Revenue Cycle Executive

Tony
Esposito

VP · Director · Strategic Leader

Thirty years transforming how health systems capture, manage, and optimize revenue. I specialize in the space where clinical operations meet financial performance — and I've built the AI-assisted denial triage framework that closes the gap between ambition and execution.

30+ Years RCM
Anthropic Academy Certified
$2B+ AR Managed

The discipline of
revenue integrity

I've spent three decades at the intersection of healthcare operations and financial performance — leading revenue cycle transformations for hospitals, health systems, and multi-site physician groups across the country.

My expertise runs deep in Epic Resolute, managed care contracting, denials management, and AR optimization. I've built and rebuilt RCM functions from the ground up, integrated systems through mergers and acquisitions, and led teams through the industry's most significant technology transitions.

Today, I'm focused on a critical inflection point: health systems are writing AI into every RCM job description — but few can clearly articulate what they need AI to actually do. That's the conversation I'm driving.

Revenue Cycle Leadership

End-to-end RCM strategy, team development, and operational transformation at VP and Director level across acute and ambulatory settings.

Epic / Resolute

Deep platform expertise across build, implementation, optimization, and post-live support — including charge capture, billing, and AR workflows.

Denials & Claims Optimization

Systematic denial prevention and management frameworks that reduce write-offs and accelerate cash flow at scale.

Managed Care Contracting

Payor strategy, contract negotiation, and reimbursement analysis that align clinical volume with financial outcomes.

The RCM Perspective

All Posts on LinkedIn
Denials Management

The Denial That Doesn't Need a Workaround Needs a Root Cause

Most denial management programs are built to appeal. The best ones are built to prevent. The difference is upstream clinical and coding alignment.

Epic Resolute

What Epic Can't Fix if Your Charge Capture Is Broken

A platform is only as strong as the workflow behind it. Resolute exposes gaps — it doesn't resolve them. Here's what that means at go-live.

Leadership

The RCM Talent Problem Isn't Supply — It's Selection

Health systems are struggling to hire strong RCM leaders. The shortage is real, but the bigger issue is how we've defined the role for the next decade.

Managed Care

When Payor Relations Become a Revenue Strategy

Contract management is table stakes. What separates the best health systems is how they leverage data to drive payor conversations before renewal season.

RCM Denial Management
AI-Assisted Triage

I've designed a multi-phase, AI-assisted triage and routing framework for denial management — built on structured 835 ERA data and CARC-based classification logic that most health systems already have available but aren't fully leveraging.

Phase 1 addresses the three systemic failures that plague RCM teams at scale: manual triage that breaks under volume, no priority logic separating a $500 denial from a $500,000 one, and 835 data sitting idle while appeal decisions are made by gut.

The framework is designed to deliver immediate operational value using data you already have — no new infrastructure required. Additional workflow modules can be built on demand as Phase 2 contract data integration and professional claims workstreams activate.

Phase 1 · Acute Care / UB-04 · 835 CARC Classification
Phase 1

AI Triage & Routing — Defined & Ready

Acute care facility claims. UB-04 institutional billing. Three-layer triage model using 835 ERA CARC codes to classify, prioritize, route, and score every denied claim for appeal probability — automatically.

Phase 2

Contract Data Integration

Payer contract data layer unlocks automated timely filing logic, payer-specific appeal routing, and underpayment detection by comparing contract rates against 835 paid amounts.

Parallel

Professional Claims Workstream

CMS-1500 triage adapted for physician and specialist billing — deployed across eClinicalWorks, Athena Health, GE Centricity/IDX, and mid-market PM systems via API or HL7 interface.

On Demand

Additional Workflow Modules

The triage architecture is modular. New claim types, payer-specific logic, coding edits, and underpayment recovery workflows can be layered on top of the same foundational infrastructure.

1

Layer One

Dollar Segmentation & Escalation Routing

Every denied claim is tiered by total billed amount — not denied amount. Write-off zone under $100. Supervisor queue $100–$20K. Manager queue $20K–$100K. Director mandatory review above $100K. Dollar tier determines reviewer level before any other logic fires.

2

Layer Two

Payer Identification & Phase 2 Flagging

Claim is matched to its payer. Any claim requiring contract-specific logic is tagged with a Phase 2 dependency flag — surfacing it to the human reviewer with a structured instruction set so nothing falls through without a deliberate decision.

3

Layer Three

CARC-Based Denial Classification & Appeal Scoring

The 835 ERA CARC code classifies the denial type and drives appeal pathway logic. AI assigns an appeal probability score — High, Medium, Low, or Non-Appealable — built from 9+ months of historical 835 win-rate data. Not hardcoded assumptions. Real data.

Immediate Value

Runs on 835 ERA data, payer master, and clearinghouse logs — assets every health system already maintains. No new infrastructure required to activate Phase 1.

🔒
Human Authority Preserved

AI classifies, routes, and generates instructions. Humans make final decisions. Every write-off, appeal, and escalation is documented with timestamp, reviewer identity, and rationale — HIPAA-compliant by design.

🧩
Modular Architecture

The triage logic is a platform, not a one-time build. New claim types, payer rules, coding edit checks, and underpayment recovery modules can be activated on demand as the organization's needs evolve.

✉️
AI-Generated Appeal Letters

For cleared appealable claims, the workflow auto-populates appeal letters using patient demographics, 835 data, DRG and revenue codes, and CARC-specific letter templates — with payer portal, fax, or PDF output.

Discuss This Framework Available for implementation, consulting, or executive leadership engagements
Impact

Work that moved the needle

01

Epic Resolute Implementation

Health System Revenue Cycle Transformation

Led full-cycle Epic Resolute implementation across a multi-hospital health system — encompassing charge capture redesign, billing workflow optimization, and post-live AR stabilization. Achieved go-live on schedule with measurable reduction in days in AR within 90 days.

Platform: Epic Resolute · Scope: Enterprise
02

Denials Management Overhaul

Systematic Denial Reduction at Scale

Rebuilt a denials management function for a multi-site physician group, shifting from reactive appeal processing to proactive upstream prevention. Established denial trending, root cause workflows, and cross-functional accountability with coding and clinical documentation teams.

Result: Sustained reduction in denial write-off rate
03

Managed Care Contracting

Payor Strategy & Contract Renegotiation

Led renegotiation of a major commercial payor contract leveraging utilization data and outcome benchmarks. Repositioned the health system's negotiating posture and established a reimbursement monitoring infrastructure that surfaced underpayments systematically.

Impact: Improved reimbursement yield per encounter
04

RCM Integration · M&A

Post-Acquisition Revenue Cycle Integration

Directed revenue cycle integration for an acquired ambulatory network — harmonizing billing platforms, credentialing pipelines, and payor enrollment across multiple locations. Maintained collections continuity through transition while standardizing operations onto the parent system's infrastructure.

Platform: ResQ RCM · Scope: Ambulatory Network

Let's talk
revenue cycle.

Whether you're leading a health system through transformation, building an RCM leadership team, or navigating the AI-to-operations gap — I'd welcome the conversation.