Points of view

Top 5 HealthLeaders Exchange topics shaping revenue cycle.

At the October HealthLeaders CEO + CFO Exchange, health system executives kept coming back to the same challenge: there are plenty of worthwhile priorities, but only so much capacity to execute them well.

When every investment has a strong case behind it, the harder decision is where to focus and what to put on hold.

Revenue cycle tends to make the financial impact of these choices easy to see. Priorities that are poorly sequenced or under-resourced slow billing, increase rework, and delay reimbursement, while strong execution results in improved First-Pass Performance and more predictable financial performance.

Here are the top five takeaways from the event on where execution makes or breaks those results:

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1. Strategic priorities have to survive the execution test. | Execution Determines Value

‍A projected return is only as strong as the plan for delivering it.

Before saying yes to a new initiative, CEOs and CFOs should know what it will ask of teams, who can fix the underlying workflow, and whether the rollout will disrupt the work that keeps cash moving.

Take a new prior authorization tool, for example. Spotting payer requirements faster doesn't strengthen reimbursement if missing documentation and unresolved exceptions still land back in manual queues. A tool that finds problems but fixes none is just a messenger. An executable plan ties prior authorization to scheduling, documentation readiness, escalation ownership, and denial feedback, so the investment prevents authorization delays instead of reporting them.

Executives at the Exchange shared four conditions that separate an executable revenue cycle investment from another layer of work:

• The financial outcome is clearly defined in cash, reimbursement, margin, or cost-to-collect.
• The workflow owner can change the process where defects begin.
• Every team the workflow touches has agreed to the handoffs the change affects.
• Governance can prove the change removes rework after launch.

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2. Portfolio discipline protects workforce capacity and cash. | Priorities Protect Capacity

No one votes for an overloaded portfolio. It happens one reasonable yes at a time. 

Countless leaders at the Exchange described teams carrying more active work than they could execute. The same revenue cycle leaders, analysts, and IT resources support every initiative, so each new project slows the rest and pushes the return later than the business case promised.

A portfolio review makes that overlap visible. It lines up each initiative's expected cash and margin improvement against the demand it places on shared teams, workflow dependencies, and time to value. The result shows where capacity is already spoken for and which initiatives return the most for the capacity they use.

Capacity is the one budget line nobody can approve into existence. A good idea that starts a little later, with a team ready to carry it, can still deliver sooner than one launched into a team with no room.

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3. Revenue cycle investments are often fully funded but partially staffed. | Workforce Capacity Protects Cash

Approving the investment is the easy part. Finding the capacity to carry it through is harder. 

Executives at the Exchange were clear about the pressure on operational teams: constant reprioritization is driving burnout and leaving less capacity for new initiatives. The same teams keeping cash moving are often asked to learn new workflows, support the rollout, and handle whatever the technology cannot resolve.

The pressure adds up. When teams have to balance daily operations with implementation work, burnout rises, queues grow, and the expected return takes longer to show up. The investment can still succeed, but the organization pays more for the transition than leaders anticipated.

A stronger revenue cycle operating model plans for the workload created by the change. Deeper specialist coverage gives key employees room to focus and keeps work moving when volumes rise, payer requirements shift, or experienced team members are unavailable.

The takeaway for CEOs and CFOs is simple: funding the technology is only part of the investment. The larger decision is whether the organization has enough capacity to protect current performance while building what comes next. Funding the people and operating model behind the change reduces burnout, preserves cash during the transition, and creates the execution capacity needed to support future growth.

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4. AI should create value, not another queue. | AI Must Move Work

Artificial Intelligence (AI) creates financial value when it improves the economics of getting paid. Leaders should see faster claim readiness, fewer preventable denials, lower cost-to-collect, or more productive use of skilled teams. If AI identifies more issues but leaves the same manual work behind, it has improved visibility without improving financial performance.

CFOs can compare time to bill, denial rates, exception aging, manual touch volume, and labor cost before and after implementation. The value comes from strengthening the full path to payment, rather than optimizing one step while leaving the underlying cost elsewhere.

Faster detection only strengthens the return when it leads to quicker resolution, fewer downstream touches, and lower labor expense.

A practical revenue cycle AI review starts with First-Pass Performance. Measure whether more work is completed correctly before an edit, denial, appeal, rebill, or follow-up becomes necessary. The strategic objective is to turn AI into operating leverage, allowing the organization to handle greater revenue cycle complexity without adding cost.

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5. The 2030 portfolio can’t fund yesterday’s priorities. | 2030 Readiness Starts Now

‍Health system leaders can’t fund tomorrow’s priorities without making difficult decisions about today’s investments. 

A current investment shouldn’t be protected simply because it still performs its original function. CEOs and CFOs need to determine whether it improves financial performance across the enterprise. Leaders at the Exchange noted that the strongest investments connect enterprise revenue cycle data to action, reduce variation across facilities, and make reimbursement more predictable.

A 2030-ready portfolio requires executives to make two decisions with equal discipline: what to fund and what to stop funding. Continuing to protect investments that no longer strengthen cash flow, margin, or scalability limits the organization’s ability to execute higher-value priorities. 

