Modernizing Claims Operations with Agentic Automation
Modernizing Claims Operations with Agentic Automation
Claims Operations Challenges for Healthcare Payers
Payers are dealing with rising claim volumes, more complex cases, and pressure to reduce administrative costs. Even with solid rules and bots, 15–20% of claims miss first pass adjudication and stall in pended queues. Unstructured data (attachments, notes) and constant configuration changes fuel manual rework, longer cycle times, and staff burnout—eroding member and provider experience.
Agentic Automation for Claims Adjudication — No Rip and Replace
Agentic AI adds an adaptive layer to your current environment. Emids’ Unified Claims Analyzer Agent classifies each pended claim and orchestrates micro agents for eligibility/COB, modifier fixes, duplicate detection, and provider contract adjustments. When confidence is low, humans stay in the loop with transparent rationale. Teams are seeing fewer manual touches and faster adjudication. (Results vary by environment.)
What You’ll Learn About Claims Automation
- Where agentic AI fits after first pass adjudication
- How agents handle unstructured inputs that break rules only automation
- A walkthrough of the Unified Claims Analyzer Agent and its micro agents
- Design patterns for pended queues and pre payment audits
- Governance & rollout: start small, keep oversight, and prove value quickly
Who Should Watch: Payer & IT Leaders
- Claims & operations leaders focused on fallout and cycle time
- Automation/AI leaders moving beyond rules based RPA
- IT/platform owners for Facets, QNXT, HRP, or custom systems
Watch On-Demand
FAQ’s
FAQ: Modernizing Claims Operations with Agentic Automation
What is this webinar about?
This webinar covers how healthcare payers can reduce claims fallout and manual rework by adding agentic automation to claims adjudication—especially after first pass adjudication when claims land in pended queues.
What problem are we solving in claims operations?
Payers are facing rising volumes, increasing claim complexity, and pressure to lower administrative costs, while 15–20% of claims can miss first pass adjudication and require manual intervention in pended queues.
Why do claims get stuck in pended queues?
Common drivers include:
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Eligibility and COB mismatches
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Missing/incorrect modifiers
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Duplicate submissions
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Provider contract/payment adjustment issues
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Unstructured inputs (attachments and notes) that don’t conform to rigid rules
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Frequent configuration changes that create exceptions and rework
We already use bots and rules—why isn’t that enough?
Rules and bots are strong for structured, repeatable tasks, but many adjudication fallouts require:
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Interpreting unstructured documents
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Adapting to changing configurations and benefit designs
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Handling exceptions and context-dependent decisions
Agentic automation is intended to fill that gap—without discarding existing automation.
What is “agentic automation” in this context?
Agentic automation uses AI agents that can reason over context, take goal-driven actions, and coordinate tasks across systems—while still working alongside bots and human reviewers.
Does this require ripping out our current claims platform or RPA?
No. The approach is “no rip and replace.” Agentic AI adds an adaptive layer on top of your current environment (including existing bots, rules, and platforms).
What is the Unified Claims Analyzer Agent?
Emids’ Unified Claims Analyzer Agent is designed to:
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Classify and analyze each pended claim
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Determine likely root cause(s)
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Orchestrate specialized micro agents to resolve common fallout types
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Provide transparent rationale and a confidence signal
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Escalate to humans when confidence is low
What are “micro agents,” and what do they do?
Micro agents are specialized agents focused on common claim fallout categories, such as:
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Eligibility/COB verification and resolution
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Modifier fixes and coding-related corrections
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Duplicate detection to prevent reprocessing/overpayment
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Provider contract adjustments to apply correct reimbursement logic
How does this help with unstructured claim inputs?
Agentic automation is designed to handle inputs that commonly break rules-only approaches—like attachments, notes, and variations in how information is submitted—so teams spend less time manually interpreting and reworking claims.
How do you ensure accuracy and oversight?
The model keeps humans in the loop:
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When agent confidence is low, claims are routed for human review
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The system provides clear rationale to support the reviewer’s decision
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Oversight is maintained through governance patterns and phased rollout
What design patterns are covered in the webinar?
The webinar includes practical patterns for:
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Managing and reducing work in pended queues
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Applying agentic automation to pre-payment audits
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Using existing bots as reliable “doers” while agents reason and orchestrate
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Implementing monitoring/controls to identify issues earlier in the workflow
What outcomes can teams expect?
Teams are aiming for:
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Fewer manual touches
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Faster adjudication and shorter cycle times
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Reduced operational strain and burnout
(Results vary by environment, data quality, and process maturity.)
