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case study
Patient Payments
How a 120-Day Machine Learning Experiment Led to a 6.5% Increase in Patient Collections
In late 2019, Sift Healthcare and State Collection joined forces to test AI in the revenue cycle. Together, we conducted a rigorous 120-day live, scientific test (with a control group) for Wake Forest Baptist Health, to determine if machine learning impacted patient financial engagement outcomes. The results were impressive — a 6.5% increase in patient collections.
Data Science
Every Revenue Cycle Improvement Matters
Improving the revenue cycle means minimizing costs and increasing collections, from both patients and payers. Even on a small scale, artificial intelligence has a meaningful impact on healthcare payments and operations.