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How Vee Healthtek turns priorities into executable results. | Vee Healthtek Supports Execution

‍Every priority competes for the same teams, so we start by showing which ones earn that capacity. We follow financial risk through the workflow to find where execution breaks down and rework begins. Practitioner-led analysis connects payer behavior with patient access, documentation, coding, claims, and A/R, so workflow changes target recurring causes. AI-enabled prioritization directs repeatable work to automation and complex exceptions to experienced teams, protecting reimbursement while preserving internal control.

A strong strategy begins with the workflow and ends with the financial result. Leaders who test investments for executability, remove lower-value initiatives, and measure First-Pass Performance will be most likely to protect current cash while building capabilities for the future. 

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Key Takeaways: | Key Takeaways

• Investment value depends on whether teams can execute change without weakening current cash performance.
• Portfolio review needs an explicit stop decision so lower-value work does not consume scarce capacity.
• Workforce capacity protects implementation quality and continuity across patient-to-payment workflows.
• AI earns its place when it moves risk to resolution and reduces rework, denials, or A/R aging.
• A 2030-ready portfolio connects enterprise priorities to first-pass yield and realized reimbursement.

The right revenue cycle partner protects the patient financial journey. | Start With Affordability

Healthcare providers should evaluate a revenue cycle management partner by asking a patient-centered question: Can this organization prevent avoidable financial harm while improving operational and financial performance? The answer requires more than promises about collections, automation, or staffing. A qualified partner should demonstrate how it establishes accurate coverage, estimates responsibility, prevents billing defects, connects patients with assistance, and resolves exceptions before uncertainty becomes a corrected statement or unaffordable balance.

The stakes are significant. A 2024 KFF analysis estimated that Americans owe at least $220 billion in medical debt; approximately 14 million adults owe more than $1,000. Meanwhile, a 2024 American Hospital Association report found that administrative costs represented more than 40% of hospital expenses, while commercial and Medicare Advantage care denials rose 20.2% and 55.7%, respectively, between 2022 and 2023. Partner selection therefore affects both institutional resilience and the patient experience.

Ten evaluation criteria reveal whether an RCM partner is patient-centered. | Evaluate Ten Capabilities

1. Coverage accuracy should come before collections. Patient access management, eligibility and benefits verification and insurance discovery should prevent avoidable self-pay classification and responsibility errors. Ask for eligibility accuracy, coverage-found rates, and related denials.

2. Authorization should protect access to care. Prior authorization workflows should identify requirements early, track payer decisions, escalate delays, and measure authorization-related denials and rescheduling.

3. Estimates should be explainable and reliable. Price transparency and patient estimates should combine known services, contracted rates, current benefits, and documented assumptions. Require estimate accuracy and variance reporting.

4. Affordability pathways should be built into clearance. Financial clearance and counseling should connect eligible patients with assistance, Medicaid screening, charity care, and suitable payment options before balances age.

5. Billing accuracy should be prevented upstream. Clinical documentation integrity, medical coding, and revenue integrity should reduce unsupported, missing, or duplicate charges. Ask how defects are intercepted before claims and statements.

6. Claims should be validated before submission. Claims editing and clean-claim validation should improve first-pass acceptance, while payment posting and reconciliation should allocate payer and patient responsibility correctly.

7. Patient communication should make action easier. Patient communication should be timely, plain-language, accessible, and consistent with HFMA’s 2024 Patient Financial Communications Best Practices, which connect a good financial experience with lower administrative cost, stronger results, and better patient decisions.

8. Technology should connect work, not fragment it. Revenue cycle execution systems and EHR integrations should connect EHR, payer, clearinghouse, workflow, and reporting data. Test exception visibility, data lineage, security, and human oversight.

9. Governance should expose causes and ownership. Open Accountability should define who owns an exception, when it escalates, and how learning returns upstream. A partner should show root-cause trends, corrective actions, and sustained results rather than activity counts.

10. Outcomes should unite patient and provider value. First-Pass Performance should reduce repeat touches and corrected bills while elevating patient experience, reducing cost to collect and accelerating cash.

A buyer scorecard turns promises into comparable evidence. | Score Operating Evidence

A credible evaluation tests evidence, governance, and fit. | Test Accountability

Ask partners to demonstrate three real workflows: an authorization exception, a changed estimate, and a denied claim transferred toward patient responsibility. Require each partner to show the data used, decision path, escalation, communication, correction, and root-cause feedback. Then validate reference-client results by care setting, payer mix, EHR, scope, and operating model. For example, this outsourced coding transition case study illustrates why disciplined transition governance and quality control matter when continuity and cash are at risk.

Score partners on measurable baselines and improvement commitments, not generic maturity claims. Useful measures include estimate accuracy, coverage discovery, authorization turnaround, eligibility and authorization denials, pre-bill interception, clean-claim rate, corrected statements, avoidable patient-balance transfers, inquiry resolution, financial-assistance screening, and cost to collect. Contract language should define data access, reporting cadence, escalation thresholds, patient communication standards, transition milestones, and ownership for corrective action.

