V. Traynor, B. Ho, J. Bimrose, M. Riegel, H. Chiu, L. M. Boehm, M. Hayter, S. Neville
{"title":"Nurses Must Improve Delirium Care: A Call to Action","authors":"V. Traynor, B. Ho, J. Bimrose, M. Riegel, H. Chiu, L. M. Boehm, M. Hayter, S. Neville","doi":"10.1111/jocn.17757","DOIUrl":null,"url":null,"abstract":"<p>World Delirium Awareness Day is March 12, 2025. This important annual event is a reminder that delirium is a frequently overlooked yet treatable health issue. Globally, delirium significantly and negatively impacts the wellbeing of millions of people, particularly those who are older. The purpose of this event is to raise awareness about delirium and the wide-ranging effects it has on people experiencing delirium, their families, carers and significant others, as well as health systems and health professionals.</p><p>Nurses are the health professional group who spend the most time with consumers of health services, their families and significant others. We pride ourselves on taking a holistic approach to delivering health services. These services include, but are not limited to, therapeutic communication, socio-cultural understandings of consumers of health services and the utilisation of evidence-based practice that informs assessment and clinical decision-making activities.</p><p>Why is it that despite its prevalence, delirium remains under diagnosed and is frequently poorly managed? Nurses are integral to improving delirium outcomes, yet even with over 30 years of empirical evidence, the delirium landscape remains unchanged. This editorial reminds nurses that delirium is not an inevitable consequence of getting older and being unwell. It is preventable and with early detection and intervention positively impacts on the health and wellbeing of people. We are using World Delirium Awareness Day as a ‘call to action’ and urge nurses to commit to ending 30 years of inaction.</p><p>Understanding the past is essential to informing the future. Over several years this journal has published a number of empirically based manuscripts on delirium, each providing valuable insights to guide nurses' assessment and decision-making. These manuscripts promoted best practice in delirium care and should have led to improved patient outcomes, enabling individuals to return home in the best possible state of health. Some of the more significant contributions have related to intensive care-acquired delirium, including findings that delirious patients have significantly less factual recall, as well as encouraging nurses to fill in the ‘missing gaps’ for people, and how the use of physical restraints contributes significantly to the incidence of delirium. The potential long-term effects of delirium in all settings should not be underestimated though, as developing delirium can increase a person's risk of mortality. It is also no surprise that delivering nursing care to a person with delirium is considered to be a burden, particularly if the person is is unable to cooperative and difficult to offer care to. Nurses should know that being vigilant when assessing behaviour changes, like disorientation and decreased psychomotor activity, can serve as early warning signs for delirium. Evidence indicates that improving knowledge and clinical assessment skill acquisition, as well as enabling nurses to implement non-pharmacological interventions like the timely removal of urinary catheters, managing pain, and decreasing the use of physical restraints will reduce delirium.</p><p>The focus on delirium in Intensive Care Unit (ICU) is warranted because of the high prevalence rate in this setting. While risk factors are well documented, including older age, higher severity of illness and pain scores, elevated blood urea levels and increased requirements for mechanical ventilation, sedation and physical restraints, further work is required to ensure early detection and prevention of the significant adverse consequences of delirium in ICU (Ho et al. <span>2023</span>). Management strategies are documented for ICU, with the most effective being a focus on prevention and early detection, employing the ABCDEF bundle, regular assessment of pain and level of consciousness, promoting early mobility and engaging family members to reorient patients. Capturing the severity of delirium in ICU is possible with the well validated CAM-ICU-7, ICDSC and DRS-R98 tools. There is also significant available evidence about the effectiveness of nonpharmacologic interventions such as reorientation, cognitive stimulation and minimising environmental stressors like noise and lights. Not surprisingly, multicomponent interventions are the most effective non-pharmacological strategy (Chen et al. <span>2022</span>). Nurses should be leading the implementation of nonpharmacologic interventions to prevent and treat delirium. However, evidence suggests this is not the case, and delirium prevalence remains unacceptably high.</p><p>Now that digital technologies are part of the healthcare vernacular, nurses have an opportunity to take a leadership role in delirium care. Delirium detection has been described as subjective, requiring bedside workload effort, and resulting in treatment delays. In addition, since delirium has a sudden onset and fluctuating manifestations, detection can be challenging. The integration of artificial intelligence (AI) into nursing practice has the potential to enhance delirium deetection and care.