抗菌素处方的计算机决策支持:每个抗生素管理员应该知道的。

Davide Bosetti, Rebecca Grant, Gaud Catho
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引用次数: 0

摘要

目的:探讨计算机临床决策支持系统(CDSS)在抗菌药物管理(AMS)中的潜在作用,并确定其有效性和实施方面的重大挑战。设计:叙述回顾。背景和方法:本综述基于不同医疗环境(如医院和初级保健设施)中AMS中CDSS的现有文献。评估的系统包括独立工具和集成到电子健康记录(EHR)中的工具,具有基于规则的专家逻辑和新的机器学习(ML)模型。CDSS功能包括处方指导、警报、抗性预测和降级协议。结果:CDSS旨在通过整合临床指南和每位患者的具体数据来帮助抗菌药物处方。尽管它们在理论上有潜力,但它们的有效性经常受到临床实践不一致、用户参与度低和设计不充分的阻碍。许多系统是被动的,不能很好地满足用户需求,或者在其建议中缺乏透明度。由于结果不同,研究方法质量差,以及在复杂的护理环境中归因于因果关系的复杂性,评估这些系统具有挑战性。实现的障碍包括警惕疲劳、感知到的时间限制、与现有工作流的不匹配以及对更改的抵制。像COMPASS试验这样的实例表明了设计和实际应用之间的脱节,强调了以用户为中心的开发、清晰的推理以及强制性和咨询要素之间的平衡方法的必要性。结论:CDSS具有改善抗菌药物使用的潜力,但评估和实施方面的挑战阻碍了其广泛影响。实现它们的价值需要更好的集成、可用性和针对复杂医疗保健环境量身定制的严格研究框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computerized decision support for antimicrobial prescribing: what every antibiotic steward should know.

Objective: To examine the potential role of computerized clinical decision support systems (CDSS) in antimicrobial stewardship (AMS) and to identify significant challenges concerning their effectiveness and implementation.

Design: Narrative review.

Setting and methods: This review is based on existing literature regarding CDSS in AMS across various healthcare environments, such as hospitals and primary care facilities. The systems evaluated include both stand-alone tools and those integrated into electronic health records (EHR), featuring expert rule-based logic and new machine learning (ML) models. CDSS capabilities include prescribing guidance, alerts, resistance prediction, and de-escalation protocols.

Results: CDSS are intended to aid in antimicrobial prescribing by integrating clinical guidelines with data specific to each patient. Despite their theoretical potential, their effectiveness is often hindered by inconsistent incorporation into clinical practices, low user engagement, and inadequate design. Many systems are reactive, not well-suited to user needs, or lack transparency in their recommendations. Evaluating these systems is challenging due to varied outcomes, poor methodological quality of studies, and the complexity of attributing causality in intricate care settings. Barriers to implementation include alert fatigue, perceived time constraints, poor fit with existing workflows, and resistance to change. Instances like the COMPASS trial demonstrate the disconnect between design and practical application, underscoring the necessity for user-focused development, clear reasoning, and a balanced approach between mandatory and advisory elements.

Conclusions: CDSS have the potential to improve antimicrobial use, but widespread impact is hindered by evaluation and implementation challenges. Realizing their value requires better integration, usability, and rigorous research frameworks tailored to complex healthcare settings.

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