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Revolutionizing Appeals and Grievances Processing with Multi-Modal Generative AI

Health plans face significant challenges in efficiently managing member and provider appeals and grievances. The process is time-sensitive, highly regulated, and involves handling inputs from multiple channels including paper documents, faxes, and phone calls. Traditional approaches often struggle to keep up with volume and complexity while meeting strict regulatory timelines to avoid penalties. However, emerging multi-modal generative AI tools offer promising solutions to transform this critical process.

Enter Multi-Modal Generative AI

The latest gen AI tools and models can process multiple modalities - text, images, audio, and structured data – combining these inputs to make more comprehensive summaries or connect relationships among these inputs. This makes multimodal AI tools uniquely suited to tackle the varied inputs and complex decision-making involved in appeals and grievances. Here’s a rundown of their capabilities and benefits:

Intelligent Document Processing

Advanced computer vision and natural language processing allow AI to:

  • Scan and digitize paper documents and faxes
  • Extract key information from forms and letters beyond a few fields extracted by OCR
  • Assess Urgent vs Non - urgent cases
  • Generate a summary and chronologically arrange documents for quick research
  • Classify document types and route accordingly
  • Understand handwritten notes

Speech-to-Text and Natural Language Understanding

For phone-based appeals and grievances, AI can:

  • Transcribe calls in real-time
  • Analyze sentiment and intent
  • Extract key details and claims
  • Summarize conversations

Automated Analysis and Decision Support

By combining extracted information with health plan data, AI can:

  • Verify member eligibility and benefits
  • Match appeals to relevant policies and clinical guidelines
  • Identify missing information or documentation
  • Suggest appropriate resolutions based on precedent
  • Flag high-priority or time-sensitive cases

Natural Language Generation

To assist with responses, AI can:

  • Draft personalized determination letters
  • Generate call scripts for follow-up conversations
  • Create internal summaries for review

Putting it All Together

Because it integrates all the above capabilities, a multi-modal generative AI system can serve as an end-to-end solution for A&G:

  1. Ingest appeals/grievances from all channels
  2. Extract and structure relevant information
  3. Analyze details against policies and guidelines
  4. Recommend determinations for human review
  5. Generate responses to the providers/members
  6. Track timelines and flag at-risk cases

This multimodal AI-powered workflow can dramatically reduce processing times, improve accuracy and consistency, and help ensure regulatory compliance - all while freeing up human staff to focus on complex cases and member interactions.

The Path Forward:

While the potential is immense, health plans should approach AI implementation thoughtfully:

  • Start with pilot programs to prove value and refine workflows
  • Ensure strong data governance and privacy protections
  • Maintain human oversight, especially for sensitive determinations
  • Continuously monitor for bias and errors
  • Stay up-to-date on evolving AI regulations in healthcare

By strategically leveraging multimodal gen AI, health plans can transform appeals and grievances from a regulatory burden into an opportunity for improved efficiency, member satisfaction, and competitive advantage.

For more information please contact Anup Panthaloor, EVP – Health Plans and Health Services or Deepan Vashi, EVP – Healthcare Payer Practice and Solutions Lead, Solutions Architecture, Firstsource. Visit Firstsource relAI to read about our suite of AI led platforms, solutions and offerings.  Learn how we’re empowering businesses of all sizes to seamlessly integrate digital technology and AI into their operations to enable new levels of efficiency, innovation, and competitive advantage.