</p><p>Machine learning (ML) algorithms have been shown to be effective in delirium prediction. A meta-analysis found excellent performance of ML in predicting delirium with a pooled sensitivity of 0.85 and specificity of 0.80 (Xie et al. <span>2022</span>). Combining ML algorithms with wearable technology shows even greater potential for non-invasive continuous monitoring solutions. Researchers around the globe are trialling the combination of ML models with actigraphic activity monitors to improve delirium prediction performance, with a specific focus on the insights gained from night-time activity data.</p><p>AI provides an alternative approach using natural language processing (NLP) to enhance the accuracy of delirium detection. The NLP approach extracts relevant words from the clinical narrative evident in nursing documentation, designed to improve diagnostic precision by identifing delirium symptoms from words that may be overlooked during routine evaluations (Wang et al. <span>2022</span>).</p><p>AI tools have the potential to facilitate early management of delirium. A new AI-AntiDelirium platform assists nurses in the real-time monitoring of vital signs, evaluating risk factors, providing timely alerts and developing personalised care plans. There is emerging evidence to suggest that the AI-AntiDelirium system enhances nurses' adherence to delirium prevention guidelines.</p><p>The numerous empirical studies, published in this journal, and beyond, provide evidence about the nursing knowledge and skills needed to deliver evidence-based delirium care. However, for several years this evidence has not translated into clinical practice. Organisational systems and clinical environments often hinder nurses from providing optimal delirium care. There is also evidence that health service managers react to problems like delirium with short-term solutions rather than investing in long-term solutions, for example, supporting professional development opportunities that enable nurses to transform their workplace and address clinical problems such as delirium mismanagement.</p><p>As a reminder, this editorial is a call to action. As nurses we must commit and be change agents, promoting and modelling knowledge translation activities that result in reducing the incidence and prevalence of delirium. We understand that healthcare organisations service and respond to the needs of their communities and that, globally, many healthcare systems are resource ‘poor’. As a discipline, we therefore have an opportunity to lead the transformation of delirium care. Firstly, nurses should demand professional development opportunities with a focus on using resource efficient nonpharmacological nursing interventions. Secondly, nurses need to be knowledgeable about the role and use of AI and ML as mechanisms that support delirium decision making. Finally, adoption of comprehensive bundled strategies like the ABCDEF bundle in the ICU and the Age-Friendly Health Systems framework, incorporating the 4Ms (what matters, medication, mentation, and mobility), is crutial for improving health outcomes and effectively reduce delirium incidence and prevalence (Kwak et al. <span>2023</span>).</p><p><b>V. Traynor:</b> conceptualisation, project administration, writing of the manuscript, editing of the manuscript. <b>S. Neville:</b> conceptualisation, project administration, writing of the manuscript, editing of the manuscript. <b>M. Hayter:</b> review and editing of the manuscript. All other authors: writing of the manuscript.</p><p>L.M. Boehm is receiving funding from the National Institutes of Health National Institute on Aging. The other authors declare no conflicts of interest.</p>","PeriodicalId":50236,"journal":{"name":"Journal of Clinical Nursing","volume":"34 6","pages":"1979-1981"},"PeriodicalIF":3.5000,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jocn.17757","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Clinical Nursing","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jocn.17757","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
Abstract
World Delirium Awareness Day is March 12, 2025. This important annual event is a reminder that delirium is a frequently overlooked yet treatable health issue. Globally, delirium significantly and negatively impacts the wellbeing of millions of people, particularly those who are older. The purpose of this event is to raise awareness about delirium and the wide-ranging effects it has on people experiencing delirium, their families, carers and significant others, as well as health systems and health professionals.
Nurses are the health professional group who spend the most time with consumers of health services, their families and significant others. We pride ourselves on taking a holistic approach to delivering health services. These services include, but are not limited to, therapeutic communication, socio-cultural understandings of consumers of health services and the utilisation of evidence-based practice that informs assessment and clinical decision-making activities.
Why is it that despite its prevalence, delirium remains under diagnosed and is frequently poorly managed? Nurses are integral to improving delirium outcomes, yet even with over 30 years of empirical evidence, the delirium landscape remains unchanged. This editorial reminds nurses that delirium is not an inevitable consequence of getting older and being unwell. It is preventable and with early detection and intervention positively impacts on the health and wellbeing of people. We are using World Delirium Awareness Day as a ‘call to action’ and urge nurses to commit to ending 30 years of inaction.
