This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
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.
Evaluation of MA Proactive Care Program Using Cost Prediction Model With Randomized Waitlist
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
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Sponsor: University of California, Los Angeles
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.