Evaluation of AI Cost Prediction Model to Enroll Patients in Complex Care Management Program

NCT06916247 | Recruiting

• 1 other identifier: IRB-24-0849
• Study Type: interventional
• Target: 5,000
• Locations: 1 country
• Sites: 1

Brief Summary

Currently, UCLA Health (specifically the Office of Population Health and Accountable Care, or OPHAC) runs a complex care management program called Proactive Care (goal is to reduce care utilization by providing personalized care navigation/case management). Every month, an AI Population Risk tool runs to identify around 250 of the 480,000 or so UCLA primary care patients, and RNs contact these 250 patients to enroll in Proactive Care. Starting in December 2024, OPHAC launched a new method of enrolling UCLA's Medicare Advantage (MA) patients into Proactive Care: an AI Cost Prediction model. The idea is the same-- the top 250 highest predicted cost patients will be enrolled in Proactive Care. The investigators will evaluate this model and subsequent enrollment into the program by randomizing the waitlist of MA patients waiting to enroll in Proactive Care, thereby creating a control group. The top 500 highest predicted cost patients will be identified each month, and following a 1:1 randomization, 250 will be contacted for enrollment and the rest will be put on a wait-list control group for 10 months unless otherwise requested by their provider to be enrolled in the Proactive Care program earlier.

Conditions

Chronic Disease

Keywords

High utilization; Complex care management; Cost prediction model

Outcome Measures

Primary Outcomes (1)

• Days alive and out of hospital (DAOH) at 120 days from randomization

  The sum of the number of days that a patient is not hospitalized under inpatient or observation status, and alive, out of a maximum of 120 days post-randomization.

  120 days after randomization

Secondary Outcomes (8)

• Days alive and out of hospital (DAOH) at 30 days from randomization

  30 days after randomization

• Days alive and out of hospital (DAOH) at 90 days from randomization

  90 days after randomization

• Days alive and out of hospital (DAOH) at 10 months from randomization

  10 months post-randomization

• Total healthcare expenditures at 10 months from randomization

  10 months post-randomization

• All-cause hospitalizations at 10 months from randomization

  10 months post-randomization

Other Outcomes (4)

• Cost prediction model performance over 22 months, as measured by area under the receiver operating characteristic curve

  12 months after the final cohort enrolls

• Protocol fidelity over the 10 months of enrollment

  14 months post-randomization

• Avoidable hospitalizations

  10 months post-randomization

Study Arms (2)

Complex Care Management

ACTIVE COMPARATOR

Patients randomized to be contacted for enrollment into the complex care management program called ProActive Care.

Behavioral: Complex care management program

Care as usual

NO INTERVENTION

Patient randomized to be put on a waitlist for being contacted for enrollment into ProActive Care (ie, not enrolled in ProActive Care).

Interventions

Complex care management program BEHAVIORAL

Intensive outpatient care management program that includes contact from nurses and case managers to help coordinate care, detect clinical red flags, and reduce overall unplanned acute care utilization.

Complex Care Management

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• At least 18 years of age
• Enrolled in a UCLA Managed Care Plan
• Cost prediction model identifies patient as having high predicted costs over the next 12 months

You may not qualify if:

• Currently enrolled in any UCLA care management program
• Enrolled in any UCLA care management program in the last 12 months
• Already has an active referral to a care management program

Sponsors & Collaborators

• University of California, Los Angeles: lead

Study Sites (1)

UCLA Health

Los Angeles, California, 90095, United States

RECRUITING

MeSH Terms

Conditions

Chronic Disease

Condition Hierarchy (Ancestors)

Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Richard K Leuchter, MD

  University of California, Los Angeles

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Richard K Leuchter, MD

CONTACT

310-267-9111; rleuchter@mednet.ucla.edu

William Turner, BA

CONTACT

310-267-9111; wturner@mednet.ucla.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: INVESTIGATOR, OUTCOMES ASSESSOR
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assistant Professor

Study Record Dates

• First Submitted: March 21, 2025
• First Posted: April 8, 2025
• Study Start: August 16, 2024
• Primary Completion: September 9, 2025
• Study Completion (Estimated): May 12, 2026
• Last Updated: January 29, 2026

Record last verified: 2026-01

Locations

US (1)