RCM REPORT
Payer friction, reimbursement pressure, denials, underpayments, and rising operating costs are increasing the financial consequence of disconnected revenue cycle work. Provider organizations need a more connected RCM model to protect cash flow, yield, and margin predictability.
8-Minute Read | June 4, 2026
INTRODUCTION
Revenue cycle performance has become a test of financial resilience.
As margin pressure, regulatory changes, and reimbursement complexity intensify, provider organizations can no longer rely on incremental productivity gains to improve operations or reactive cost-containment to protect cash flow. The operating environment is changing faster than the traditional RCM model can support.
The next phase of RCM maturity will be defined by connected systems and performance across the revenue cycle.
McKinsey describes this transition as a “structural shift” in RCM, requiring “integrated revenue excellence across front-end, middle, and back-end processes to bridge administrative, clinical, strategic, and technological domains.” Its 2025 survey of 215 U.S. hospital and health system leaders found that payer dynamics, regulatory shifts, and margin pressure are reshaping how organizations invest in RCM technology, services, and operating models.1
Revenue cycle performance now depends on how well the organization can see risk before it becomes leakage; connect work across access, authorization, documentation, coding, billing, denials, underpayments, A/R, and patient collections; and apply automation with enough governance to link insight to action.
WHY NOW
Provider organizations once had more room to improve RCM performance through staffing adjustments, workflow optimization, and targeted technology upgrades. That margin for incrementalism has narrowed.
Revenue cycle leaders are now managing financial performance under compounding pressure in an environment where more risk is created outside their direct control.
The issue is not the presence of any single pressure point. It is the cumulative effect on cash, yield, cost to collect, and forecast confidence.
RCM underperformance is more expensive when provider economics are already strained.
The American Hospital Association reports that Medicare reimbursed hospitals just 83 cents for every dollar spent in 2023, contributing to more than $100 billion in underpayments. Hospitals absorbed $130 billion in underpayments from Medicare and Medicaid in 2023 alone, with those shortfalls growing an average of 14% annually between 2019 and 2023. AHA’s "2026 Costs of Caring" report also notes that total hospital expenses grew 7.5% in 2025, more than twice the rate of hospital price growth over the same period.2
Kaufman Hall’s "January 2026 National Hospital Flash Report" shows the same pressure in operating performance: hospital operating margin declined 20% month over month and 17% year over year, while bad debt and charity care per calendar day increased 40% compared with January 2025.3
These pressures reduce tolerance for preventable leakage. Delayed cash, underpayments, avoidable write-offs, and documentation gaps now carry a greater financial consequence because they land on top of reimbursement shortfalls and elevated operating costs.
RCM has become a lever for liquidity, margin protection, and planning confidence.
McKinsey’s survey shows payer dynamics are becoming a direct source of financial deterioration. More than 65% of surveyed leaders anticipate negative financial impacts from H.R.1, with respondents also expecting increases in denials, A/R days, self-pay bad debt and uncompensated care, and patient out-of-pocket exposure.1
That pressure is already visible in cash timing. McKinsey found that 78% of respondents attributed at least 10% of A/R lengthening to payer-related causes such as pending medical records, disputed authorizations, and appeal backlogs. Escalated reimbursement issues took 36 days to resolve on average, with only 43% resulting in a favorable outcome.1
The burden is also shifting in complexity. Becker’s Hospital Review, citing Kodiak, Experian Health, and Aspirion data, reported that initial claim denial rates reached 11.81% in 2024, while medical necessity denials rose 5% and additional information requests increased 5.4% — evidence that payer scrutiny is moving deeper into documentation, clinical validation, and payment integrity review.4
Working claims faster is insufficient when payer-driven risk is identified too late.
Health systems need earlier visibility into payer friction, stronger denial prevention, tighter documentation and coding integrity, and recovery insights that flow back into upstream workflows.
