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AI Assessment and Prediction Models for Geriatric Trauma

NCT ID: NCT05176054

Last Updated: 2022-12-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

418 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-08-01

Study Completion Date

2024-10-31

Brief Summary

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To fill up the research gaps and build up a healthcare service model for geriatric trauma patients, this two-stage study aims to (a) develop geriatric trauma Artificial Intelligence (AI) prediction models by comparing the outcomes from clinical assessment and AI joint images; and (b) examine the long-term effects of an innovative health service program in geriatric trauma patients.

Detailed Description

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Background: About 40% trauma patients will be over age 65 years by 2050, thus geriatric trauma constitutes an increasingly recognized problem that should be concerned. However, little is known about complicated causes of injury and long-term outcomes in older injured patients. Previous study strategies to promote health outcomes for geriatric trauma still are inconclusive. Due to the limited healthcare resources and workforce, health service for geriatric trauma care should be refined in the new era.

Expected outcomes/impacts: This study attempts to build up a modern healthcare model that may influence geriatric trauma care as well geriatric assessment. The AI prediction model can be used to quickly assess "degree of balance" for geriatric trauma patients. This study will involve a nursing student and healthcare professionals, and help them to learn how AI connects to geriatric trauma care. This would be an opportunity to cultivate potential experts for AI and healthcare. Last, the outcomes are highly associated with the government's policies related to smart health, smart healthcare, and long-term care workforce.

Conditions

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Trauma Aging

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Blinding Strategy

NONE

Study Groups

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Experimental group

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Group Type EXPERIMENTAL

Health service program

Intervention Type OTHER

The program will be implemented into the experimental group, the program has been designed as a three-stage model including hospital management, transition care, and post-acute stage care.

Contrast group

The contrast group will be receiving the routine care only.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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Health service program

The program will be implemented into the experimental group, the program has been designed as a three-stage model including hospital management, transition care, and post-acute stage care.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* admitted to the hospital due to injury first time
* able to communicate in Mandarin
* agree to participate in this study from hospital discharge to one month after hospital discharge
* patients and their primary caregivers have smart mobile phones and internet access available
* can move independently before trauma

Exclusion Criteria

* not frequent user for smart phones
* severe cognitive impairment
* victims of hangings and poisonings
Minimum Eligible Age

65 Years

Maximum Eligible Age

74 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Kaohsiung Medical University Chung-Ho Memorial Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Bih-O Lee, PHD

Role: PRINCIPAL_INVESTIGATOR

Kaohsiung Medical University

Locations

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Kaohsiung Medical University

Kaohsiung City, , Taiwan

Site Status RECRUITING

Countries

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Taiwan

Central Contacts

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Bih-O Lee, PHD

Role: CONTACT

Phone: 886-7-312-1101

Email: [email protected]

Facility Contacts

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Bih-O Lee, PHD

Role: primary

Other Identifiers

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KMUHIRB- F(II)-20210057

Identifier Type: -

Identifier Source: org_study_id