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2On-Line Provider Directory Accuracy

Strategic Application of Artificial Intelligence in On-Line Provider Directory Accuracy

This use case leverages AI technology to address the challenge of maintaining accurate On-Line Provider Directories. The proposed solution involves implementing AI-driven processes to ensure the accuracy of provider data, helping healthcare providers and health plans avoid member/patient complaints, comply with regulatory requirements, and avoiding penalties. The solution includes enhancing internal health plan business processes through AI, including proactively identifying changes in provider data, and accelerating updates to the directories while creating a “curated” and tightly controlled provider data master. By incorporating AI technology, health plans can streamline provider data management, proactively flag provider data changes for review, expedite the update process and then automatically send updates to downstream applications and third parties who also depend upon accurate provider information. The benefits of staying in compliance, improving efficiency, eliminating complaints through timely updates, and increasing patient and member satisfaction make this AI-driven solution crucial for maintaining reliable provider data in On-Line Provider Directories.

Utilizing AI in On-Line Provider Directory Accuracy

1.  Utilize the AI to anticipate provider data changes by continuously analyzing activity in other systems, processing of rosters from provider systems, portal provider demographic change requests, provider contracts, member complaints, and other sources of provider data changes like re-credentialing and provider relations

2.  Review AI driven analysis of current inaccurate provider data to identify sources and reasons of inaccuracy and determine remediation activities through root case analysis methods to “cleanse” provider directory data once and ensure on-going accuracy. Add learned knowledge to the AI Knowledge Base for future reference by the AI

3.  Produce AI learned best practices when determining how to remediate inaccurate data and sources

4.  Apply the knowledge of the AI to other health plan business systems and workflows that create their own provider data files that are impacting provider data accuracy in on-line directories

5.  Utilize the real-time AI Copilot monitoring changes to provider data feeds, new complaints, timing of updates from Health System Rosters, volume of new clinicians being on-boarded after credentialing, provider portal demographic updates and others, apply AI to continuously get “smarter” over time to offer insights for continuous Improvement of data accuracy 

6.  Integrate new knowledge into the AI by continuously teaching the AI the results of remediation, its time duration, level of effort and outcome

7.  Enhance the AI’s known experience into an enterprise resource which can access strategic growth planned for provider network expansion offering guidance, insights, reminders and relevant recommendations to expedite the entry of accurate and verified provider data to the on-line directory updates

8.  Grow the AI Copilot to be a “partner” - not a replacement - for the experienced users in your provider data management function