Before contracting, examine how the partner will operate across each care setting. Enterprise health systems, ambulatory surgery centers, and physician practices and groups have different scheduling patterns, payer rules, coding complexity, patient-responsibility profiles, and integration constraints. Confirm that staffing, quality sampling, business-continuity planning, and governance reflect those differences. A strong partner should also explain which decisions remain with the provider, which are delegated, and how policy changes are translated into frontline workflows without disrupting patients.

The best partner does not promise to make every balance affordable. It helps the provider make every financial interaction more accurate, understandable, timely, and accountable. That operating discipline reduces rework, protects patient trust, and gives leaders a clearer path to transform revenue cycle performance without separating financial outcomes from the experience of the people receiving care.

At The Health Management Academy (THMA) Chief Revenue Cycle Officer Forum in Washington, D.C., one word connected conversations about turning Artificial Intelligence (AI) and workforce capacity into stronger performance: execution.

Today’s health systems have more ways to automate revenue cycle work, but technology doesn’t automatically improve cash flow. The financial return depends on whether rework is prevented, complex exceptions reach experienced people, and cleaner work carries through to payment.

The impact appears in denial volume, accounts receivable aging, cost-to-collect, and cash timing. Together, these outcomes determines whether technology investments strengthen forecast confidence and operating margin or create another layer of work to manage. 

Disciplined execution improves First-Pass Performance. Weak execution gives rework a head start.
 

Here are our top six lessons learned from THMA about effective execution across the revenue cycle: 

1. Fix the right problem first. | Fix the Right Problem

‍Strong execution starts by identifying where performance breaks down, then deciding whether technology is the right answer. Automation creates value when it removes the source of recurring errors or delays, rather than making a flawed process move faster. The highest-value opportunities have repeatable tasks, clear decision rules, and measurable financial impact. Complex exceptions still need experienced judgment. The goal is to apply automation where it can improve first-pass quality, protect reimbursement, and release capacity for higher-value work. 

2. Pair speed with quality. | Pair Speed with Quality

Productivity gains create value only when quality keeps pace. Automation may increase the number of accounts completed, but the benefit disappears when downstream teams have to correct the output. Speed creates capacity only when it reduces intervention instead of shifting responsibility to the next team.

Tracking coding accuracy, preventable denials, and cash timing shows whether added capacity improves financial performance or gives rework another place to land. When speed and quality improve together, productivity gains translate into lower cost-to-collect and more predictable reimbursement.
 

3. Put expertise on the exceptions. | Put Expertise on Exceptions

Automation creates the most value when it changes where people spend their time. Routine, rules-based tasks should move through technology, while experienced staff focus on exceptions where judgment protects reimbursement or prevents a costly delay.

In patient access, this means automating coverage checks while routing conflicting benefits, coordination-of-benefits issues and payer-specific conditions to experienced staff. The financial test is lower eligibility denial exposure and fewer touches per resolved account, not bot volume.

The leadership decision is where human judgment produces the greatest incremental reimbursement, not where automation can generate the most activity.

4. Govern what you intend to scale. | Govern What Scales

Anything designed to scale deserves governance before it gains momentum. Governance must define approved use cases, accountable owners, quality thresholds, and escalation paths. A model that performs well in one specialty may create risk in another because documentation patterns and payer rules differ.

A quarterly steering meeting cannot replace active control. Leaders need visibility into exception rates, manual overrides, denial outcomes, and financial variance by use case. Governance becomes meaningful when it stops weak automation from scaling and directs investment toward measurable cash protection.

5. Plan for change before it arrives. | Plan for Change

Revenue cycle requirements shift quickly, so leaders need to evaluate the roadmap as closely as current capability. Long commitments built around a static feature set can limit the organization’s response. An adaptable model preserves integration flexibility, establishes review points and requires a clear path from new functionality to operating outcomes. This gives health systems room to adapt without creating parallel workflows, disrupting performance, or rebuilding the technology foundation each time priorities change.

6. Reward resolved outcomes. | Reward Resolved Outcomes

Strong execution depends on measuring whether work reaches the right financial outcome, not how much activity a team completes. Automation adoption alone proves very little if accounts still require correction, escalation, or repeated follow-up before payment.

First-Pass Performance shifts attention to accounts resolved correctly across patient access, clinical documentation integrity, coding, claims, and denials. When incentives follow resolution, teams use technology to prevent rework instead of simply increasing throughput. 

The ROI appears in lower cost-to-collect, shorter accounts receivable cycles, and more reliable forecasting.

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Vee Healthtek builds accountability into execution.

‍The real test of execution is whether change holds across the revenue cycle and produces results leaders can see in cash, cost, and predictability. Vee Healthtek connects automation, workflow design, and practitioner judgment across the path to payment so execution stays tied to financial outcomes. This approach supports rework prevention while protecting the reimbursement evidence behind each claim.

Open Accountability keeps change tied to measurable results rather than completed tasks. Leaders can see whether intervention reduces repeated touches, strengthens denial prevention, and improves cash timing across the account population. The operating model provides scalable execution without separating technology from the people responsible for the outcome, helping health systems build revenue resilience as payer complexity increases. 