Recent industry data reinforces how much capacity denials and underpayments now consume. In Experian Health’s 2025 "State of Claims" survey, 41% of providers reported denial rates of 10% or higher, while 68% said submitting clean claims is more challenging than it was a year ago. The capacity burden is just as clear: 43% of providers reported being understaffed, and 90% of claim denials still require at least some human review before resubmission.5
The financial impact is also growing. According to the AHA, hospitals spent nearly $18 billion in 2025 on overturning claims denials alone. All told, the AHA estimates hospitals spent $43 billion in 2025 trying to collect payments insurers owe for care already delivered — work driven by prior authorization, claims denials, repeated documentation requests, and evolving billing and coverage rules.2
Incremental productivity gains are critical, but they cannot carry the full burden. Health systems need an RCM operating model that can manage compounding pressure across the full cycle: connect prevention and recovery, prioritize work by financial impact, and translate insight into action before delays become write-offs.
THE NEW RCM OPERATING MODEL
Revenue cycle performance is shaped by a chain of dependencies. Front-end access breakdowns create downstream denials, delays, rework, and patient friction. Mid-cycle documentation and coding gaps weaken revenue integrity, slow bill drop, and increase compliance exposure. Back-end denials, underpayments, and aging A/R trap cash and increase cost to collect.
A connected performance model manages those dependencies as part of one operational and financial system.
Front-end, mid-cycle, and back-end functions still require distinct areas of expertise, but they operate from shared intelligence, shared performance priorities, and a common view of revenue risk. Access and authorization teams need visibility into the downstream denial patterns created by front-end breakdowns. Coding and documentation teams need insight into payer behavior, clinical denial trends, and reimbursement risk. Back-end teams need better prioritization so they can focus skilled resources on the work most likely to affect yield, cash, or write-off exposure.
A connected operating model has five requirements.
Health systems need to identify access, authorization, documentation, coding, denial, underpayment, and A/R risk before those issues become delayed cash or write-offs. The earlier the signal, the greater the opportunity to prevent leakage before recovery becomes the only option.
Eligibility and benefits verification, prior authorization, claim submission, attachments, claim status inquiry, remittance advice, and claim payment operate as linked steps in the administrative process.6 Each step can introduce friction that affects downstream performance. A more integrated model helps teams understand where breakdowns originate and how to correct them upstream.
RCM teams have more work than they can reasonably treat with the same level of urgency. Prioritization has to reflect financial consequences. The highest-value work is not always the oldest account, the easiest account, or the next item in the queue.
Automation should reduce avoidable manual effort, accelerate repeatable actions, and improve consistency. It also needs defined workflow logic, escalation pathways, quality controls, and compliance standards. Automation creates value when it informs execution against financial outcomes.
Clinical denials, coding interpretation, payer escalation, documentation integrity, and exception-based follow-up often require judgment, context, and domain knowledge. Technology should surface and organize the work, but expert review remains critical where financial, clinical, or compliance risk is material.
Revenue excellence now depends on disciplined investment, stronger denial prevention infrastructure, tighter vendor governance, and scalable platforms that improve yield and cash flow.¹ The strategic point is larger than any one capability. To turn revenue cycle activity into financial outcomes, providers need an RCM model that can connect risk signals, workflow execution, automation, and human expertise across the full cycle.
What the RCM structural shift means for executive leadership
Revenue cycle performance is now a shared leadership mandate. The shift to a connected RCM model changes what finance, operations, and technology leaders need to control.
CFOs and financial leadership
Protect cash, margin, and predictability. Revenue cycle performance now affects liquidity, working capital, capital planning, and enterprise resilience. CFOs need visibility into where revenue is delayed, denied, underpaid, or written off — and confidence that improvement efforts will produce measurable financial outcomes.
Revenue cycle executives
Move from reactive work to connected execution. RCM leaders need earlier risk signals, smarter work prioritization, stronger denial prevention, and feedback loops that connect front-end, mid-cycle, and back-end performance. The goal is to improve yield, speed, and consistency without simply asking teams to do more.
CIOs and digital transformation leaders
Make technology accountable to the work. AI and automation need to fit the operating environment, support governance, and reduce execution burden. CIOs need approaches that work with existing systems, limit vendor sprawl, and connect technology investment to measurable operational and financial performance.
AI has become central to any RCM conversation because revenue cycle work is data-intensive, pattern-driven, and exception-heavy. The use cases are real. So are the implementation challenges and execution risk.
