Why Healthcare CFOs Need a Revenue Operating System

The healthcare revenue cycle too often resembles a game of whack-a-mole. 

Patient access, utilization management, coding, billing, denials management and accounts receivable teams all work to improve performance within their areas of responsibility. They may succeed individually while their broader system struggles to improve overall financial performance, because their siloed efforts are not aligned to achieve the optimal system outcome.

The costs of this misalignment are staggering. According to the Journal of the American Medical Association, routine administrative activities cost $200B+ in annual healthcare spending. Healthcare providers must navigate growing payer complexity, constant policy changes, workforce constraints and mounting pressure to improve financial performance.

As long as revenue cycle operations are designed to optimize individual functions, not the system connecting them, these activities will consume a growing number of resources and further distract providers from their core mission: quality patient care.

To solve this problem requires a different approach supported by a new technology architecture that unlocks the advantages and scale of AI.  We’ve taken that approach at R1—we call it a Revenue Operating System (ROS). An ROS acts as a connected operating layer between clinical and financial systems, orchestrating work to help healthcare organizations translate complex clinical reality into more accurate capture of acuity at lower cost and higher yield. 

So, how did we get here, and how can an ROS drive substantially improved outcomes and fundamentally transform the payer-provider relationship? Let’s explore.

The Revenue Cycle Is Essentially a Translation Problem

Every patient encounter generates clinical documentation across the care continuum. In many cases, a single patient encounter creates thousands of clinical, administrative and financial data points that ultimately support reimbursement.

To secure reimbursement, that information is translated into payer-specific language shaped by complex rules and contractual expectations. But healthcare doesn’t operate in a single reimbursement language. Every payer effectively speaks its own dialect, with unique documentation requirements, authorization rules, medical policies, reimbursement policies and adjudication practices. Adding to the complexity, these dialects are constantly changing throughout the year across hundreds of plans and a thousand payers. 

Typically, this translation process is divided across revenue cycle functions, with each team responsible for its own portion of the journey. As information moves through multiple handoffs, it becomes more difficult to identify where reimbursement leakage occurs. A denial may surface at the claim stage, though the underlying source issue occurred earlier in authorization, documentation or coding.

Consider utilization management, where assessing clinical accuracy at a point-in-time has traditionally been the primary focus. Though essential, clinical confidence that a patient meets the inpatient criteria does not guarantee reimbursement. 

The ROS approach is different. It continually evaluates medical necessity during the patient encounter, identifies potential documentation gaps, and integrates historical payer-specific medical necessity denials insights into utilization management decision making to optimize outcomes even as payer policies and behaviors evolve.

This leads to more optimal decisions that prevent downstream problems.  For example, in a retrospective analysis of a multi-state health system's open inpatient denial inventory, a common score-based utilization management tool classified 99% of denied inpatient accounts as safe for inpatient billing. When those same accounts were evaluated by Phare Utilization Management (Phare UM), only 69% were identified as low-risk, revealing significant denial exposure that went undetected. Phare UM also surfaced documentation-level risk insights across 41% of the denied accounts, highlighting opportunities to address reimbursement risk before claims were submitted.

The findings illustrate a growing challenge for healthcare organizations: clinical justification and reimbursement outcomes are not always aligned. To prevent denials, providers need systems that understand not only clinical criteria, but also how payer behavior, documentation quality and downstream reimbursement outcomes interact across the revenue cycle.

As a result, healthcare providers spend significant time addressing symptoms rather than preventing problems. Research cited by the American Hospital Association found that hospitals spend nearly $20 billion annually appealing claim denials, with more than half of that cost tied to claims that should have been paid upon submission.

These costs highlight the limitations of a reactive approach and reinforce the need for greater orchestration across the revenue cycle. Still, many organizations continue to address these challenges one function at a time, rather than treating the conditions creating them.

As healthcare organizations struggle with fragmented workflows, disconnected technologies and mounting administrative costs, the challenge is no longer generating more data or adding more tools. It's creating a system that can turn complexity into orchestrated action. 

Why Isolated Point Solutions Have Reached Their Limits 

To manage reimbursement complexities, healthcare providers have traditionally pursued two options: deploying point solutions in areas like coding, denials, utilization management, billing and reporting, and/or adding staff to divide the workload.

