Refining Risk Prediction Models for Older Adults Using Electronic Health Records

University of California, Los Angeles (UCLA)

Status: Not yet enrolling

Conditions: Predictive Modeling

Treatments: Other: Risk Prediction Model

Study type: Observational

Funder types: Other

Identifiers

NCT06995365

IRB-25-0471

Details and patient eligibility

About

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.

Enrollment: 18,000 estimated patients

Sex: All

Ages: 65+ years old

Volunteers: No Healthy Volunteers

Inclusion and exclusion criteria

Inclusion Criteria include, but are not limited to:

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

Exclusion Criteria:

• 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.