Description: Session 1G: Rethinking Catastrophic Claims - Strategies for Sustainable Stop-Loss Pricing

Description: Over the last 10 years, Artificial Intelligence (AI) healthcare foundation models have made tremendous strides when it comes to delivering highly accurate predictive results when compared to traditional models. This is especially true for models developed and trained on the ‘language’ of healthcare. When trained on healthcare data sequences (claims, EHR, CPT, ICD, pharmacy, lab, etc.), these models deliver far more accurate results as to WHAT beneficiary-level health events will occur and even WHEN they will occur.

Description: This webcast will walk through several statistical methods for imputing race and ethnicity from U.S. datasets, highlighting their strengths and weaknesses, talking about how to use them and evaluating their accuracy, and telling you where you can get code packages as well as a free dataset to try the methods out.