McKinsey found that AI and advanced technologies are moving up the priority list, with 51% of leaders citing them as focus areas in 2025, up from 33% in 2024. Everest Group found similar momentum, with 85% of surveyed senior healthcare executives and RCM leaders expecting AI, gen AI, or agentic AI to improve RCM efficiency, and 51% actively testing or considering RCM use cases.7
According to Adonis’ 2026 RCM research, the strongest interest is concentrated in the functions with the clearest financial pressure: 66% of respondents identified automated denial follow-up and resolution as a “very important” AI capability for their 2026 RCM strategy.5
These findings do not support an AI-first strategy. They support a performance-first strategy in which AI improves the timing, precision, and consistency of revenue cycle action.
The most valuable use cases are practical: detecting payer patterns, flagging documentation risk, prioritizing high-value work, identifying likely denial causes, accelerating appeal development, supporting coding accuracy, and reducing avoidable manual touches.
In a mature operating model, AI does not sit outside the workflow as a separate analytics layer. It informs the next action inside the work itself.
It’s an essential distinction. Many provider organizations have existing dashboards, reports, queues, and analytics tools. The gap is operational translation — the distance between insight and execution. A model that produces insight without changing action will not materially improve cash, yield, or cost to collect. An intelligence-led RCM model moves teams from knowing a problem exists to acting on it quickly, consistently, and with appropriate governance.
AI also needs clear operational boundaries. Revenue cycle leaders should understand where automation can make reliable decisions, where it should recommend action, and where human review is required. Clinical, coding, regulatory, payer, and patient-facing workflows carry different levels of risk. Governance should be specific enough to define escalation rules, audit requirements, quality controls, performance measures, and ownership.
The most credible AI strategies will be tied to near-term operating value, focusing on specific challenges within broader RCM processes, using ROI benchmarks, and demonstrating credible nine- to 12-month impact to sustain internal support.1
Most health systems can’t rebuild their RCM infrastructure in one motion. They operate within existing EHR environments, payer processes, staffing models, vendor relationships, budget constraints, and competing priorities. The practical path is to start where financial pressure is most material while building toward a more connected operating model.
This is the case for modular, integrated adoption. Organizations may begin with a specific control point: access and authorization, documentation and coding, denial prevention, underpayment management, A/R recovery, or patient financial engagement. The value depends on whether each improvement strengthens the broader system.
Without integration, modular adoption can become another source of fragmentation. A new tool, workflow, or vendor may solve a local problem while making enterprise performance harder to govern.
McKinsey’s research supports this direction. Its analysis notes that market dynamics favor scaled platforms that integrate services and automation, and that organizations are prioritizing the same functions where revenue pressure is most acute: denials, A/R follow-up, coding, and eligibility and authorization. McKinsey also notes that half of surveyed leaders plan to pursue modular, integrated solutions that can be adopted over time and connected into a unified system.1
The starting point should reflect the organization’s revenue risk profile and operating capacity, but each step should contribute to a more connected performance model. One health system may begin with denials and underpayments, where the cash impact is visible. Another may focus on documentation and coding integrity to strengthen claim readiness before billing.
The principle is connection. Denial prevention should inform access, documentation, and coding workflows. A/R recovery should expose root causes that can be addressed upstream. Each capability should improve the next decision, the next workflow, and the next financial result.
ACCOUNTABILITY
Despite increased investment in automation, external partnerships remain critical to revenue cycle performance. McKinsey found that only 6% of surveyed leaders plan to reduce outsourcing because of technology, while 60% expect to change their outsourcing approach over the next two to three years.1
These key data points reflect a broader change in the nature of RCM partnerships. Health systems still need capacity, technology, workflow expertise, and specialized execution. They also need partners that can help absorb operational risk, reduce execution burden, and build toward a more connected RCM model over time. But, successful engagements should not be defined by added labor or deployed tools.
Capability is the baseline. Accountability is the differentiator.
RCM partners should be evaluated by their ability to contribute to performance, stand behind outcomes, and share in the risk and reward. A partner engaged to improve a revenue cycle function should be accountable for the financial outcomes in that area.
Shared accountability can take several forms: performance-based KPIs, defined escalation processes, governance cadences, transparent reporting, gainsharing models, downside risk provisions, or contractual commitments tied to specific outcomes. The structure will vary by organization, scope, baseline performance, data quality, and operational control. The principle is consistent. Accountability should be visible in how work is governed, how performance is measured, and how commercial terms are structured.