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Key Takeaways

• Execution creates value when it addresses the source of recurring defects instead of accelerating a flawed process. 
• Productivity gains strengthen financial performance only when quality keeps pace. 
• Technology should give experienced staff more capacity for exceptions where judgment can protect reimbursement. 
• Governance and an adaptable roadmap prevent weaker approaches from scaling as requirements change. 
• Measuring resolved outcomes connects operational capacity to lower cost-to-collect, shorter accounts receivable cycles, and more predictable cash.

Patient affordability begins long before a statement is mailed. | Why Controls Matter

The patient affordability-centered revenue cycle is the set of operational controls that protects patients from avoidable financial harm across scheduling, registration, coverage, authorization, documentation, coding, claims, and billing. It does not change the clinical price of care or the patient’s benefit design. It does improve whether the right account, coverage, responsibility, estimate, and assistance pathway are established before an inaccurate or unexpected balance reaches the patient.

The need is material. A 2024 KFF analysis estimated that Americans owe at least $220 billion in medical debt; about 14 million adults owe more than $1,000. A separate 2024 KFF explanation of surprise bills noted that billing or plan-processing mistakes can still cause patients to be charged more than they should owe. These findings make accuracy, clarity, and timely resolution patient-protection priorities.

Ten controls can prevent financial harm before the bill. | Ten Preventive Controls

1. Match the patient to the correct record. Registration quality should validate identity and demographics at entry. AHIMA reported in 2024 that 45% of large hospitals had difficulty accurately identifying patients through electronic health information.

2. Verify coverage and benefits early. Eligibility and benefits verification should confirm active coverage, benefit limits, deductibles, coordination of benefits, and authorization indicators before service.

3. Discover available coverage. Insurance discovery can identify coverage that prevents an account from being classified as self-pay unnecessarily.

4. Secure authorization before care. Prior authorization should surface payer requirements, documentation gaps, pending decisions, and service changes before they cause delays or non-covered balances.

5. Set a reliable expectation. Price transparency and patient estimates should combine benefit information, contracted rates, known services, and clear assumptions. Estimates should be updated when the care plan changes.

6. Screen for appropriate assistance. Financial clearance and counseling should connect eligible patients with financial assistance, charity care, Medicaid screening, or suitable resolution pathways before balances age.

7. Make the record claim-ready. Clinical documentation integrity and health information management support should resolve missing or ambiguous information before coding and billing.

8. Protect coding and charge accuracy. Medical coding, charge capture optimization and revenue integrity should ensure the claim reflects documented care without omissions, duplication, or unsupported charges.

9. Validate the claim and responsibility. Clean-claim validation should stop preventable defects before submission, while payment posting and reconciliation should ensure payer and patient amounts are allocated correctly.

10. Communicate and resolve responsibly. Patient communication and self-pay, charity care, and Medicaid screening should give patients understandable information, accessible help, and a clear route to resolution. HFMA’s 2024 best practices link a good financial experience with lower administrative cost, stronger financial results, and better patient decisions.

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A control dashboard makes patient risk and ownership visible. | Make Ownership Visible

Open accountability keeps prevention from becoming another checklist. | Measure Patient Impact

Controls work only when exceptions have an owner, an escalation path, and a feedback loop. Open Accountability makes performance visible without taking control away from the provider. When a corrected statement, denied claim, or changed estimate is traced to its source, teams can remove the failure mode instead of normalizing rework. First-Pass Performance then becomes practical: complete the work correctly at the earliest appropriate step so patients and staff do not repeat it later.

The economic context strengthens the case. The American Hospital Association reported in 2024 that administrative costs exceeded 40% of hospital expenses and that commercial and Medicare Advantage care denials rose 20.2% and 55.7%, respectively, between 2022 and 2023. Downstream appeals remain necessary, but prevention reduces the avoidable touches, delays, and uncertainty that affect both provider finances and patient confidence.

Patient-centered measures show whether the controls are working. | Build Upstream Resilience

Executives should review record-match accuracy, eligibility-related denials, authorization turnaround, estimate accuracy, assistance-screening completion, pre-bill defect interception, clean-claim rate, avoidable patient-balance transfers, corrected statements, inquiry volume, and time to resolution. These measures connect elevating the patient experience with reducing cost to collect and transforming revenue cycle performance.

Providers should review patterns by payer, facility, service line, and control owner. This outsourced coding transition case study shows how visible governance, rapid workflow stabilization, and quality control can protect continuity while improving financial resilience. The same discipline applies to patient affordability: find where harm enters, correct the account, and redesign the control so the defect is less likely to recur.

A patient affordability-centered revenue cycle converts the abstract goal of affordability into ten governable controls. It protects clarity before care, accuracy before billing, and access to help before a balance becomes a crisis. Most importantly, it gives healthcare leaders a practical way to improve patient trust while strengthening first-pass operational and financial performance.

