Machine Learning Model for Improving Auto Adjudication Rates For Large Provider – Sponsored Health Plan
Machine Learning Model for Improving Auto Adjudication Rates For Large Provider – Sponsored Health Plan
2 PagesMachine Learning Model for Improving Auto Adjudication Rates For Large Provider – Sponsored Health Plan Client Requirement Client is a leading regional health plan and a subsidiary of one of the largest integrated health systems in the US. Using a legacy claims management system, the clients had a low Claims Auto Adjudication Rate (AAR) of 72%. It needed to increase AAR to align with industry benchmarks (over 90%). CitiusTech was engaged to develop an AI/ML-based solution that would minimize the number of suspended claims, significantly improve the AAR. CitiusTech also needed to use the client’s existing infrastructure for achieve this objective. CitiusTech Approach CitiusTech’s team of AI/ML specialists and clinical data experts developed an AI/ML model that could accurately