Where does agentic AI fit in the adjudication lifecycle?
Agentic AI is most impactful after first pass adjudication, where exceptions and fallouts accumulate—especially in pended queues and audit workflows that require contextual research and multi-step resolution.
Modernizing Data Foundations for AI: How to Accelerate Value from Legacy to Cloud
Modernizing Claims Operations with Agentic Automation
Claims Operations Challenges for Healthcare Payers
Payers are dealing with rising claim volumes, more complex cases, and pressure to reduce administrative costs. Even with solid rules and bots, 15–20% of claims miss first pass adjudication and stall in pended queues. Unstructured data (attachments, notes) and constant configuration changes fuel manual rework, longer cycle times, and staff burnout—eroding member and provider experience.
Agentic Automation for Claims Adjudication — No Rip and Replace
Agentic AI adds an adaptive layer to your current environment. Emids’ Unified Claims Analyzer Agent classifies each pended claim and orchestrates micro agents for eligibility/COB, modifier fixes, duplicate detection, and provider contract adjustments. When confidence is low, humans stay in the loop with transparent rationale. Teams are seeing fewer manual touches and faster adjudication. (Results vary by environment.)
What You’ll Learn About Claims Automation
- Where agentic AI fits after first pass adjudication
- How agents handle unstructured inputs that break rules only automation
- A walkthrough of the Unified Claims Analyzer Agent and its micro agents
- Design patterns for pended queues and pre payment audits
- Governance & rollout: start small, keep oversight, and prove value quickly
Who Should Watch: Payer & IT Leaders
- Claims & operations leaders focused on fallout and cycle time
- Automation/AI leaders moving beyond rules based RPA
- IT/platform owners for Facets, QNXT, HRP, or custom systems
Watch On-Demand
Unlocking Interoperability: Navigating CMS Mandates, FHIR Standards & Implementation Challenges
Modernizing Claims Operations with Agentic Automation
Claims Operations Challenges for Healthcare Payers
Payers are dealing with rising claim volumes, more complex cases, and pressure to reduce administrative costs. Even with solid rules and bots, 15–20% of claims miss first pass adjudication and stall in pended queues. Unstructured data (attachments, notes) and constant configuration changes fuel manual rework, longer cycle times, and staff burnout—eroding member and provider experience.
Agentic Automation for Claims Adjudication — No Rip and Replace
Agentic AI adds an adaptive layer to your current environment. Emids’ Unified Claims Analyzer Agent classifies each pended claim and orchestrates micro agents for eligibility/COB, modifier fixes, duplicate detection, and provider contract adjustments. When confidence is low, humans stay in the loop with transparent rationale. Teams are seeing fewer manual touches and faster adjudication. (Results vary by environment.)
What You’ll Learn About Claims Automation
- Where agentic AI fits after first pass adjudication
- How agents handle unstructured inputs that break rules only automation
- A walkthrough of the Unified Claims Analyzer Agent and its micro agents
- Design patterns for pended queues and pre payment audits
- Governance & rollout: start small, keep oversight, and prove value quickly
Who Should Watch: Payer & IT Leaders
- Claims & operations leaders focused on fallout and cycle time
- Automation/AI leaders moving beyond rules based RPA
- IT/platform owners for Facets, QNXT, HRP, or custom systems
Watch On-Demand
Unlocking The Cloud Cost Conundrum – Expert Talks Ep.1
Unlocking The Cloud Cost Conundrum – Expert Talks Ep.1
Cloud migration is transforming the healthcare industry, but it comes with unique challenges. In this exclusive fireside chat, healthcare leaders and cloud experts from Emids share actionable insights on how to navigate the complexities of cloud adoption, manage rising costs, and unlock the true potential of data in healthcare.
What you’ll learn:
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- Strategies to integrate and refactor legacy data for real-time insights
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- Best practices for controlling cloud costs and improving ROI
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- How to align cloud initiatives with long-term organizational goals
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- Key KPIs to monitor for financial governance and cost management
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- Expert perspectives on the future of cloud-driven innovation in healthcare
Featuring Industry Experts:
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- Balajee Sethuraman, President & Managing Partner, Emids
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- Yogesh Shinde, Healthcare Industry Expert
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- Rajeev Ranjan, Cloud Strategy Expert, Emids
Who Should Watch:
Healthcare executives, IT leaders, and decision-makers in payer and provider organizations looking to optimize cloud migration, improve financial governance, and drive better patient outcomes through innovative data strategies.
Watch the Talk