However, healthcare executives are finding it harder to achieve meaningful improvements through incremental fixes alone. Rather than simplifying information flow, a patchwork of technologies can ultimately make coordination more difficult. According to Experian Health's 2025 State of Claims report, nearly 8 in 10 healthcare providers use multiple solutions to gather claim submission information, creating duplication, inefficiencies and more opportunities for errors.

The challenge goes beyond disconnected technology to competing priorities across the revenue cycle. One revenue cycle function may focus on maximizing claim value. Another helps accelerate cash collection. Another may prioritize denial reduction or controlling labor costs.

Each function is important, but optimizing one can cause problems for another. For example, maximizing claim value may improve reimbursement accuracy but create downstream collection challenges that delay accounts receivable (AR) operations. 

The fundamental problem is that most point solutions are designed to optimize a single task or workflow. They lack visibility into the downstream consequences of their recommendations and cannot continuously learn from outcomes occurring elsewhere in the revenue cycle. As a result, healthcare providers often improve individual functions without improving overall financial performance.

This does not mean healthcare organizations need to replace everything at once. Most providers adopt new technology incrementally, focusing first on the workflows where they can drive the greatest operational or financial impact. The difference is whether those capabilities operate as isolated solutions or as part of a shared operating model.

With an ROS, organizations can begin with a targeted use case, then expand over time. Each solution connects to common data, intelligence, governance and operational expertise, creating greater visibility and coordination across the revenue cycle.

Organizations may start with a single workflow, but they are effectively docking into a broader ROS that continuously learns payer behavior, operational decisions and financial outcomes across the enterprise.

Why Systems of Record Can't Orchestrate Revenue Performance

Healthcare organizations already rely on critical systems such as EHRs, clearinghouses, and data platforms. Each serves an important purpose, but none were designed to orchestrate revenue cycle performance across the enterprise. EHRs document and coordinate care. Clearinghouses facilitate transactions. Analytics platforms surface insights. Yet reimbursement outcomes depend on thousands of interconnected decisions that span patient access, utilization management, coding, billing and denials management across many payers.

An ROS fills that gap by coordinating work across these functions, learning from both operational actions and financial outcomes, and continuously improving decision-making. R1’s decades of experience connecting decisions, actions and reimbursement results across the revenue cycle enables it to build AI agents that optimize not just individual tasks, but overall financial performance.

The Financial Outcomes That Matter Most 

R1’s Phare Operating System drives intelligence throughout the revenue cycle, helping decision makers understand where priorities compete and optimize around those tradeoffs to determine the best path forward. Phare OS uses AI to comb decades of real-world revenue cycle expertise to help healthcare providers transform fragmented processes into connected financial operations. It’s the only operating model capable of improving performance at the system level.

Each of these metrics reflects a different aspect of revenue cycle performance, but they are closely connected. For example, earlier identification of errors such as documentation gaps or authorization issues can reduce first-pass denials, while better visibility into payer behavior can help healthcare providers take action to accelerate reimbursement and lower administrative costs.

An ROS doesn’t simply connect workflows. It continuously learns from outcomes across every revenue cycle function and uses those insights to improve future decisions. Claims that are denied become signals that inform coding and documentation, helping prevent similar issues from recurring. As payer policies and regulatory requirements change, the system adapts, reducing the time staff spend researching updates and allowing them to focus on higher-complexity, higher-judgment work.

In the long run, unifying all revenue cycle functions into an ROS platform means healthcare providers can compound gains across tasks – rather than getting stuck in incremental improvements.

Building the Future of Revenue Cycle Performance

More tools won’t help Healthcare CFOs manage complexity. They need a system designed to eliminate it. As payer requirements, labor pressures and financial demands continue to grow, optimizing individual functions is no longer enough. The organizations that outperform will be those that connect processes, intelligence and decision-making across the entire revenue cycle.

A Revenue Operating System represents that next evolution: shifting revenue cycle management from a collection of tasks to a continuously learning, connected operating layer built to orchestrate work between clinical and financial systems that optimizes system-level performance.