Sponsored by Prognos Health

As risk adjustment programs are looking to be more effective and less wasteful, manual tasks are being automated, processes are becoming more precise, and less friction is experienced by payers and providers. So what is left? Clinical lab data with predictive models can be valuable when combined with other available data, then leveraging the analytical models to improve risk adjustment and the resulting member outcomes.