Understanding the past is essential to informing the future. Over several years this journal has published a number of empirically based manuscripts on delirium, each providing valuable insights to guide nurses' assessment and decision-making. These manuscripts promoted best practice in delirium care and should have led to improved patient outcomes, enabling individuals to return home in the best possible state of health. Some of the more significant contributions have related to intensive care-acquired delirium, including findings that delirious patients have significantly less factual recall, as well as encouraging nurses to fill in the ‘missing gaps’ for people, and how the use of physical restraints contributes significantly to the incidence of delirium. The potential long-term effects of delirium in all settings should not be underestimated though, as developing delirium can increase a person's risk of mortality. It is also no surprise that delivering nursing care to a person with delirium is considered to be a burden, particularly if the person is is unable to cooperative and difficult to offer care to. Nurses should know that being vigilant when assessing behaviour changes, like disorientation and decreased psychomotor activity, can serve as early warning signs for delirium. Evidence indicates that improving knowledge and clinical assessment skill acquisition, as well as enabling nurses to implement non-pharmacological interventions like the timely removal of urinary catheters, managing pain, and decreasing the use of physical restraints will reduce delirium.
The focus on delirium in Intensive Care Unit (ICU) is warranted because of the high prevalence rate in this setting. While risk factors are well documented, including older age, higher severity of illness and pain scores, elevated blood urea levels and increased requirements for mechanical ventilation, sedation and physical restraints, further work is required to ensure early detection and prevention of the significant adverse consequences of delirium in ICU (Ho et al. 2023). Management strategies are documented for ICU, with the most effective being a focus on prevention and early detection, employing the ABCDEF bundle, regular assessment of pain and level of consciousness, promoting early mobility and engaging family members to reorient patients. Capturing the severity of delirium in ICU is possible with the well validated CAM-ICU-7, ICDSC and DRS-R98 tools. There is also significant available evidence about the effectiveness of nonpharmacologic interventions such as reorientation, cognitive stimulation and minimising environmental stressors like noise and lights. Not surprisingly, multicomponent interventions are the most effective non-pharmacological strategy (Chen et al. 2022). Nurses should be leading the implementation of nonpharmacologic interventions to prevent and treat delirium. However, evidence suggests this is not the case, and delirium prevalence remains unacceptably high.
Now that digital technologies are part of the healthcare vernacular, nurses have an opportunity to take a leadership role in delirium care. Delirium detection has been described as subjective, requiring bedside workload effort, and resulting in treatment delays. In addition, since delirium has a sudden onset and fluctuating manifestations, detection can be challenging. The integration of artificial intelligence (AI) into nursing practice has the potential to enhance delirium deetection and care.
Machine learning (ML) algorithms have been shown to be effective in delirium prediction. A meta-analysis found excellent performance of ML in predicting delirium with a pooled sensitivity of 0.85 and specificity of 0.80 (Xie et al. 2022). Combining ML algorithms with wearable technology shows even greater potential for non-invasive continuous monitoring solutions. Researchers around the globe are trialling the combination of ML models with actigraphic activity monitors to improve delirium prediction performance, with a specific focus on the insights gained from night-time activity data.
AI provides an alternative approach using natural language processing (NLP) to enhance the accuracy of delirium detection. The NLP approach extracts relevant words from the clinical narrative evident in nursing documentation, designed to improve diagnostic precision by identifing delirium symptoms from words that may be overlooked during routine evaluations (Wang et al. 2022).
AI tools have the potential to facilitate early management of delirium. A new AI-AntiDelirium platform assists nurses in the real-time monitoring of vital signs, evaluating risk factors, providing timely alerts and developing personalised care plans. There is emerging evidence to suggest that the AI-AntiDelirium system enhances nurses' adherence to delirium prevention guidelines.
The numerous empirical studies, published in this journal, and beyond, provide evidence about the nursing knowledge and skills needed to deliver evidence-based delirium care. However, for several years this evidence has not translated into clinical practice. Organisational systems and clinical environments often hinder nurses from providing optimal delirium care. There is also evidence that health service managers react to problems like delirium with short-term solutions rather than investing in long-term solutions, for example, supporting professional development opportunities that enable nurses to transform their workplace and address clinical problems such as delirium mismanagement.