Healthcare affordability starts before the patient receives a bill. | Affordability Starts Upstream

Revenue Cycle Management (RCM) can support patient affordability by confirming coverage, identifying financial assistance, producing reliable estimates, preventing billing errors, and resolving insurance responsibility before balances reach patients. It does not directly reduce the clinical price of care. It does, however, limit avoidable financial harm created when administrative work is incomplete, inaccurate, or delayed.

That distinction matters. A 2024 KFF analysis estimated that Americans owe at least $220 billion in medical debt; about 14 million adults owe more than $1,000. For healthcare providers, affordability therefore includes not only what care costs, but whether patients receive correct coverage information, understandable estimates, accurate statements, and timely help.

Administrative errors can become patient financial problems. | Errors Become Patient Costs

A patient’s financial journey begins at scheduling, not collections. Incomplete registration can lead to failed eligibility and benefits verification. Missing authorization can delay care or shift uncertainty toward the patient. Documentation gaps, incorrect charges, coding errors, payer edits, and posting mistakes can produce denials or balances that require investigation before anyone can explain what the patient truly owes.

The system cost is substantial. The American Hospital Association reported in 2024 that administrative costs represented more than 40% of hospital expenses, while commercial and Medicare Advantage care denials rose 20.2% and 55.7%, respectively, between 2022 and 2023. Each preventable exception creates rework for staff and uncertainty for patients. Better denials management and appeals matters, but preventing defects earlier is more affordable than repeatedly correcting them downstream.

Eight revenue cycle practices can protect affordability. | Eight Preventive Practices

Healthcare providers can strengthen the patient financial experience through connected controls across the revenue cycle:

• Capture accurate demographics and insurance information through consistent patient access management.
• Verify eligibility, benefits, deductibles, and coordination of benefits before care whenever possible.
• Use prior authorization workflows that surface requirements early and escalate exceptions.
• Provide patient-specific estimates with plain-language explanations of assumptions and uncertainty.
• Screen for financial assistance and appropriate payment pathways before avoidable balances age.
• Strengthen medical coding, clinical documentation integrity and revenue integrity so claims and statements reflect the care delivered.
• Validate patient responsibility before statements are released, then reconcile payments accurately through payment posting.
• Use clear, concise, correct communications aligned with HFMA patient financial communication guidance.

A simple affordability control dashboard makes accountability visible.

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Providers should measure what patients experience. | Measure Patient Impact

Traditional revenue cycle measures remain important, but affordability requires a patient-centered scorecard. Leaders should monitor estimate accuracy, eligibility-related denials, authorization-related delays, pre-bill error interception, corrected statements, avoidable patient-balance transfers, inquiry volume, financial-assistance screening, and time to resolution. These indicators connect elevating patient experience with reducing cost to collect and improving revenue integrity.

They also make ownership visible. With Open Accountability, every exception should have a named owner, a defined escalation path, and a feedback loop to the step where the defect began. Technology can support this discipline by connecting EHRs, payers, clearinghouses, and teams through revenue cycle execution systems such as RevAmp and reliable EHR integrations.

First-pass performance turns administrative work into patient trust. | From Rework To Trust

Affordability improves when providers stop treating every error as an isolated downstream task. First-Pass Performance means completing work correctly upstream so patients and staff do not repeatedly revisit the same coverage, authorization, coding, claim, or billing issue. It helps reduce revenue leakage, accelerate cash and protect patients from avoidable confusion at the same time.

The operational lesson is simple: follow the patient balance upstream. A provider that can identify why an inaccurate or unexpected balance was created can redesign the process that produced it. This case study illustrates how a health system used agentic AI eligibility verification to reduce preventable eligibility denials by 26% and saved $3.6 million per month in the process. More broadly, transforming the revenue cycle requires connected workflows, transparent measures, and accountability for outcomes, not only activity.

For executives, the priority is not a collection of disconnected projects. It is a governed operating model that links the front, mid, and back office around a shared view of the patient account. Monthly reviews should examine where estimates changed, why responsibility shifted, which statements were corrected, and whether the originating defect was removed. Teams can then distinguish unavoidable complexity from preventable variation, direct resources toward the highest-impact breakdowns, and verify that automation improves accuracy rather than merely moving work faster. This creates a practical bridge between affordability, operational resilience, and financial sustainability.

Healthcare affordability is larger than revenue cycle management. Yet revenue cycle leaders control many moments that shape whether patients understand, trust, and can act on their financial information. When those moments work correctly the first time, providers reduce rework while giving patients greater clarity before, during, and after care.

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Re-engineering revenue cycle for the AI era.

Artificial intelligence is moving into coding, clinical documentation, authorization, analytics, and other parts of the revenue cycle. But in my work with healthcare leaders, I continue to see the same tension: technology can accelerate a process without correcting the design beneath it.

That tension framed “Back to First Principles: Re-Engineering the Revenue Cycle for the AI Era,” a Vee Healthtek webinar presented in partnership with Becker’s Healthcare. I had the opportunity to moderate a conversation with Dawn Castro of Surgery Partners, Shannan Bolton of Stanford Health Care, and Peter Thompson of UF Health. Together, we explored what revenue cycle leaders must reconsider before scaling AI.

