Case Study: UCSD School of Medicine achieves targeted Hepatitis B screening and informs public health policy with Palisade (@RISK & PrecisionTree)

UCSD Research uses @RISK and PrecisionTree to Inform Public Health Policy

UCSD School of Medicine researchers faced a public‑health challenge: Hepatitis B prevalence is highly concentrated in local Asian populations (as high as 16–18%), so the team needed to determine which screening tests and locations would be cost‑effective and improve detection and follow‑up. They worked with Palisade, using @RISK and PrecisionTree to model screening strategies and communicate complex probabilities to clinicians and policymakers.

Using Palisade’s @RISK to build Markov simulations and PrecisionTree decision trees, the team compared point‑of‑care versus standard testing and clinic versus community event locations, finding clinic-based standard testing best for wealthier Asian groups while community point‑of‑care testing worked better for lower‑income immigrants. Those Palisade‑powered results were incorporated into San Diego County’s GIS targeting program and helped prompt the U.S. Preventive Services Task Force to revise its Hepatitis B screening guidance—a clear policy impact from the modelling.

UCSD School of Medicine

John Fontanesi

Director, Center for Management Science in Health