AI-Driven Personalization of End-of-Life Care for the Elderly (PEACE-AI)

June 11, 2025 updated by: Amir Vahedian-Azimi, Baqiyatallah Medical Sciences University

"Evaluating the Effectiveness of an AI-Based Software in Personalizing High-Quality End-of-Life Care for the Elderly: A Randomized Controlled Clinical Trial"

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.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

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.

Study Type

Interventional

Enrollment (Estimated)

140

Phase

  • Not Applicable

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Prevention
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: AI-based Personalized End-of-Life Care
Participants in this group will receive personalized end-of-life care supported by an AI-based software. The software monitors vital signs and behavior through wearable sensors, provides intelligent medication reminders, issues preventive alerts to the care team, delivers personalized care plans, and offers psychological and social support through communication features.
Behavioral: AI-based Software for Personalized End-of-Life Care
This intervention involves the use of an AI-powered software system designed to personalize end-of-life care for elderly patients. The software continuously monitors vital signs and behavior through wearable sensors, sends smart medication reminders, issues preventive alerts to care providers, delivers customized care plans, and provides psychological and social support through communication features.
Active Comparator: Standard End-of-Life Care
Participants in this group will receive standard end-of-life care without the use of the AI-based software. Care is provided according to usual clinical practices and guidelines.
Behavioral: AI-based Software for Personalized End-of-Life Care
This intervention involves the use of an AI-powered software system designed to personalize end-of-life care for elderly patients. The software continuously monitors vital signs and behavior through wearable sensors, sends smart medication reminders, issues preventive alerts to care providers, delivers customized care plans, and provides psychological and social support through communication features.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Change in Quality of Life Score
Time Frame: Up to 3 months after intervention start
Assessed using a validated instrument such as the Quality of Life at the End of Life (QUAL-E) scale to measure overall well-being, comfort, and satisfaction with care during end-of-life.
Up to 3 months after intervention start

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Baqiyatallah Medical Sciences University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

July 1, 2025

Primary Completion (Estimated)

August 1, 2026

Study Completion (Estimated)

September 1, 2026

Study Registration Dates

First Submitted

June 11, 2025

First Submitted That Met QC Criteria

June 11, 2025

First Posted (Actual)

June 18, 2025

Study Record Updates

Last Update Posted (Actual)

June 18, 2025

Last Update Submitted That Met QC Criteria

June 11, 2025

Last Verified

June 1, 2025

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • BUMS

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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