Nurses Must Improve Delirium Care: A Call to Action

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. The authors have nothing to report. L.M. Boehm is receiving funding from the National Institutes of Health National Institute on Aging. The other authors declare no conflicts of interest. Data sharing is not applicable to this article, as no datasets were generated or analysed during the current study.