Risk Adjustment Models Prove to be Effective According to New Research

In this day and age, it’s extremely important for providers to determine who their high-risk patients are and how they can reduce readmissions.  According to new research, hospitals can focus on several specific models to help coordinate care.  Researchers from the Mayo Clinic studied seven risk-adjustment models and how useful they were in predicting hospitalizations, 10 day readmissions, high expenditures, and emergency room visits.  The models they evaluated included Adjusted Clinical Groups (ACG), Minnesota Tiering, the Hybrid Model, among three others.  Although all the models analyzed proved to have fair predictive value, the ACG model was the most accurate predictor.  It’s important to note that risk adjustment models have also proved to be problematic in the past.

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