My clearest takeaway was this: AI value begins with redesigning the work. Leaders need to understand why a process exists, where defects originate, how users experience the workflow, and which outcomes the technology is expected to change.

Start with the work, not the technology. | Start With the Work

Revenue cycle improvement often begins with a familiar question: how can we make the current process faster? Shannan challenged that starting point. Before optimizing or automating a workflow, leaders should ask whether the work should exist in its current form and whether the process was designed to prevent problems or manage them after they occur.

“Our first question is not how the work is done today, but why it should exist at all.”  
Shannan Bolton, Stanford Health Care

Denial management was a useful example. A workflow designed primarily to recover dollars after a claim fails may become more efficient without reducing the source of the denial. Shannan also noted that a result that remains consistent over time can point to the design, rather than an isolated execution issue. This shifts the conversation from who made an error to what the process repeatedly produces.

Fit AI to operational reality. | Fit AI to Operations

Dawn’s experience reinforced why a promising capability can still miss its expected value. An authorization use case may look attractive at an enterprise level, but performance can vary across service lines, payers, states, systems and user groups.

“What can you actually do today? Let’s focus on those service lines instead of the big, pie-in-the-sky opportunities.”
Dawn Castro, Surgery Partners

Her team’s work showed the importance of observing how people use technology in practice. Seat rides exposed integration gaps, repeated work and the trust issues that develop when users have experienced unreliable tools. The lesson for me is that AI adoption is not a communication task added after implementation. It must be designed into the workflow from the beginning.

Peter shared a related example from clinical documentation integrity. When an initial implementation did not sufficiently reflect clinicians’ day-to-day experience, the organization stepped back and involved clinician work groups in shaping the reimplementation. The technology had to fit the people and the work, not the other way around.

Move prevention upstream. | Move Prevention Upstream

The panel also returned to the need to move attention earlier in the revenue cycle. Recovery work will remain necessary, but leaders should not judge performance only by how effectively teams resolve downstream defects.

“There is a lot that we can do to prevent things from occurring in the first place.” 
Peter Thompson, UF Health

Peter described denial-prevention work groups that examine root causes and look for earlier intervention points. This idea connected with the measures discussed across the panel: revenue leakage, first-pass payment, yield, avoidable denials, speed to payment, and the percentage of accounts requiring human intervention. Each offers a different view, but all help leaders see whether redesign is reducing avoidable work or simply moving it faster.

A first-principles sequence for revenue cycle AI.

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Redesign roles and oversight. | Redesign Roles and Oversight

AI also changes the work people perform. Peter described a shift from completing tasks to auditing AI-generated output. That shift requires skills in exception management, quality review, and identifying when technology is not performing as expected.

“With AI, we’re moving people from being doers to being auditors.”
Peter Thompson, UF Health

Shannan discussed roles focused on automation leadership, workflow review, and post-launch monitoring. Dawn extended the point to product ownership, RFP discipline, and technology-vendor management. These are not supporting activities around AI. They are part of the operating model required to govern it with open accountability.

Retire low-value work. | Retire Low-Value Work

Re-engineering is also about deciding what to stop. Shannan described efforts to remove duplicate work queues, manual reconciliations, low-value reviews, and overlapping tools. The objective is not consolidation for its own sake. It is to create a less fragmented environment in which teams can act on insights instead of maintaining unnecessary activity.

What I would ask revenue cycle leaders to consider. | Leadership Takeaways

• Does the work still need to exist in its current form?
• Is the AI use case aligned with the users, service lines, payers and systems it will affect?
• Are we preventing avoidable defects or becoming faster at recovering from them?
• Who owns adoption, auditing and performance after the technology goes live?
• Which outcomes will show that the operating model has improved?

The organizations best positioned to scale AI will be those willing to question the work before automating it, involve the people closest to the process, retire unnecessary activity and make performance visible. That is the work behind an AI-ready revenue cycle.

Underpayment visibility is not underpayment recovery.

Finding underpayments is only half the job. Recovering the revenue requires a different level of execution. Teams must validate each shortfall, appeal within payer deadlines, and follow the account through corrected payment. With the American Hospital Association reporting $130 billion in Medicare and Medicaid underpayments absorbed by hospitals in 2023, payment accuracy belongs inside margin protection and cash forecasting.

Payer contract underpayment recovery translates contract terms into expected reimbursement, compares expected and actual payment, pursues supported variances, tracks recovered cash, and corrects the workflow behind repeat loss. Revenue leakage falls only when contract intelligence and account resolution operate as one system. The first challenge is distinguishing a valid, recoverable underpayment from a variance that only appears to represent revenue.

Variance identification creates exposure, not recovered revenue. | Why Exposure Stays Theoretical

A variance report can overstate the value available for recovery. Some differences reflect valid contract provisions, timing, or data quality rather than payer error. A credible revenue integrity program separates gross exposure from underpayments supported by the contract, giving finance a more defensible view of expected recovery.

Validation then connects the contract to the payment received. Reliable payment reconciliation and accurate adjustment data help leaders determine which variances warrant action. Without this discipline, teams spend time on false positives while valid underpayments move closer to write-off.

