As discussed in our previous article, agentic artificial intelligence (AI), the next generation of digital workforce technology, enables healthcare organizations to approach automation in ways that achieve greater efficiency, scalability, and accuracy. Adopting agentic AI is about more than simply deploying technology, as it has the potential to optimize workflows, transform teams, and ensure data readiness.
The key is to build a successful hybrid intelligence model that fosters collaboration between digital agents and human teams for optimal results. Digital agents handle structured, repetitive tasks, while human agents focus on high-touch, complex processes. The approach includes a feedback loop to ensure continuous improvement by enabling digital agents to learn from outcomes to improve future decisions and empower human teams to provide feedback to retrain AI models and refine workflows.
Steps to Prepare for Implementation
Implementing agentic AI through a hybrid intelligence model requires careful planning and preparation. As healthcare leaders explore how to build a digital workforce using agentic automation, one of the most critical early steps is preparing the organization’s data and workflows for intelligent systems.
Key questions to answer include:
- What internal data do you have access to?
- What data can your development team and partners access?
- Can you grant secure access to systems, documentation, or portals?
Upon answering these questions and accessing data, below are key steps to achieve the full potential and return on investment:
- Prepare to be AI-ready: Identify internal and external data sources, including electronic health records (EHRs), billing systems, and payer portals. Ensure secure access to systems and documentation.
- Clean data: Standardize formats across systems and resolve missing fields such as CPT codes and denial reasons. Clean, contextual, and connected data is essential for autonomous decision-making and to adapt over time.
- Define governance frameworks: Establish role-based permissions, escalation paths, and audit logs for AI actions. Ensure compliance with regulations like HIPAA and payer-specific rules.
- Engage security teams: Involve internal security teams early to address data privacy and compliance concerns.
Human involvement is essential in a digital workforce model, where human agents provide feedback to retrain AI models and refine workflows and digital agents learn from outcomes to improve future decisions. Applications that are well-suited for digital agents to collaborate include:
- Authorization Agent, which automates prior authorization.
- Eligibility Agent, which verifies insurance coverage and benefits.
- Denials Agent, which automates denial intake, classification, and routing.
- Appeals Agent, which automates appeal packet creation and submission.
Healthcare organizations can start with a focused approach where digital agents engage in high-volume tasks such as eligibility verification, claim status updates, and standard denial workflows that involve repeatable workflows. This allows digital agents to learn while managing less complex processes.
For more actionable insights on how to prepare for agentic AI implementation to enhance your RCM workflows, download A Healthcare Leader’s Guide to Building a Digital RCM Workforce. Watch for our next article in the series, where we explore best practices for optimizing agentic AI.
