Precision ICU Care: Evaluating an AI-Driven Nursing Decision Support System for Delirium Prevention

Efficacy of an Intelligent Computational Nursing Decision Support System in Precision Critical Care for Delirium Prevention: A Randomized Controlled Trial

Delirium affects up to 83% of mechanically ventilated patients in the Intensive Care Unit (ICU), often leading to longer hospital stays and long-term memory or cognitive problems. While standard care protocols (such as the ABCDEF bundle) exist, they are often difficult to implement fully due to their complexity and the heavy workload on nursing staff.

To address these challenges, this study introduces a 'Precision Nursing' approach by integrating Artificial Intelligence (AI) and Virtual Reality (VR). We will implement an AI-driven system to assist nurses in making personalized care decisions more efficiently. Additionally, interactive VR technology will be used to stimulate patients' cognitive function and encourage early mobility. Our goal is to reduce the clinical burden on healthcare providers while significantly improving recovery outcomes for ICU patients.

Delirium affects up to 83% of ventilated ICU patients, necessitating precise non-pharmacological interventions like the SCAN-D program, which aims to improve outcomes by integrating smart computing and virtual reality into nursing decisions. This three-year, assessor-blinded, parallel randomized controlled trial will enroll 188 patients, assigning them to either usual care or the SCAN-D group, where the latter receives personalized strategies based on machine learning risk weights, including family-supervised immersive VR exercise and cognitive training. Throughout their stay, patients will be monitored via shift-based assessments (ICDSC/RASS) and nightly sleep tracking using actigraphy combined with one-lead EEG, while long-term cognitive function and quality of life (EQ-5D-3L) will be evaluated at three and six months post-discharge. The primary outcomes are the incidence of delirium and delirium-free days within the first 28 days of ICU admission, measured using the ICU Delirium Screening Checklist. Secondary outcomes include sleep quality and quantity, functional status during the ICU stay, ICU length of stay, duration of mechanical ventilation, total hospital length of stay, ICU mortality rate, Sedative and Analgesic Loading, 90-day Mortality Post-discharge, cognitive function, and quality of life. Finally, the collected data will be analyzed using SPSS 22.0 through independent t-tests, Chi-square tests, and Generalized Estimating Equations (GEE) to determine the program's efficacy in reducing delirium incidence and enhancing overall patient recovery.

Inclusion Criteria:

• Patients aged 18 years
• High risk of developing delirium are defined as PRE-DELIRIC (PREdiction of DELIRium in ICu patients) with a score of ≥40%
• Sedation assessment form (Richmond Agitation-Sedation). Scale, RASS) is assessed as between +1 and -1
• Patient is clearly aware and able to communicate with Chinese and Taiwanese customers.

Exclusion Criteria:

• Those who have developed delirium before joining the study (assessed by the Intensive Care Delirium Screening Checklist (ICDSC) >4 points)
• Expected to stay in the ICU for less than 24 hours
• APACHE II score > 25 (meaning > 50% mortality)
• Delirium cannot be evaluated, such as those with severe acute brain injury, audio-visual impairment, speech problems, psychotic disorders, aphasia, or in the entire ICU During this period, patient remained comatose.