Automation adoption is high in US healthcare administration. However, automation of PriorAuthorization (PA) falls significantly behind, with less than 30% adoption across US health plans.
One major US healthcare administrator was struggling with the complexity of PA processing, as experts need access to multiple data points and must maintain regulatory compliance for each state.
Therefore PA decision-making is slow and difficult to automate, resulting in delays in care and patients abandoning treatments.
Partnering with UiPath, Rainbird introduced knowledge graphs to the clients’ RPA program which allowed them to codify human PA expertise and power automated decision making. Meanwhile, UiPaths’ RPA focused on completing specific tasks and triggered the Rainbird-powered decision tool for instruction. This solution provided an effective separation between process tasks and decision-making, which sped up the entire PA cycle significantly.
The resulting Rainbird-UiPath hybrid model executes faster and has reduced build time by 95%.
The model is more consistent, delivering accurate HIPPA-compliant decisions every time. It is easier to maintain, cheaper to operate, and overall, more reliable.
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