AI-Assisted Antidiabetic Drug Consultation System for Glycemic Control in Type 2 Diabetes Patients Managed by Non-Specialist Physicians

Sponsor
National Taiwan University Hospital
Study ID
NCT07684690
Status
Not Yet Recruiting

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Conditions

  • Type 2 Diabetes Mellitus (T2DM)

Eligibility Criteria

Sex
ALL
Age
19 Years - 80 Years
Healthy Volunteers
Not accepted

Interventions

  • AI-assisted antidiabetic drug consultation system — DEVICE
    A machine-learning based clinical decision support software that provides non-specialist physicians with real-time, interactive antidiabetic prescribing recommendations, a drug-prioritization order, and outcome predictions (e.g., the predicted likelihood of reaching glycemic targets and responder/non-responder status for individual drugs). The system was developed and validated using the NTUH integrated medical database platform. It provides advisory recommendations only; the treating physician retains full control over the final prescribing decision. All recommended medications are approved in Taiwan and within approved dose ranges.
  • Manual antidiabetic prescribing (without AI) — OTHER
    Antidiabetic medications prescribed manually by non-specialist physicians according to usual clinical practice, without using the AI consultation system. All medications are approved in Taiwan and prescribed within approved dose ranges.

Study Details

This study tests whether an artificial intelligence (AI) tool can help doctors choose better diabetes medicines for their patients. Type 2 diabetes is very common, but there are far more patients than diabetes specialists, so many patients are treated by doctors who are not diabetes specialists. The researchers built an AI consultation system that gives doctors real-time suggestions and predictions about diabetes medicines while they are prescribing. The doctor always makes the final decision. In this trial, patients with type 2 diabetes whose blood sugar is not well controlled will be placed by chance (randomly) into one of two groups. In one group, the doctor uses the AI system when deciding on diabetes medicines. In the other group, the doctor prescribes as usual, without the AI system. All medicines used are already approved in Taiwan and given at approved doses. The study follows each patient for 12 months, with check-ups at the start and at 3, 6, 9, and 12 months. The main goal is to compare how much the patients' long-term blood sugar level (HbA1c) improves between the two groups after one year. The researchers also look at how many patients reach their blood sugar target, how often low blood sugar happens, and whether any side effects occur. The aim is to find out whether using the AI tool leads to better blood sugar control.

Key Dates

First listed
Jul 6, 2026
Start date
Jul 31, 2026
Status verified
Jun 2026
Primary completion
Nov 30, 2027
Completion
Nov 30, 2027

Study Design

Enrollment
400 participants (estimated)
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT

Arms

  • Experimental: AI-Assisted Prescribing
    Non-specialist physicians prescribe antidiabetic medications after consulting the AI-assisted antidiabetic drug consultation system. The system provides real-time, interactive prescribing recommendations, a drug-prioritization order, and outcome predictions. The physician retains full control over the final prescribing decision. All medications are approved in Taiwan and prescribed within approved dose ranges. Patients are followed for 12 months.
  • Active Comparator: Manual Prescribing (Non-AI)
    Non-specialist physicians prescribe antidiabetic medications manually according to usual clinical practice, without using the AI consultation system. All medications are approved in Taiwan and prescribed within approved dose ranges. Patients are followed for 12 months.

Primary Outcome Measure

Change in HbA1c from baseline to 12 months [ Time Frame: Baseline and 12 months ]

Central Contacts

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