Refining Risk Prediction Models for Older Adults Using Electronic Health Records

NCT06995365 | Not Yet Recruiting

• 1 other identifier: IRB-25-0471
• Study Type: observational
• Target: 18,000
• Locations: 1 country
• Sites: 1

Brief 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

Keywords

Lab Result Communication; Risk Stratification

Outcome Measures

Primary Outcomes (1)

• Performance of the Risk Prediction Model

  Evaluate the predictive performance of a machine learning-based risk model using retrospective Electronic Health Records (EHR) data. The model estimates the likelihood of disease progression in older adults. The model should be designed to be adaptable to various clinical conditions. Metrics include Area Under the Receiver Operating Characteristic Curve (AUC-ROC), sensitivity, and specificity.

  Up to 5 years of retrospective follow up

Interventions

Risk Prediction Model OTHER

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.

Eligibility Criteria

• Age: 65 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adults aged 65 and older who received care within the UCLA or UC Health system, have at least 5 years of clinical follow-up, and have had a serum creatinine test. Data are drawn from existing electronic health records.

You may qualify if:

• being over the age of 65; having at least 5 years of clinical follow up; and having a serum creatinine lab test conducted

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.

Sponsors & Collaborators

• University of California, Los Angeles: lead

Study Sites (1)

UCLA Health System

Los Angeles, California, 90024, United States

Location

Central Study Contacts

Katelyn Nguyen

CONTACT

13102675250; katenguyen@mednet.ucla.edu

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor of Medicine

Study Record Dates

• First Submitted: May 20, 2025
• First Posted: May 29, 2025
• Study Start: August 1, 2025
• Primary Completion: December 1, 2025
• Study Completion: March 1, 2026
• Last Updated: May 29, 2025

Record last verified: 2025-05

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)