Lindroth, Heidi

Introduction: Delirium is a common, severe neuropsychiatric syndrome in hospitalised older adults. We evaluated use of validated delirium assessment tools, adherence to national guidelines and prevalence and management of delirium across Scotland, identifying barriers to effective care. Methods: Secondary analysis of national survey data, collected by participating clinicians on World Delirium Awareness Day (15 March 2023). Results: Among 120 responses (3,257 patients), the 4AT was the most frequently used assessment tool (75%), while 14% of units reported using clinical judgement alone. The delirium assessment rate was 74%, with a prevalence of 22% at 8 am. Management protocols varied, with frequent routine non-pharmacological interventions including pain management (88%), hydration (87%) and open family visiting (80%). Barriers to delirium care included insufficient staffing and training. Conclusion: While many hospital settings follow national delirium guidelines, some still rely on clinical judgement for assessment, with variability in management protocols and practices. We have highlighted key barriers to effective delirium care in Scotland.

Abstract Background Delirium, an acute brain dysfunction, is proposed to be highly prevalent in clinical care and shown to significantly increase the risk of mortality and dementia. Objectives To report on the global prevalence of clinically documented delirium and delirium-related clinical practices in wards caring for paediatric and adult patients in healthcare facilities. Design A prospective, cross-sectional, 39-question survey completed on World Delirium Awareness Day, 15 March 2023. Participants Clinicians or researchers with access to clinical data. Main Outcome and Measure The primary outcome was the prevalence of clinically documented delirium at 8:00 a.m. (4 h) and 8:00 p.m. (±4 h). Secondary outcomes included delirium-related care practices and barriers to use. Descriptive statistics were calculated and multilevel modelling was completed. Results 1664 wards submitted surveys from 44 countries, reporting on delirium assessments at 8:00 a.m. (n = 36 048) and 8:00 p.m. (n = 32 867); 61% reported use of validated delirium assessment tools. At 8:00 a.m., 18% (n = 2788/15 458) and at 8:00 p.m., 17.7% (n = 2454/13 860) were delirium positive. Top prevention measures were pain management (86.7%), mobilisation (81.4%) and adequate fluids (80.4%). Frequently reported pharmacologic interventions were benzodiazepines (52.7%) and haloperidol (46.2%). Top barriers included the shortage of staff (54.3%), lack of time to educate staff (48.6%) and missing knowledge about delirium (38%). Conclusion and Relevance In this study, approximately one out of five patients were reported as delirious. The reported high use of benzodiazepines needs further evaluation as it is not aligned with best-practice recommendations. Findings provide a benchmark for future quality improvement projects and research.

The early detection of the acute deterioration of escalating illness severity is crucial for effective patient management and can significantly impact patient outcomes. Ambient sensing technology, such as computer vision, may provide real-time information that could impact early recognition and response. This study aimed to develop a computer vision model to quantify the number and type (clinician vs. visitor) of people in an intensive care unit (ICU) room, study the trajectory of their movement, and preliminarily explore its relationship with delirium as a marker of illness severity. To quantify the number of people present, we implemented a counting-by-detection supervised strategy using images from ICU rooms. This was accomplished through developing three methods: single-frame, multi-frame, and tracking-to-count. We then explored how the type of person and distribution in the room corresponded to the presence of delirium. Our designed pipeline was tested with a different set of detection models. We report model performance statistics and preliminary insights into the relationship between the number and type of persons in the ICU room and delirium. We evaluated our method and compared it with other approaches, including density estimation, counting by detection, regression methods, and their adaptability to ICU environments.

AbstractPatients in delirium require trustful communication and re‐orientation. We developed a flyer with positive, re‐orientating suggestions for families of delirious patients in intensive care units. Suggestions include creating a safe environment, interpreting unusual behaviours positively and fostering mental resilience. Additionally, families are encouraged to prioritize their own well‐being, recognizing their crucial role in supporting their loved ones. This flyer offers practical strategies across four key areas: ensuring security and orientation, reframing noises and body experiences, managing agitation and reshaping perceptions. By equipping families with knowledge and tools, this resource aims to promote understanding, resilience and strength to humanize delirium care.

Abstract Background Delirium is a common complication of older people in hospitals, rehabilitation and long-term facilities. Objective To assess the worldwide use of validated delirium assessment tools and the presence of delirium management protocols. Design Secondary analysis of a worldwide one-day point prevalence study on World Delirium Awareness Day, 15 March 2023. Setting Cross-sectional online survey including hospitals, rehabilitation and long-term facilities. Methods Participating clinicians reported data on delirium, the presence of protocols, delirium assessments, delirium-awareness interventions, non-pharmacological and pharmacological interventions, and ward/unit-specific barriers. Results Data from 44 countries, 1664 wards/units and 36 048 patients were analysed. Validated delirium assessments were used in 66.7% (n = 1110) of wards/units, 18.6% (n = 310) used personal judgement or no assessment, and 10% (n = 166) used other assessment methods. A delirium management protocol was reported in 66.8% (n = 1094) of wards/units. The presence of protocols for delirium management varied across continents, ranging from 21.6% (on 21/97 wards/units) in Africa to 90.4% (235/260) in Australia, similar to the use of validated delirium assessments with 29.6% (29/98) in Africa to 93.5% (116/124) in North America. Wards/units with a delirium management protocol [n = 1094/1664, 66.8%] were more likely to use a validated delirium test than those without a protocol [odds ratio 6.97 (95% confidence interval 5.289–9.185)]. The presence of a delirium protocol increased the chances for valid delirium assessment and, likely, evidence-based interventions. Conclusion Wards/units that reported the presence of delirium management protocols had a higher probability of using validated delirium assessments tools to assess for delirium.

Computer vision (CV), a type of artificial intelligence (AI) that uses digital videos or a sequence of images to recognize content, has been used extensively across industries in recent years. However, in the healthcare industry, its applications are limited by factors like privacy, safety, and ethical concerns. Despite this, CV has the potential to improve patient monitoring, and system efficiencies, while reducing workload. In contrast to previous reviews, we focus on the end-user applications of CV. First, we briefly review and categorize CV applications in other industries (job enhancement, surveillance and monitoring, automation, and augmented reality). We then review the developments of CV in the hospital setting, outpatient, and community settings. The recent advances in monitoring delirium, pain and sedation, patient deterioration, mechanical ventilation, mobility, patient safety, surgical applications, quantification of workload in the hospital, and monitoring for patient events outside the hospital are highlighted. To identify opportunities for future applications, we also completed journey mapping at different system levels. Lastly, we discuss the privacy, safety, and ethical considerations associated with CV and outline processes in algorithm development and testing that limit CV expansion in healthcare. This comprehensive review highlights CV applications and ideas for its expanded use in healthcare.