Study EHR Risk Stratification Tools

Part of paid clinical trials in Los Angeles, California.

Sponsor
University of California, Los Angeles
Study ID
NCT06995378
Status
Not Yet Recruiting

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Conditions

  • Health Communication
  • Patient Comprehension
  • Prediabetes

Eligibility Criteria

Sex
ALL
Age
65 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Hemoglobin A1c Lab Result Communication Tool — DEVICE
    A behavioral intervention delivered through a personalized Electronic Health Record (EHR)-integrated lab result communication tool designed to improve emotional and cognitive responses to lab results among adults aged 65+. The tool applies behavioral science principles such as risk personalization, simplified messaging, and visual framing to reduce patient anxiety, enhance understanding, and support informed decision-making.

Study Details

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.

Key Dates

Start date
Apr 30, 2026
Status verified
Apr 2026
Primary completion
Oct 31, 2026
Completion
Sep 30, 2029

Study Design

Enrollment
1,200 participants (estimated)
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH

Arms

  • Experimental: Personalized Lab Result Messaging
    Participants receive modified electronic health record (EHR) lab result communications in the patient portal (MyChart) and provider-facing EHR interface that include a qualitative "very low risk" label generated by a machine learning-based tool, along with brief explanatory text providing context about their current results and indicating a low level of concern at this time.
  • No Intervention: Standard Lab Result Messaging
    Participants receive standard electronic health record (EHR) lab result communications without any machine learning-generated risk labeling or explanatory text providing additional context about level of concern.

Primary Outcome Measure

Prediabetes- Related Healthcare Utilization [ Time Frame: 365 days after result ]

Central Contacts

Locations (1)

FacilityCityStateZIPSite coordinators
UCLA Health SystemLos AngelesCalifornia90049
Katelyn Assistant Clinical Research Coordinator
[email protected]
310-267-5250
Catherine Sarkisian, MD
[email protected]
3102068272
Catherine Sarkisian, MD (PRINCIPAL_INVESTIGATOR)

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By research site
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