Medical Information Only. Always consult your healthcare provider before enrolling in any clinical trial.

NCT06995378 · ClinicalTrials.gov registry record · NA

Study EHR Risk Stratification Tools

A NA study, sponsored by University of California, Los Angeles.

Recruiting
Registry status
NA
Development phase
1,200
Enrollment target

NCT06995378 is a NA study that is actively recruiting participants, run by University of California, Los Angeles. The registered enrollment target is 1,200 participants.

View on ClinicalTrials.gov ↗

View your shortlist →

The verdict

NCT06995378, a NA study, is actively recruiting participants, sponsored by University of California, Los Angeles.

RECRUITING
Registry status
NA
Development phase
1,200 participants
Enrollment target

Study Summary

This study evaluates whether adding machine learning-based risk information to electronic health record (EHR) lab result messages helps older adults better understand their risk of developing diabetes and influences their emotional responses, quality of life, and healthcare use. Eligible participants are adults aged 65 years and older with a UCLA primary care provider and a hemoglobin A1c level in the range (5.7-6.0%). Participants are identified automatically at the time their lab results are processed and are randomly assigned to receive either standard lab result messages or modified messages that include a "very low risk" label generated by a machine learning model. All participants who are randomized are invited to complete two surveys: one shortly after their lab result is posted in MyChart and a follow-up survey approximately 30 days later. The study also uses de-identified EHR data to examine patterns of healthcare utilization and progression to diabetes. Provider comments related to lab result messaging will be analyzed to explore differences in response patterns between the two groups.

Interventions

  • DEVICE Hemoglobin A1c Lab Result Communication Tool

Trial Details

FieldValue
Enrollment Target 1,200 participants
Start Date 2026-05-27
Est. Completion 2029-09
Phase NA

What the Registry Record Tells You About NCT06995378

The ClinicalTrials.gov registry entry for NCT06995378 describes a study currently listed as recruiting, categorized as NA. The registered enrollment target is 1,200 participants, a figure that helps gauge the scale of data the investigators plan to collect. The listed sponsor is University of California, Los Angeles, which has 897 total studies on file at ClinicalTrials.gov.

The record links to 0 conditions, and to 1 intervention - of which Hemoglobin A1c Lab Result Communication Tool is the first listed.

NCT06995378 reports 0 study locations.

Frequently Asked Questions

What is clinical trial NCT06995378 about?

NCT06995378 is a clinical study titled "Study EHR Risk Stratification Tools". This study evaluates whether adding machine learning-based risk information to electronic health record (EHR) lab result messages helps older adults better understand their risk of developing diabetes and influences their emotional responses, quality of life, and healthcare use. Eligible participan...

What is the current status of trial NCT06995378?

This trial is currently recruiting. It is a NA study. The enrollment target is 1,200 participants. The study started on 2026-05-27. Estimated completion is 2029-09.

What interventions are being tested in trial NCT06995378?

The interventions under investigation include: Hemoglobin A1c Lab Result Communication Tool (DEVICE).

Who is sponsoring clinical trial NCT06995378?

This trial is sponsored by University of California, Los Angeles, which has 897 total clinical trials registered on ClinicalTrials.gov.

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainTrial Editorial

Every figure on PlainTrial is rendered directly from the ClinicalTrials.gov registry, no number is typed in by an editor. This page mirrors this trial's own ClinicalTrials.gov registry record, live from the dataset. See our editorial standards & corrections policy, the methodology behind these numbers, or report a data error.