). A slight increase in physicians adherence to clinical guidelines has been observed, but ithad very small influence on surrogate outcomes, and there is no effect on clinical patient outcomes. A slight increase in risk with respect to patient outcomes was found in only a few studies. However, the methodological quality of the evidence is very low. In this regard, a few products based on artificial intelligence have so far approached the licensing phase. The field of CDS systems is developing, but not yet sufficiently studied, and there is a long way to real successes ahead. Meanwhile, there is a wide gap between the postulated and empirically demonstrated benefits of CDS systems.
临床决策支持系统的有效性:方法和评估
临床决策支持(CDS)系统是贯穿其生命周期的医疗技术。应在开发、临床试验、许可、临床和经济分析、卫生技术评估等各个阶段对有效性和安全性进行评价。迄今为止,CDS系统的有效性和安全性各不相同,而且有成功也有失败。进行了数百项临床试验,并发表了一百多篇系统评论。在评估CDS系统的有效性和安全性时,通常估计两种类型的结果:医疗保健指标(数量、时间、成本等)和患者结果(临床和替代)。观察到医生对临床指南的依从性略有增加,但对替代结果的影响很小,对患者的临床结果没有影响。仅在少数研究中发现患者预后方面的风险略有增加。然而,证据的方法学质量非常低。在这方面,一些基于人工智能的产品到目前为止已经接近许可阶段。CDS系统领域正在发展,但尚未得到充分的研究,要取得真正的成功还有很长的路要走。与此同时,CDS系统的假设收益与经验证明的收益之间存在很大差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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