Adverse Drug Reactions in Moderate Sedation: Process Improvement During a Pandemic

IF 2.6 Q1 SURGERY
J. Bayne, A. Craft, Alex Ho, Jenna Mastromarino Riley
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Abstract

Background: A gap analysis identified the need for process improvement surrounding the identification and reporting of adverse drug reactions related to moderate sedation. A change to documentation was selected to address this gap. The challenge was disseminating the change in a meaningful way during a time of high census and limited staffing due to the COVID-19 pandemic. Complex adaptive systems theory was used to plan interventions in the current climate. Methods: Process improvement was organized into Plan-Do-Study-Act cycles guided by the gap analysis, literature, and aims. Quantitative data analysis was conducted using chart audits and a Likert survey. Interventions: Adoption of end-user-redesigned documentation was completed over time using one-on-one instruction, brief just-in-time education sessions at huddles, and ongoing feedback. Results: The survey results demonstrated a significant increase in adverse event knowledge (p = <0.01) and documentation confidence following just-in-time training (p < .01). Chart audits revealed an increase in identification of adverse events (p=0.03). Conclusions: Using a theory-based approach to implement process improvement is a successful way to create change in a challenging environment. Identification of adverse drug reactions related to moderate sedation increased, which is essential for evaluation and safe administration.
中度镇静的药物不良反应:大流行期间的过程改善
背景:一项差距分析表明,在中度镇静相关药物不良反应的识别和报告方面,需要进行流程改进。选择对文档进行更改以解决此差距。挑战在于,在2019冠状病毒病大流行导致人口普查高度密集、人员配备有限的时期,以有意义的方式传播这一变化。复杂适应系统理论被用于规划当前气候下的干预措施。方法:在差距分析、文献和目标的指导下,将过程改进组织为计划-执行-研究-行动循环。定量数据分析采用图表审计和李克特调查进行。干预措施:采用最终用户重新设计的文档,随着时间的推移,使用一对一的指导,在会议上进行简短的即时教育会议,以及持续的反馈。结果:调查结果显示,及时培训后不良事件知识显著增加(p = <0.01),文件置信度显著提高(p <0.01)。图表审核显示不良事件的识别增加(p=0.03)。结论:使用基于理论的方法来实施过程改进是在具有挑战性的环境中创造变化的成功方法。与中度镇静相关的药物不良反应的鉴定增加,这对评估和安全给药至关重要。
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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来源期刊
CiteScore
6.80
自引率
8.10%
发文量
37
审稿时长
9 weeks
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