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Assessing Clinical Impact of AI for Iron Deficiency

RecruitingNAAges 18 Years - anyAllChina Medical University Hospital
NCT07394088 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

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?

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📋 Eligibility rules (as published)
Inclusion Criteria: 1. Adults aged 18 years or older. 2. Patients attending outpatient clinics of participating departments including 2.1. Internal Medicine, 2.2 Family Medicine 2.3. Hematology/Oncology 3. Completion of a routine complete blood count (CBC) as part of usual clinical care during the outpatient encounter. 4. Availability of the CBC report in the institutional laboratory information system, allowing sufficient data for analysis. Exclusion Criteria: 1. Encounters with missing or incomplete key identifiers (e.g., patient identification number, ) that prevent determination of exposure status (AI information displayed vs not displayed) or assessment of outcomes within the defined follow-up period. 2. Encounters without a valid department code required by the information system to trigger the randomization mechanism and AI risk display. 3. Encounters with incomplete or missing laboratory data required to activate the AI system. 4. Repeated CBC encounters from the same patient during the study period, if applicable; only the first eligible encounter will be included to avoid duplication.
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What it tests

  • AI Risk Display
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Where

1 site
China Medical University Hospital
Taichung, Taiwan
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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