Clinical trial NCT06846229: AI-Assisted Medical Decision-Making
Official title: A Cohort Study to Evaluate an Artificial Intelligence Model for Assisting Medical Decision-Making Using Real-Time Hospital-Wide Electronic Health Record Data
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Real-world Study
Keywords: diagnosis
prediction
AI
outcome
Lead sponsor: The Eye Hospital of Wenzhou Medical University
Sponsor class: OTHER
First posted: 2025-02-26
Enrollment: 50000000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: This study includes all patients admitted to any hospital department, with real-time electronic health record data (e.g., labs, vital signs, history, imaging). Participants must consent to data collection.

Brief summary: The study builds and applies an AI model to help doctors predict patient diagnoses and outcomes, such as survival or hospital stay. Real-time, multimodal data (labs, vital signs, history, imaging) from hospital records will be used. Patients will be tracked to compare the AI's performance with standard care. The goal is to improve diagnosis and treatment accuracy in a real-world, prospective study.

Detailed description: This study aims to build and apply an artificial intelligence (AI) model to assist doctors in predicting patient diagnoses and outcomes, such as survival or hospital stay length. Patients will be enrolled across the hospital, and real-time, multimodal health data-including lab results, vital signs, medical history, and imaging-from electronic health records will be used. The study will follow participants to evaluate the AI model's performance against standard practice. The goal is to improve the accuracy and speed of diagnoses and treatments, enhancing patient care. This prospective study tests the model in real-world hospital settings.

Eligibility criteria: Inclusion Criteria:

1. Patients admitted to any department of the hospital (e.g., ICU, general wards, emergency, outpatient services) during the study period.
2. Patients with available real-time electronic health record (EHR) data, including at least two of the following: laboratory results, vital signs, medical history, and imaging data.

Exclusion Criteria:

Patients currently enrolled in another clinical trial that could interfere with data collection or outcomes of this study.

Primary outcomes:
measure: Area Under the Curve (AUC)
timeFrame: 1 year
measure: Overall Hospital Resource Utilization Improvement
timeFrame: 1 year
measure: Population-Level Diagnostic Accuracy Enhancement
timeFrame: 1 year
measure: System-Wide Reduction in Adverse Event Rates
timeFrame: 1 year
Secondary outcomes:
measure: Overall Improvement in Hospital Patient Outcomes
timeFrame: 1 year
measure: Enhancement of Healthcare System Efficiency
timeFrame: 1 year
measure: Population Health Impact Score
timeFrame: 1 year
measure: Long-Term Public Health Benefit Index
timeFrame: 1 year
Other outcomes:
Locations:
city: Wenzhou
country: China
facility: First Affiliated Hospital of Wenzhou Medical University
state: Zhejiang
city: Wenzhou
country: China
facility: Second Affiliated Hospital of Wenzhou Medical University
state: Zhejiang
Study officials:
References: