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...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2020-05-01
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| Series: | BMC Public Health |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12889-020-08735-0 |