A recovery chain turns contract terms into cash. | Build the Recovery Chain

Recovery requires one accountable path from identified variance to corrected payment. Contract terms must support the expected reimbursement, each claim must be validated against the payment received, and valid shortfalls must move into action before appeal rights expire.

Teams first normalize contract terms so expected reimbursement can be compared consistently with actual payment. They then validate each claim line, prioritize recovery work by value and deadline, submit supported appeals, and track account resolution until the payer corrects the payment or the organization reaches a supported closure.

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Use the recovery waterfall to find where revenue is getting stuck. | Find Where Recovery Stalls

‍Compare the dollar value at each stage. The largest gap shows where recoverable revenue is stalling and where leadership should act:

Leadership should review these gaps by payer, contract, service line and variance type. A large gap between identified and validated dollars may reveal unreliable contract data or overstated opportunity. A gap between validated and appealed dollars points to documentation, capacity or deadline failures. A gap between appealed and recovered dollars calls for stronger payer follow-up and escalation. Comparing recovered cash with cost to collect shows whether the program created net financial value. Recurring underpayments should be monitored separately to confirm that the source of leakage was corrected.

Once leaders know where recovery is stalling, the next decision is which accounts should receive attention first.

Prioritization protects appeal rights and recovery yield. | Prioritize Recoverable Cash

‍‍The largest balance is not always the best recovery opportunity. Prioritization should weigh recoverable value, time remaining to appeal, strength of contract support, payer behavior, and effort required. This directs specialized capacity toward accounts most likely to improve near-term cash flow instead of allowing high-value, time-sensitive claims to age behind weaker opportunities.

Recovery results can also reveal broader patterns in payer performance. Recurring mispricing, slow appeal responses, and service-line variances show where reimbursement is breaking down and which issues require escalation. These insights give leaders stronger evidence for payer reviews, contract renewals, and decisions about where recovery resources will produce the greatest return.

Root-cause correction stops the same loss from returning. | Correct Recurring Leakage

Recovery restores the immediate cash, but recurring underpayments show that the source of the loss remains. Modifier-related patterns may point to coding logic, while repeated contractual adjustments may expose outdated payer terms, posting rules or billing configurations. Each recurring variance should be assigned to an accountable owner with a defined correction and follow-up measure.

Revenue integrity leaders should then track whether the same variance declines after the change. This closes the loop between recovery and prevention. Without that accountability, teams may repeatedly recover the same lost revenue while absorbing avoidable research, appeal and follow-up costs. The goal is not only to collect the missed payment, but to improve the accuracy of future reimbursement.

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Vee Healthtek connects recovery to prevention. | How Vee Healthtek Supports

Contract compliance becomes financially meaningful only when modeled terms drive account action and resolved accounts feed process improvement. Identified exposure informs where to look; validated underpayments establish what is defensible; recovered cash proves what the program delivered. This progression gives finance a cleaner basis for cash forecasts, reserve decisions, and payer performance review.

Vee Healthtek follows payer variance from contract logic through posted cash, keeping each action tied to the evidence supporting recovery. Practitioner-led review works within defined workflows, while AI-powered execution directs attention toward accounts with the strongest combination of value, urgency, and recoverability.

Open Accountability keeps recovered cash, rework, and prevention visible in the same operating cadence. Leaders can see whether each intervention improves reimbursement predictability and reduces repeat loss. The approach can scale across enterprise health systems while preserving provider authority over contracts and escalation decisions.

Key Takeaways

• Variance identification measures exposure; cash posted and reconciled measures realized value.
• Claim-line validation needs versioned contract logic, accurate remittance data, and source evidence.
• Prioritization must balance recoverable value with deadline, confidence, payer behavior, and effort.
• Root-cause correction converts one-time recovery into stronger future reimbursement yield.
• Operating-model decisions need to test execution depth, accountability, and prevention capability.

Payment can look complete while revenue remains missing. | Why Paid Claims Hide Revenue

The claim says paid. The contract says otherwise.

Repeated across a high-volume contract, a modest shortfall becomes a material financial loss. Because the claim was paid, the variance can bypass denial reports and traditional exception queues, allowing the same pricing error to weaken reimbursement across service lines and reporting periods.

Finance leaders need a reimbursement variance assessment that converts claim-level differences into enterprise exposure and directs action toward the most recoverable value. Measuring these gaps alongside claim volume, recurrence and recovery deadlines allows finance leaders to quantify the full exposure, distinguish isolated errors from systemic patterns and prioritize the revenue most likely to be recovered.

Contract leakage stays hidden when payment is treated as proof. | Paid Claims Versus Denials

Underpayments can go unnoticed because the claims were paid and closed rather than denied. Once the balance adjusts, the account leaves active work queues, even when the remittance reflects an incorrect rate, bundling rule, modifier treatment or contractual adjustment. A strong payer contracting process has to test whether cash matches the agreement instead of treating remittance as evidence of accuracy.

