Evaluation of Patient and Provider Facing EHR-embedded Risk Stratification Tools
University of California, Los Angeles
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.
Description
Prediabetes thresholds based on hemoglobin A1c were originally developed using younger, healthier populations and may not reflect the slower and more variable glycemic changes observed in older adults. Evidence from large community-based cohorts suggests that adults aged 65 years and older with A1c values in the prediabetes range are often more likely to return to normal glycemia than to progress to diabetes, creating uncertainty for patients and providers when interpreting lab results. Machine learning models developed using de-identified UCLA Health EHR data from multiple annual cohorts bet…
Eligibility
- Age range
- 65+ years
- Sex
- All
- Healthy volunteers
- No
Inclusion Criteria: * Age 65 years or older * Most recent hemoglobin A1c in the prediabetes range (5.7-6.0%) Exclusion Criteria: * Have lab results outside the defined inclusion range * 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.
Interventions
- DeviceHemoglobin A1c Lab Result Communication Tool
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.
Location
- UCLA Health SystemLos Angeles, California