DECISION LENS
The shift to a connected RCM model should begin with a clear view of where financial risk is created, where work breaks down, and where better intelligence could change the outcome. Leaders can use the following questions to guide planning.
1. Where is revenue risk first created?
Identify whether the most material risk originates in access, authorization, documentation, coding, payer behavior, underpayment, follow-up, or patient collections.
2. Which workflows create the greatest downstream cost?
Focus on the breakdowns that produce denials, rework, delayed cash, avoidable write-offs, compliance exposure, or patient friction.
3. Where does the organization have visibility without action?
Many teams can see problems before they can act on them. Leaders should identify where insight fails to trigger workflow changes, ownership, escalation, or prevention.
4. Which work should be automated, prioritized, or escalated?
Repeatable pattern-based work should be evaluated for automation. High-value or high-risk work should be prioritized. Complex clinical, coding, payer, or compliance issues should be routed to expert review.
5. Where should accountability be formalized?
Accountability should be reflected in KPIs, operating cadence, reporting, governance, and contracts. Leaders should define which outcomes matter, who owns them, and how performance will be measured at each control point and across the revenue cycle.
These questions help leaders distinguish between technology adoption and operating model change. Adding tools without changing execution logic will compound complexity. The goal is a revenue cycle model that can detect risk earlier, act faster, learn continuously, and improve financial performance over time.
WHAT’S NEXT
The revenue cycle has become a financial resilience mandate because the environment around it has changed. Payer friction, reimbursement pressure, regulatory change, labor constraints, and rising patient responsibility are increasing the financial cost of every delay, denial, underpayment, documentation gap, and disconnected workflow.
Provider organizations cannot manage this pressure through isolated improvements alone.
The new RCM model has to connect the work across the full cycle, identify risk earlier, apply intelligence inside the workflow, and align execution to measurable financial outcomes.
That shift also changes what health systems should expect from partners. Capacity and technology are vital, but they are no longer enough to support necessary transition. The stronger standard is accountability: partners that can meet the organization where pressure is greatest, improve the outcomes they are engaged to improve, and share risk and reward as the work scales into a more connected performance model.
The strategic case for change is financial control. Health systems that build a more connected, accountable RCM model will be better positioned to protect cash flow, reduce leakage, improve yield, and create more predictable revenue performance in a more complex reimbursement environment.
Save a copy of the report to share with finance, revenue cycle, operations, and technology leaders across your organization.
Omega Healthcare helps health systems move from fragmented revenue cycle effort to connected, accountable financial performance.
Our model brings together deep RCM expertise, operational execution, governed automation, and outcome-focused accountability to help provider organizations address revenue cycle pressure where it is most material — then expand into a fully connected, intelligence-led revenue cycle over time. The result is improved performance across cash flow, leakage, revenue integrity, cost to collect, and financial predictability.
Sources
[1] McKinsey & Company. Healthcare revenue cycle management at a strategic turning point: Survey insights. April 2026. https://www.mckinsey.com/industries/healthcare/our-insights/healthcare-revenue-cycle-management-at-a-strategic-turning-point-survey-insights
[2] American Hospital Association. Costs of Caring: Challenges Facing America’s Hospitals as They Care for Patients in 2026. March 2026.
[3] Kaufman Hall. National Hospital Flash Report: January 2026 Data. January 2026. https://www.kaufmanhall.com/insights/research-report/national-hospital-flash-report-january-2026-data
[4] Becker’s Hospital Review. Clinical Denials: “Not a Human-Addressable Problem Anymore at This Scale.” April 2026. https://www.beckershospitalreview.com/academic-medical-center/finance-academic-medical-center/clinical-denials-not-a-human-addressable-problem-anymore-at-this-scale/
[5] Experian Health. The State of Claims 2025: Rising denial rates, AI and automation. September 2025. https://www.experian.com/blogs/healthcare/state-of-claims-2025/
[6] CAQH. 2025 CAQH Index Report: Recovery by the Numbers: Administrative Resilience After a Systemwide Disruption. April 2026.
[7] Everest Group. Realizing the Promise of Tech-Enabled, AI-Driven Revenue Cycle Management: Outsourcing in the New Era. March 2025. https://www.omegahms.com/resources/default/everest-report/
© 2026. All rights reserved.