Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments

• Auteurs principaux: Jeremy A. Irvin (Auteur), Andrew A. Kondrich (Auteur), Michael Ko (Auteur), Pranav Rajpurkar (Auteur), Behzad Haghgoo (Auteur), Bruce E. Landon (Auteur), Robert L. Phillips (Auteur), Stephen Petterson (Auteur), Andrew Y. Ng (Auteur), Sanjay Basu (Auteur)
• Format: Livre
• Publié: BMC, 2020-05-01T00:00:00Z.
• Sujets: article
• Accès en ligne: Connect to this object online.

Abstract Background Risk adjustment models are employed to prevent adverse selection, anticipate budgetary reserve needs, and offer care management services to high-risk individuals. We aimed to address two unknowns about risk adjustment: whether machine learning (ML) and inclusion of social determi...