Artificial Intelligence (AI)PEACE-AINCT07027618
AI-Driven Personalization of End-of-Life Care for the Elderly
A study testing AI-based Software for Personalized End-of-Life Care in people with Artificial Intelligence (AI) and Dementia, run by Baqiyatallah Medical Sciences University.
Trial 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. Read more about this study
- Who is it for?
- Ages 60 years and older
- Conditions the study is for
- Artificial Intelligence (AI), Dementia, Palliative Care
- What is being tested?
- AI-based Software for Personalized End-of-Life Care
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 140 participants
- Where
- No sites listed yet
- Study dates
- Jul 2025to Sep 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 60 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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)
Who cannot join
- 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
About this study
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"
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.
Read the 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.
- Conditions
- Artificial Intelligence (AI), Dementia, Palliative Care
- Being tested
- AI-based Software for Personalized End-of-Life Care
- Medical subject headings
- Dementia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-based Software for Personalized End-of-Life CareBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| AI-based Personalized End-of-Life Care | Experimental | 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. Receives: Behavioral: AI-based Software for Personalized End-of-Life Care |
| Standard End-of-Life Care | Active comparator | 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. Receives: Behavioral: AI-based Software for Personalized End-of-Life Care |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in Quality of Life Score
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.
Measured: Up to 3 months after intervention start
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Jun 2025
- Study startJul 2025 (estimated)
- Primary completionAug 2026 (estimated)
- Study completionSep 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Artificial Intelligence (AI)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- 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.
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 140 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Baqiyatallah Medical Sciences University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Amir Vahedian-Azimi, Baqiyatallah Medical Sciences University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07027618
- Sponsor's protocol ID
- BUMS
- Acronym
- PEACE-AI
- Status last verified
- Jun 2025
- First submitted
- 11 Jun 2025
- Last updated
- 18 Jun 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 18 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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"
- ClinicalTrials.gov ID
- NCT07027618
- Acronym / sponsor ID
- PEACE-AI / BUMS
- Conditions
- Artificial Intelligence (AI), Dementia, Palliative Care
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 140 participants (estimated)
- Lead sponsor
- Baqiyatallah Medical Sciences UniversityUniversity, hospital or other
- Study start
- Jul 2025 (estimated)
- Primary completion
- Aug 2026 (estimated)
- Study completion
- Sep 2026 (estimated)
- First posted
- 18 Jun 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- 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.
| Arm | Type | Receives |
|---|---|---|
| AI-based Personalized End-of-Life Care | Experimental | Behavioral: AI-based Software for Personalized End-of-Life CareParticipants 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. |
| Standard End-of-Life Care | Active comparator | Behavioral: AI-based Software for Personalized End-of-Life CareParticipants 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. |
Who may qualify
- Ages
- 60 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- 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)
Key exclusion criteria (4 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-based Software for Personalized End-of-Life CareThis 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. | Behavioural | AI-based Personalized End-of-Life Care, Standard End-of-Life Care |
Primary outcome
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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 Jun 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
A study testing AI-based Software for Personalized End-of-Life Care in people with Artificial Intelligence (AI) and Dementia, run by Baqiyatallah Medical Sciences University.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 18 Jun 2025. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in Quality of Life Score (time frame: Up to 3 months after intervention start). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 18 Jun 2025.