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

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

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...

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Bibliographic Details
Main Authors: Jeremy A. Irvin, Andrew A. Kondrich, Michael Ko, Pranav Rajpurkar, Behzad Haghgoo, Bruce E. Landon, Robert L. Phillips, Stephen Petterson, Andrew Y. Ng, Sanjay Basu
Format: Article
Language:English
Published: BMC 2020-05-01
Series:BMC Public Health
Subjects:
Risk estimation
Machine learning
Social determinants of health
Online Access:http://link.springer.com/article/10.1186/s12889-020-08735-0

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http://link.springer.com/article/10.1186/s12889-020-08735-0

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