AI Assessment and Prediction Models for Geriatric Trauma

Kaohsiung Medical University

Status: Enrolling

Conditions: Aging; Trauma

Treatments: Other: Health service program

Study type: Interventional

Funder types: Other

Identifiers

NCT05176054

KMUHIRB- F(II)-20210057

Details and patient eligibility

About

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.

Full description

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.

Enrollment: 418 estimated patients

Sex: All

Ages: 65 to 74 years old

Volunteers: No Healthy Volunteers

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

Trial design

Primary purpose: Health Services Research

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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418 participants in 2 patient groups

Experimental group

Experimental group

Description:

Researchers will conduct the health service program for the experimental group.

Treatment:

Other: Health service program

Contrast group

No Intervention group

Description:

The contrast group will be receiving the routine care only.