NCT06995365

Refining Risk Prediction Models for Older Adults Using Electronic Health Records

Patient-centered Precision Medicine Lab Result Communication for Older Adults - Validation and Refinement of an Existing Chronic Kidney Disease (CKD) Risk Model

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 18,000 (estimated)
• Sponsor: University of California, Los Angeles · Academic / Other
• Sex: All
• Age: 65 Years
• Healthy volunteers: Not accepted

Summary

This study aims to improve how lab results are communicated to older adults by refining a predictive model that uses electronic health record (EHR) data. The model was originally developed to estimate the risk of chronic kidney disease (CKD) progression. Researchers will use existing health data to test and improve the accuracy of the model and explore how it might be adapted for use in other health conditions. The study does not involve direct interaction with patients and is conducted entirely using de-identified data in a secure environment.

Conditions

• Predictive Modeling

Interventions

Type	Name	Description
OTHER	Risk Prediction Model	This study analyzes retrospective electronic health record (EHR) data from older adults to refine and validate a predictive model for other conditions in future studies.

Timeline

• Start date: 2025-08-01
• Primary completion: 2025-12-01
• Completion: 2026-03-01
• First posted: 2025-05-29
• Last updated: 2025-05-29

Locations

1 site across 1 country: United States