Proactive Care Management of AI-Identified At-Risk Patients Decreases Preventable Admissions

AJMC November 6, 2024
Ann C. Raldow, MD, MPH,Naveen Raja, DO, MBA,Chad W. Villaflores, MS,Samuel A. Skootsky, MD,Elizabeth A. Jaureguy, MSN, FNP-C,Hanina L. Rosenstein, MS,Sarah D. Meshkat, MHA,Sitaram S. Vangala, MS,Catherine A. Sarkisian, MD, MSHS

Proactive care management for artificial intelligence (AI)–identified at-risk patients reduced potentially preventable hospital admissions.

ABSTRACT

Objectives: We assessed whether proactive care management for artificial intelligence (AI)–identified at-risk patients reduced preventable emergency department (ED) visits and hospital admissions (HAs).

Study Design: Stepped-wedge cluster randomized design.

Methods: Adults receiving primary care at 48 UCLA Health clinics and determined to be at risk based on a homegrown AI model were included. We employed a stepped-wedge cluster randomized design, assigning groups of clinics (pods) to 1 of 4 single-cohort waves during which the proactive care intervention was implemented. The primary end points were potentially preventable HAs and ED visits; secondary end points were all HAs and ED visits. Within each wave, we used an...

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