Enhancing Accurate Delirium Detection in Older Patients With Heart Failure: Integrating Education and an Electronic Health Record Tool for Nurses.

IF 0.2 Q4 NURSING
Eva Tabarani, Kimberly Hickey, Raymond R Blush
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Abstract

Background: Detecting delirium accurately in older patients with heart failure (HF) is challenging for nurses due to difficulties in assessing baseline cognition, leading to inaccurate delirium assessment. Objective: The project aimed to evaluate the effectiveness of an educational intervention and a documentation tool in the electronic health record (EHR) to enhance delirium detection rates by up to 30% in patients over 65 years with HF. Methods: Delirium detection rates were assessed pre- and postimplementation through chart review spanning 8 weeks. The Chart-based Delirium Identification Instrument was applied to preimplementation (2023) and postimplementation (2024) data for comparison over 8 weeks. Additionally, the project included a pre-post survey to examine nurses' self-reported knowledge, confidence, and perspectives on delirium detection and management. Results: Nurses achieved a 100% detection rate by accurately identifying the sole case of delirium postimplementation. Notably, nurses accurately ruled out delirium in patients who tested negative. Additionally, they reported increased knowledge and confidence in delirium detection. Conclusions: The dual intervention of nurses' education and structural documentation support contributed to enhancing the nurses' ability to accurately identify delirium. The intervention facilitated the consistent identification and documentation of baseline cognition. The streamlined process ensured consistency and facilitated easy retrieval by nurses when completing the Confusion Assessment Method for delirium detection. Implications for Nursing: Combining nurse education and an EHR tool ensures equitable access to resources for accurate delirium detection among older patients with HF. Improving delirium detection rates helps provide targeted interventions, ultimately reducing disparities in delirium-related outcomes.

提高老年心力衰竭患者谵妄的准确检测:整合教育和护士电子健康记录工具。
背景:由于难以评估基线认知,导致谵妄评估不准确,因此准确检测老年心力衰竭(HF)患者的谵妄对护士来说是一项挑战。目的:该项目旨在评估教育干预和电子健康记录(EHR)文件工具的有效性,以提高65岁以上HF患者谵妄检出率高达30%。方法:通过为期8周的图表回顾,评估治疗前后谵妄检出率。应用基于图表的谵妄识别仪对实施前(2023年)和实施后(2024年)的数据进行8周的比较。此外,该项目还包括一项前后调查,以检查护士自我报告的谵妄检测和管理的知识、信心和观点。结果:护士对唯一一例实施后谵妄的准确识别达到100%的检出率。值得注意的是,护士准确地排除了检测呈阴性的患者的谵妄。此外,他们报告了谵妄检测的知识和信心的增加。结论:护士教育和结构化文献支持的双重干预有助于提高护士对谵妄的准确识别能力。干预促进了基线认知的一致识别和记录。简化的流程确保了一致性,方便护士在完成谵妄检测混淆评估方法时检索。对护理的启示:结合护士教育和电子病历工具确保公平获取资源,以准确检测老年心衰患者的谵妄。提高谵妄检出率有助于提供有针对性的干预措施,最终减少谵妄相关结果的差异。
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
0.60
自引率
0.00%
发文量
45
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