As a reminder, this editorial is a call to action. As nurses we must commit and be change agents, promoting and modelling knowledge translation activities that result in reducing the incidence and prevalence of delirium. We understand that healthcare organisations service and respond to the needs of their communities and that, globally, many healthcare systems are resource ‘poor’. As a discipline, we therefore have an opportunity to lead the transformation of delirium care. Firstly, nurses should demand professional development opportunities with a focus on using resource efficient nonpharmacological nursing interventions. Secondly, nurses need to be knowledgeable about the role and use of AI and ML as mechanisms that support delirium decision making. Finally, adoption of comprehensive bundled strategies like the ABCDEF bundle in the ICU and the Age-Friendly Health Systems framework, incorporating the 4Ms (what matters, medication, mentation, and mobility), is crutial for improving health outcomes and effectively reduce delirium incidence and prevalence (Kwak et al. 2023).
V. Traynor: conceptualisation, project administration, writing of the manuscript, editing of the manuscript. S. Neville: conceptualisation, project administration, writing of the manuscript, editing of the manuscript. M. Hayter: review and editing of the manuscript. All other authors: writing of the manuscript.
L.M. Boehm is receiving funding from the National Institutes of Health National Institute on Aging. The other authors declare no conflicts of interest.
2025年3月12日为世界意识谵妄日。这个重要的年度活动提醒我们,谵妄是一种经常被忽视但可以治疗的健康问题。在全球范围内,谵妄对数百万人,特别是老年人的福祉产生了严重的负面影响。这一活动的目的是提高人们对谵妄的认识,以及它对谵妄患者、其家人、照顾者和重要他人以及卫生系统和卫生专业人员造成的广泛影响。护士是与卫生服务的消费者、他们的家人和重要的其他人相处时间最多的卫生专业群体。我们以采取整体方法提供保健服务而感到自豪。这些服务包括但不限于治疗沟通、对保健服务消费者的社会文化理解,以及利用为评估和临床决策活动提供信息的循证实践。为什么尽管它很普遍,但谵妄仍然没有得到诊断,而且经常管理不善?护士是改善谵妄结果不可或缺的一部分,然而,即使有超过30年的经验证据,谵妄的景观仍然没有改变。这篇社论提醒护士,精神错乱并不是年老和身体不适的必然结果。它是可以预防的,早期发现和干预会对人们的健康和福祉产生积极影响。我们利用世界意识谵妄日作为“行动呼吁”,敦促护士承诺结束30年来的无所作为。了解过去对于预测未来至关重要。几年来,该杂志发表了一些基于经验的谵妄手稿,每个提供有价值的见解,指导护士的评估和决策。这些手稿促进了谵妄护理的最佳实践,本应改善患者的预后,使患者能够以最佳的健康状态返回家中。一些更重要的贡献与重症监护获得性谵妄有关,包括发现谵妄患者的事实回忆明显减少,以及鼓励护士为人们填补“缺失的空白”,以及使用身体约束如何显著增加谵妄的发生率。然而,在所有情况下,谵妄的潜在长期影响都不应被低估,因为谵妄会增加一个人的死亡风险。对谵妄患者进行护理被认为是一种负担也就不足为奇了,特别是当患者无法合作且难以提供护理时。护士应该知道,在评估行为变化时保持警惕,比如定向障碍和精神运动活动减少,可以作为谵妄的早期预警信号。有证据表明,提高知识和临床评估技能的获得,以及使护士能够实施非药物干预,如及时拔除导尿管、管理疼痛和减少使用身体约束,将减少谵妄。重症监护病房(ICU)谵妄的关注是有理由的,因为在这种情况下谵妄的患病率很高。虽然危险因素有充分的记录,包括年龄较大、疾病严重程度和疼痛评分较高、血尿素水平升高以及对机械通气、镇静和身体约束的需求增加,但需要进一步的工作来确保早期发现和预防ICU谵妄的重大不良后果(Ho et al. 2023)。ICU的管理策略被记录,最有效的是关注预防和早期发现,采用ABCDEF包,定期评估疼痛和意识水平,促进早期活动和让家庭成员重新定位患者。使用经过验证的CAM-ICU-7、ICDSC和DRS-R98工具可以捕获ICU中谵妄的严重程度。也有重要的证据表明非药物干预的有效性,如重新定位,认知刺激和最小化环境压力,如噪音和灯光。