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Assessing Clinical Impact of AI for Iron Deficiency

NCT07394088 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 2196

Last updated 2026-02-11

No results posted yet for this study

Summary

The goal of this clinical trial is to evaluate whether an AI-based risk notification system integrated into routine clinical care can improve the clinical detection of iron deficiency in adult patients attending Internal Medicine, Family Medicine, and Hematology/Oncology clinics at China Medical University Hospital in Taiwan.

The main questions this study aims to answer are:

1. Does displaying AI-generated iron deficiency risk classification to physicians increase the overall detection rate of iron deficiency at the population level?
2. Does the AI-based risk notification influence physicians' diagnostic behavior by increasing the rate at which ferritin testing is ordered specifically for suspected iron deficiency?
3. Among ferritin tests ordered for suspected iron deficiency, does the diagnostic yield (positivity rate) remain appropriate, reflecting efficient use of testing resources?
4. Are the effects of the AI-assisted intervention consistent among patients with anemia and without anemia?

Comparison Groups Researchers will compare clinical encounters in which physicians receive AI-generated iron deficiency risk information (the Prompt Group) with encounters in which physicians receive standard laboratory results without AI risk display (the Control Group). The comparison focuses on differences in iron deficiency detection, ferritin ordering behavior for suspected iron deficiency, and diagnostic yield.

What Participants Will Experience

1. No Additional Procedures:

As this is a pragmatic study embedded in routine clinical care, participants will not undergo any additional blood draws, invasive procedures, or clinic visits beyond standard care.
2. Routine Care Only:

Patients attend their scheduled outpatient visits and receive complete blood count (CBC) testing as ordered by their treating physician, independent of study participation.
3. Background Data Integration:

The AI system operates within the hospital's information system, analyzing routinely collected CBC data after results become available. No additional data entry or action is required from patients.
4. Physician Autonomy Preserved:

The AI provides a non-mandatory risk classification as decision support. For patients identified as high risk, the system may display an informational prompt suggesting consideration of iron-related testing if no recent testing is found. All diagnostic and management decisions remain entirely at the discretion of the treating physician.

Conditions

Interventions

OTHER

AI Risk Display

Participants in this group receive AI-generated information showing their high or low risk of iron deficiency to assist clinical decision-making. For participants identified as high-risk, the system automatically checks for iron-related tests performed in the past 30 days and alerts the physician if no recent tests are found. The final decision to order any tests remains with the physician.

Sponsors & Collaborators

  • China Medical University Hospital

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
DOUBLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-03-31
Primary Completion
2026-08-31
Completion
2027-01-31

Countries

  • Taiwan

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07394088 on ClinicalTrials.gov