The objective of this solution is to leverage AI technology to enhance the configuration process of provider contracts in Health Plan administrative systems. The proposed solution involves utilizing AI to analyze new provider contracts, modifications and extensions, identifying changes in written terms and conditions, rate tables, reimbursement terms and conditions, payment and banking information, and the steps to complete required updates to ensure accurate and timely provider payments. The AI system would analyze contract details, generate configuration recommendations, identify the correct sequence of completing configuration in the system and automate the completion of input for final review and approval of the necessary updates before being released for testing. Once testing is completed and errors are corrected (which is a related AI Solution), the configuration input would be generated, reviewed and then released to update the production system. The benefits include improved claims payment accuracy, efficiency, contract compliance, enhanced provider experience and easier on-going contract administration. By implementing this AI-enhanced solution, healthcare organizations can streamline contract configuration processes and ensure a level of accuracy, completeness and timeliness in configuring new contracts or contract renewals to ensure seamless provider payment processes at Health Plans.

Utilizing AI in Provider Contract Configuration

1.  Utilize the AI to “read” and analyze provider contracts end to end, identify and document those contractual items that must be configured: Written terms and conditions, formulas, rates/rate tables, procedures and modifiers including provider/contract specific modifiers, bundled procedure rates, and any value-based care reimbursement arrangements

2.  Review AI driven analysis of the provider contract and summarize for users the key changes from the new contract or the prior contract (if an extension or new contract with an existing provider)

3.  Use the AI Configuration Copilot to prioritize configuration activities, estimate timing for configuration go-live, determine resource level of effort based upon complexity and amount of configuration, and make recommendations for sequence of activities and steps

4.  Incorporate a AI-Driven configuration pre-production testing capability (can be a separate AI in Healthcare Solution) to ensure that a large volume of claims are tested against the new vs. old provider contract claims adjudication configuration. AI can greatly reduce the manual effort for identifying discrepancies, and determining configuration changes

5.  Produce AI learned best practices when determining how to streamline business processes and subsequent pre-production configuration testing

6.  Apply the knowledge of the AI to related claims adjudication health plan business systems and workflows such as pre-payment review, claims audits for overpayments/underpayments, special audits/reviews, and compliance.

7.  Utilize the real-time AI Copilot to monitor the progress and performance against the AI estimated completion timeframe to assess staff performance, identify process issues, and bottlenecks that could impact the estimated completion timeframe against the effective date of the provider contract

8.  Integrate new knowledge into the AI by continuously teaching the AI the results of audit results from over/underpayments, provider complaints/appeals, better ways to sequence configuration tasks, under/over utilization of staff resources, prevention of bottlenecks and other “learnings” to be added to the AI’s best practices knowledge

9.  Grow the AI to be the Provider Contract Configuration Copilot that is a “partner” - not a replacement - for the experienced users in your health plan systems configuration and testing business function and processes