毫不奇怪,多组分干预是最有效的非药物策略(Chen et al. 2022)。护士应带头实施非药物干预措施,预防和治疗谵妄。然而,有证据表明情况并非如此,谵妄的患病率仍然高得令人无法接受。如今,数字技术已成为医疗保健用语的一部分,护士有机会在谵妄护理中发挥领导作用。谵妄的检测被描述为主观的,需要床边工作量的努力,并导致治疗延误。此外,由于谵妄有突然发作和波动的表现,检测可能具有挑战性。 人工智能(AI)与护理实践的整合有可能增强谵妄的检测和护理。机器学习(ML)算法已被证明是有效的谵妄预测。一项荟萃分析发现,ML在预测谵妄方面表现出色,总敏感性为0.85,特异性为0.80 (Xie et al. 2022)。将机器学习算法与可穿戴技术相结合,显示出非侵入性连续监测解决方案的更大潜力。世界各地的研究人员正在尝试将ML模型与活动监测仪相结合,以提高谵妄预测的性能,并特别关注从夜间活动数据中获得的见解。人工智能提供了一种使用自然语言处理(NLP)的替代方法来提高谵妄检测的准确性。NLP方法从护理文献中明显的临床叙述中提取相关词汇,旨在通过从日常评估中可能被忽视的词汇中识别谵妄症状来提高诊断精度(Wang et al. 2022)。人工智能工具有可能促进谵妄的早期管理。新的AI-AntiDelirium平台可帮助护士实时监测生命体征,评估风险因素,提供及时警报并制定个性化护理计划。有新的证据表明,AI-AntiDelirium系统可以提高护士对谵妄预防指南的依从性。大量的实证研究,发表在这个杂志上,并超越,提供护理知识和技能所需的证据,以提供证据为基础的谵妄护理。然而,几年来,这一证据并没有转化为临床实践。组织系统和临床环境往往阻碍护士提供最佳的谵妄护理。还有证据表明,卫生服务管理者对谵妄等问题的反应是短期解决方案,而不是投资于长期解决方案,例如,支持专业发展机会,使护士能够改变工作场所,解决谵妄管理不善等临床问题。作为一个提醒,这篇社论是一个行动的呼吁。作为护士,我们必须承诺并成为变革推动者,促进和模拟知识转化活动,从而减少谵妄的发病率和患病率。我们知道,医疗机构服务和响应他们社区的需求,而在全球范围内,许多医疗系统资源“贫乏”。因此,作为一门学科,我们有机会引领精神错乱护理的变革。首先,护士应该要求专业发展机会,重点是使用资源高效的非药物护理干预措施。其次,护士需要了解人工智能和机器学习作为支持谵妄决策的机制的作用和使用。最后,在ICU和老年友好型卫生系统框架中采用综合捆绑策略,如ABCDEF捆绑,包括4Ms(重要的,药物,心理状态和流动性),对于改善健康结果和有效降低谵妄的发病率和患病率至关重要(Kwak等人,2023)。特雷纳:构思,项目管理,撰写手稿,编辑手稿。内维尔:构思、项目管理、撰写稿件、编辑稿件。海特:审阅和编辑手稿。所有其他作者:撰写原稿。Boehm正在接受美国国立卫生研究院国家老龄研究所的资助。其他作者声明没有利益冲突。
期刊介绍:
The Journal of Clinical Nursing (JCN) is an international, peer reviewed, scientific journal that seeks to promote the development and exchange of knowledge that is directly relevant to all spheres of nursing practice. The primary aim is to promote a high standard of clinically related scholarship which advances and supports the practice and discipline of nursing. The Journal also aims to promote the international exchange of ideas and experience that draws from the different cultures in which practice takes place. Further, JCN seeks to enrich insight into clinical need and the implications for nursing intervention and models of service delivery. Emphasis is placed on promoting critical debate on the art and science of nursing practice.
JCN is essential reading for anyone involved in nursing practice, whether clinicians, researchers, educators, managers, policy makers, or students. The development of clinical practice and the changing patterns of inter-professional working are also central to JCN''s scope of interest. Contributions are welcomed from other health professionals on issues that have a direct impact on nursing practice.
We publish high quality papers from across the methodological spectrum that make an important and novel contribution to the field of clinical nursing (regardless of where care is provided), and which demonstrate clinical application and international relevance.