Study EHR Risk Stratification Tools

NCT06995378 | Recruiting FDA Device

• 1 other identifier: IRB-24-6052
• Study Type: interventional
• Target: 1,200
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Prediabetes; Patient Comprehension; Health Communication

Keywords

Prediabetes; Machine Learning; Risk Stratification; Electronic Health Record; Lab Result Communication; Predictive Modeling; Patient Comprehension

Outcome Measures

Primary Outcomes (1)

• Prediabetes- Related Healthcare Utilization

  Total count of prediabetes-related healthcare utilization defined as the sum of outpatient visits to endocrinology, repeat hemoglobin A1c tests, and new prescriptions for diabetes-related medications following the index A1c result.

  365 days after result

Secondary Outcomes (11)

• Number of Repeat Hemoglobin A1c Tests

  365 days after result

• Number of Prescriptions for Diabetes-Related Medications

  180 days after result

• Total Number of Outpatient Healthcare

  180 days after result

• Numbers of Referrals to Endocrinology

  14 days after initial result

• Number of Referrals to Nutrition Services

  14 days after initial result

Other Outcomes (5)

• Self-Reported Quality of Life

  30 days after initial survey invitation

• Self-Reported Physical Function Following Lab Result

  30 days after initial survey invitation

• Self-Reported Dietary Behaviors Following Lab Result

  30 days after initial survey invitation

Study Arms (2)

Personalized Lab Result Messaging

EXPERIMENTAL

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.

Device: Hemoglobin A1c Lab Result Communication Tool

Standard Lab Result Messaging

NO INTERVENTION

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.

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.

Personalized Lab Result Messaging

Eligibility Criteria

• Age: 65 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Older Adult (65+)

You may qualify if:

• Age 65 years or older
• Hemoglobin A1c in the prediabetes range (5.7- but not including 6.0%)

You may not qualify if:

• No UCLA primary care provider
• Age \<65 years
• Eligibility for Surveys:
• All randomized participants are eligible to receive study surveys. No additional eligibility criteria apply for survey participation.
• HgbA1c of 6.0 or above is not eligible.

Sponsors & Collaborators

• University of California, Los Angeles: lead
• National Institute on Aging (NIA): collaborator

Study Sites (1)

UCLA Health System

Los Angeles, California, 90049, United States

RECRUITING

MeSH Terms

Conditions

Prediabetic State

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases

Central Study Contacts

Katelyn Nguyen Assistant Clinical Research Coordinator

CONTACT

310-267-5250; katenguyen@mednet.ucla.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor of Medicine

Study Record Dates

• First Submitted: May 20, 2025
• First Posted: May 29, 2025
• Study Start: May 27, 2026
• Primary Completion (Estimated): November 1, 2026
• Study Completion (Estimated): September 1, 2029
• Last Updated: July 9, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)