Refining Risk Prediction Models for Older Adults Using Electronic Health Records

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Conditions studied: Predictive Modeling

In brief

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.

Key facts

Study ID

NCT06995365

Run by

University of California, Los Angeles

People needed

18000

Starts

2026-09-01

Expected to finish

2028-03-01

Last updated by the study team

2026-07-24

Who can join

Age: 65 and older. Sex: any. Healthy volunteers: not accepted.

You may not qualify if…

• Patients younger than 65 years old
• Patients with less than 5 years of clinical follow-up
• Patients from health systems outside of the UC Health network.

Where it is running

• UCLA Health System — Los Angeles, California, United States

Full record on ClinicalTrials.gov

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