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.
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
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
Parallel
Complex care management program
BehavioralIntensive 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.
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.
Days alive and out of hospital (DAOH) at 30 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 30 days post-randomization.
Days alive and out of hospital (DAOH) at 90 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 90 days post-randomization.
Days alive and out of hospital (DAOH) at 10 months 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 300 days post-randomization.
Total healthcare expenditures at 10 months from randomization
The sum of all healthcare expenditures (inpatient, outpatient, prescription, etc.) as determined by claims data.
Cost prediction model performance over 22 months, as measured by area under the receiver operating characteristic curve
Observed healthcare expenditures for each month's control cohort will be measured over the subsequent 12 months after randomization (ie, 10 months of enrollment + 12 months of follow-up= 22 months), and compared to model-predicted healthcare expenditures. This analysis will only be conducted in the control group, as the intervention is designed to affect healthcare expenditures in the treatment group.
Protocol fidelity over the 10 months of enrollment
The sum of two metrics: * The proportion of patients randomized to the intervention who enroll in the complex care management program * The proportion of patients randomized to the control who do not enroll in the complex care management program.
Avoidable hospitalizations
The number of hospitalizations that could have been avoided through timely access to ambulatory care
Avoidable emergency department visits
The number of emergency department visits that could have been avoided through timely access to ambulatory care
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