Clinical decision support(CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors(ME) and adverse drug events(ADEs). Critically ill patients a...Clinical decision support(CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors(ME) and adverse drug events(ADEs). Critically ill patients are at increased risk for ME, ADEs and serious negative outcomes related to these events. Capitalizing on CDS to detect ME and prevent adverse drug related events has the potential to improve patient outcomes. The key to an effective medication safety surveillance system incorporating CDS is advancing the signals for alerts by using trajectory analyses to predict clinical events, instead of waiting for these events to occur. Additionally, incorporating cutting-edge biomarkers into alert knowledge in an effort to identify the need to adjust medication therapy portending harm will advance the current state of CDS. CDS can be taken a step further to identify drug related physiological events, which are less commonly included in surveillance systems. Predictive models for adverse events that combine patient factors with laboratory values and biomarkers are being established and these models can be the foundation for individualized CDS alerts to prevent impending ADEs.展开更多
目的研发实施基于CDSS(Clinical Decision Support System,CDSS)的护理信息系统,并评价该系统的临床应用效果。方法根据临床工作需要研发并运行基于CDSS的护理信息化系统,采用便利抽样法在该系统实施前、后各抽取300名患者,100名护理人...目的研发实施基于CDSS(Clinical Decision Support System,CDSS)的护理信息系统,并评价该系统的临床应用效果。方法根据临床工作需要研发并运行基于CDSS的护理信息化系统,采用便利抽样法在该系统实施前、后各抽取300名患者,100名护理人员,并对应用前后护士自我效能感、护士对工作的满意度、患者满意度、护理不良事件等指标进行调查分析,评价护理信息系统的使用效果。结果实施护理信息系统后护士自我效能感明显提高(P<0.05);患者对护理的满意度、护士对工作的满意度,均显著提高(均P<0.01)。实施前、后相关不良事件比较,差异有统计学意义(均P<0.05)。结论基于CDSS的护理信息系统的使用,能提高护士对工作热情与自我认同感,提高患者满意度,降低安全隐患,促进护理管理的系统化科学化。展开更多
基金Supported by The Agency for Healthcare Research and Quality,No.R18HS02420-01
文摘Clinical decision support(CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors(ME) and adverse drug events(ADEs). Critically ill patients are at increased risk for ME, ADEs and serious negative outcomes related to these events. Capitalizing on CDS to detect ME and prevent adverse drug related events has the potential to improve patient outcomes. The key to an effective medication safety surveillance system incorporating CDS is advancing the signals for alerts by using trajectory analyses to predict clinical events, instead of waiting for these events to occur. Additionally, incorporating cutting-edge biomarkers into alert knowledge in an effort to identify the need to adjust medication therapy portending harm will advance the current state of CDS. CDS can be taken a step further to identify drug related physiological events, which are less commonly included in surveillance systems. Predictive models for adverse events that combine patient factors with laboratory values and biomarkers are being established and these models can be the foundation for individualized CDS alerts to prevent impending ADEs.
文摘目的研发实施基于CDSS(Clinical Decision Support System,CDSS)的护理信息系统,并评价该系统的临床应用效果。方法根据临床工作需要研发并运行基于CDSS的护理信息化系统,采用便利抽样法在该系统实施前、后各抽取300名患者,100名护理人员,并对应用前后护士自我效能感、护士对工作的满意度、患者满意度、护理不良事件等指标进行调查分析,评价护理信息系统的使用效果。结果实施护理信息系统后护士自我效能感明显提高(P<0.05);患者对护理的满意度、护士对工作的满意度,均显著提高(均P<0.01)。实施前、后相关不良事件比较,差异有统计学意义(均P<0.05)。结论基于CDSS的护理信息系统的使用,能提高护士对工作热情与自我认同感,提高患者满意度,降低安全隐患,促进护理管理的系统化科学化。