Margin pressure makes payer friction a two-sided financial problem: hospitals lose revenue when payments fall short and spend more trying to recover it. The American Hospital Association reported that hospitals spent an estimated $19.7 billion in 2022 overturning denied claims and absorbed $130 billion in Medicare and Medicaid underpayments in 2023. The financial impact extends beyond missing reimbursement to the added cost of collecting revenue already earned.

Expected reimbursement creates the baseline for every comparison. | Six Leakage Categories

Start where the financial stakes are highest: contracts with significant revenue, claim volume and recurring payment discrepancies. Then calculate what each claim should have paid under the contract terms in effect on the service date. Connecting this expected amount with coding, charging and billing data helps analysts distinguish payer errors from issues in the underlying claim. Strong revenue integrity keeps recovery efforts focused on valid payment gaps.

These inputs define the minimum baseline for expected reimbursement:

• The executed contract version and effective dates.
• The service, code, modifier and site-of-service combination.
• The payer policy and remittance logic applied to the claim.
• The actual allowed amount, payment and contractual adjustment.

Model validation is as important as model construction. Sampling should reconcile calculated expectations to known accurate payments and involve medical coding or charge capture expertise when clinical or billing details can change reimbursement. This limits false positives and prevents analysts from creating rework around variances the contract supports.

Claim-level variance becomes useful when it is scaled. | Small Variances Become Material

An individual difference gains executive meaning only after the organization estimates how often it repeats. Use this formula:

Average payment shortfall × eligible claim volume × incidence rate = Estimated revenue exposure

• Average payment shortfall: Average difference between expected and actual reimbursement for validated underpaid claims. 
• Eligible claim volume: Total number of similar claims that could contain the same payment issue. 
• Incidence rate: Percentage of reviewed claims where the shortfall occurred. 
• Estimated revenue exposure: Projected value at risk, not guaranteed recoverable revenue.

Segmenting results by payer, service line, procedure, modifier and location shows where exposure concentrates. Teams can then connect recurring patterns to payment posting, clean-claim validation and claim submission. This reveals whether the variance reflects payer adjudication, contract-model logic or an upstream claim defect.

A simple exposure framework turns variance into a decision. | Five Contract Performance Questions

This framework shows how claim-level findings roll into an enterprise estimate.

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Recovery priorities require more than the largest variance.

Dollar size alone can misdirect effort. A large discrepancy with weak contractual support or an expired filing window may yield less cash than a modest, recurring variance with clear evidence. Underpayment recovery should rank opportunities by total exposure, recoverability and time remaining, then route validated disputes before deadlines narrow.

How should CFOs prioritize payer contracts for review? Begin with contracts that combine high net revenue, high claim volume, complex reimbursement terms and repeated payment variances. A small variance in a high-value contract generally creates greater financial exposure than a large but isolated discrepancy in a low-volume agreement.

Prioritization becomes stronger when leaders also examine the labor required to recover each dollar. Accounts receivable follow-up and denials and appeals data can reveal payer response times, documentation burdens and escalation patterns. This converts gross exposure into a more realistic view of recoverable value and cost-to-collect.

Root-cause ownership protects future reimbursement. | Follow Cash to Source

‍Recovering an underpayment addresses the immediate cash loss, but greater financial benefit comes from identifying why the shortfall occurred and correcting the workflow before the same issue affects more claims. Contract configuration errors, missing modifiers and incorrect adjustment logic require different responses, but each finding should lead to a specific owner and corrective action. Applying these lessons to future claims strengthens first-pass performance and prevents teams from repeatedly recovering the same revenue.

Leaders can then monitor whether the correction improved payment accuracy and whether the shortfall continues across subsequent claims. Connecting this analysis to revenue leakage prevention shifts the measure of success from cash recovered once to revenue protected across future claim volume.

Vee Healthtek converts payment variance into accountable action. | Build Revenue Resilience

Finding the exposure is only the first step. Recovery depends on confirming which payment gaps are valid, determining which opportunities warrant immediate action and tracing recurring shortfalls back to their source. The assessment becomes more valuable when its findings guide both near-term recovery and workflow changes that improve payment accuracy across future claims.

Vee Healthtek follows payment variance from contract terms through remittance to identify where expected reimbursement breaks and how much value the pattern places at risk. Practitioner-led analysis validates recoverability, shapes work around payer behavior and connects findings to workflow updates that improve reimbursement predictability without creating another layer of disconnected review.

AI-enabled prioritization directs attention toward high-value, time-sensitive opportunities while scalable execution supports recovery across payer and service-line inventories. Outcome-based governance shows whether interventions accelerate cash, reduce cost-to-collect and prevent repeat leakage. A physician enterprise example demonstrates how a learning system can reduce accounts receivable (A/R) while hardening claim logic, reinforcing the value of pairing recovery with prevention.

Key takeaways | Key Takeaways

• A closed claim can still contain a recurring payment variance.
• Expected reimbursement must reflect contract, code, modifier and site-specific logic.
• Exposure equals average variance multiplied by affected volume and recurrence rate.
• Recovery priority combines value, recoverability, labor and filing-window risk.
• Root-cause ownership turns one-time recovery into stronger future reimbursement.