Clinical trial NCT07027618: AI-Driven Personalization of End-of-Life Care for the Elderly
Official title: "Evaluating the Effectiveness of an AI-Based Software in Personalizing High-Quality End-of-Life Care for the Elderly: A Randomized Controlled Clinical Trial"
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Artificial Intelligence (AI)
Dementia
Palliative Care
Lead sponsor: Baqiyatallah Medical Sciences University
Sponsor class: OTHER
First posted: 2025-06-18
Enrollment: 140
Sex: ALL
Minimum age (years): 60
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Participants will be randomly assigned to one of two parallel groups: an intervention group receiving AI-based palliative care through a personalized software system, and a control group receiving standard end-of-life care without the AI intervention. Randomization will be conducted using block randomization to ensure balance in baseline characteristics. Although the study is open-label, outcome assessors will be blinded to group assignments to minimize assessment bias.
Primary purpose: PREVENTION

Brief summary: This study aims to evaluate the effectiveness of an artificial intelligence (AI)-based software in personalizing high-quality end-of-life care for elderly patients. As the elderly population grows, providing tailored and quality care during the final stages of life becomes increasingly important. This AI software continuously monitors vital signs and behaviors through wearable sensors, offers smart medication reminders, alerts the care team to potential risks, and provides personalized care plans along with psychological and social support.

The study is designed as a randomized controlled trial comparing two groups: one receiving standard end-of-life care and the other using the AI software. Key outcomes include improving quality of life, reducing adverse events like falls and emergency hospitalizations, increasing patient and family satisfaction, improving medication management, and reducing caregiver burden. Data will be collected over six months to assess these effects. The results will help determine whether AI technology can enhance end-of-life care for seniors and support families and healthcare providers.

Detailed description: This section provides a comprehensive overview of the study design, objectives, population, interventions, and methods without repeating information already included in other sections of the record. It elaborates on the rationale for using AI-based software to personalize end-of-life care for elderly patients, details the randomized controlled trial setup, explains inclusion and exclusion criteria, intervention specifics, outcome measures, data collection methods, and planned statistical analyses. This description ensures a clear understanding of the study's scope and methodology.

Eligibility criteria: Inclusion Criteria:

Age ≥ 60 years

Clinical diagnosis of being in the end-of-life stage, based on criteria such as the Karnofsky Performance Scale or Palliative Performance Scale

Informed consent obtained from the participant or legal representative

Ability to use technology independently or with support provided by the research team

Access to necessary equipment for the intervention (e.g., wearable sensors, smartphone/tablet)

Exclusion Criteria:

Presence of severe cognitive impairment preventing software use

Voluntary withdrawal from the study at any stage

Critical medical deterioration or death during the study

Poor adherence or insufficient engagement with the intervention software in the intervention group

Primary outcomes:
measure: Change in Quality of Life Score
timeFrame: Up to 3 months after intervention start
Secondary outcomes:
Other outcomes:
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