In recent years, there has been a growing focus on shifting to value-based care (VBC) models in Medicaid. However, many of these payment models are “value veneers”—or modest shared savings agreements or performance bonuses that nominally pass as VBC but do not meaningfully change care delivery to improve access, quality of care, or outcomes for patients.

In a new article for Health Affairs, Waymark co-founders Rajaie Batniji and Sanjay Basu and VP of Data Science and AI Sadiq Patel discuss how data quality issues and insufficient integration of clinical and social risk factor data have limited the ability of Medicaid programs to proactively identify and deliver targeted interventions to at-risk patients—thereby contributing to the growth of value veneers. They also outline how recent advances in data science, including machine learning (ML) algorithms like Waymark Signal, can enable Medicaid programs to deliver high-value care to beneficiaries.

Read the article here.