By BENJAMIN EASTON
Healthcare’s administrative burden is not a documentation problem. It is a workflow problem. Healthcare’s next leap depends on agentic systems that can actually do the work
Over the past year, healthcare organizations have widely adopted generative AI for an array of documentation-related activities such as drafting appeal letters, producing patient-friendly summaries, and even assisting with administrative writing. While these tools have improved how information is created, healthcare’s administrative bottlenecks (e.g., prior authorizations, benefit verification, denial management, clinical trial enrollment), are not caused by a lack of text. They are caused by fragmented systems, manual tracking, payer variability, and workflow handoffs that require continuous monitoring and intervention.
If generative AI helps write the email, agentic systems send it, track it, escalate it, reconcile the response, and close the loop.
That distinction is healthcare’s next inflection point.
From Content Generation to Workflow Execution
An agentic system is not just a chatbot layered onto healthcare workflows. It is a coordinated set of AI-driven agents designed to:
- Pull structured and unstructured data from EHRs, payer portals, labs, and internal systems
- Apply payer-specific policy logic
- Validate documentation requirements
- Submit transactions through the appropriate channel
- Monitor status changes
- Trigger follow-up actions
- Escalate exceptions to humans
- Log every action for audit and compliance
Behind the scenes, these systems rely on rule engines, structured clinical mappings, secure API integrations, and event-driven automation frameworks. They continuously re-evaluate state changes (e.g., a new lab result, a status update from a payer portal, or a missing documentation flag) and dynamically adjust next steps.
This is not robotic process automation replaying keystrokes. It is intelligent orchestration across disconnected systems.
Consider prior authorization.
A generative AI tool can draft an appeal letter, whereas an agentic system:
- Identifies the denial code.
- Retrieves the relevant clinical documentation from the EHR.
- Cross-references payer policy criteria.
- Packages structured and narrative justification.
- Submits via API or portal.
- Tracks payer status updates.
- Sends reminders if timelines lapse.
- Escalates to a case manager only if a defined threshold is reached.
- Documents the full interaction trail for compliance review.
One improves writing. The other reduces days in accounts receivable and shortens patient delays.
An Administrative Crisis the Industry Can No Longer Ignore
The strain on healthcare’s workforce is not theoretical. Workforce projections indicate significant shortages of licensed practical and vocational nurses in the coming decade. Meanwhile, clinicians consistently report that prior authorizations delay treatment and negatively affect outcomes.
These inefficiencies do not disappear when appeal letters are written faster. They disappear when entire workflows are automated end-to-end. Indeed, behind every authorization request is a chain of manual steps from eligibility verification, and benefits interpretation to portal submissions, escalation calls and denial rework.
If only the writing portion improves, the administrative burden remains intact. Agentic systems compress these multi-step sequences into coordinated digital execution.
Interoperability: Where Agentic Systems Win
Healthcare interoperability is shifting from passive data exchange to actionable orchestration.
Regulatory frameworks and payer mandates increasingly require traceable, auditable information flow. But exchanging data is not the same as acting on it.
Agentic systems operate across a multitude of environments to include EHR platforms, payer portals, laboratory systems and even clinical trial databases.
Behind the scenes, they normalize data structures, apply payer-specific logic trees, and trigger workflow states based on predefined thresholds. Instead of staff re-entering data across portals, the system executes those interactions programmatically and continuously.
The result: fewer dropped tasks, faster turnaround times, and reduced human rework.
A Vision for Collaborative, System-Wide Adoption
The shift to agentic systems is already here. Organizations that move now will gain measurable advantages in operational efficiency, approval rates, and staff retention.
Two emerging examples illustrate how this works beyond theory.
Catalonia’s ALMA: Embedding Evidence into Workflow
In Catalonia, the public health system deployed an agentic assistant called ALMA to bring evidence-based clinical guidance into day-to-day clinician workflows. The results were striking: 65% of users integrated it into routine work, with a 98% user satisfaction rate. The program scaled across primary care and is now positioned for expansion into additional services.
What is happening behind the scenes?
- The system integrates with clinician-facing platforms.
- It ingests patient data in real time.
- It maps that data against clinical guidelines and decision pathways.
- It surfaces context-specific recommendations during workflow, not after.
- It logs usage patterns and refines recommendations based on clinician feedback.
This is not a static knowledge base. It is a continuously learning workflow participant.
The results: 65% of clinicians incorporated it into routine practice, with 98% satisfaction, and system-wide scaling underway.
The key insight: adoption occurred because the system participated in workflow, rather than interrupting it.
Tempus TIME: Orchestrating Clinical Trial Enrollment
Clinical trial enrollment is one of healthcare’s most coordination-intensive processes.
Tempus deployed its TIME program as an AI-powered network that orchestrates trial matching, site activation, and patient enrollment across distributed care settings.
Behind the scenes, TIME:
- Analyzes structured and genomic clinical data to identify potential matches.
- Uses algorithmic pre-screening to filter candidates.
- Routes potential matches to nurse reviewers.
- Initiates parallel site activation workflows.
- Coordinates outreach and documentation tracking simultaneously.
Multiple agents operate in concert, some scanning for eligibility, others managing site documentation, others tracking enrollment milestones.
This orchestration drove a 64% annual increase in trial enrollment at TriHealth Cancer Institute, with 95% of that growth attributed to TIME-driven coordination.
The impact was not better messaging. It was better synchronization.
The Strategic Shift Ahead
Healthcare has already experimented with generative AI. The next phase is execution-layer automation. Leaders evaluating this transition should:
- Identify high-volume workflows with measurable delay metrics
- Map the full state transitions of those workflows
- Evaluate vendors on interoperability depth, not interface polish
- Require human-in-the-loop escalation design
- Pilot with defined metrics: cycle time reduction, denial rate improvement, labor hours saved
The competitive advantage will not come from who drafts letters fastest. It will come from who closes loops fastest. The question is no longer whether AI can write. The question is whether it can act.
Benjamin Easton is the Co-Founder and CTO of Develop Health
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