Blog|Articles|January 8, 2026

The hidden revenue crisis in health care: Why billing accuracy remains an illusion

Author(s)Dalton Han
Fact checked by: Todd Shryock
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Key Takeaways

  • Healthcare billing complexity, especially with CPT codes, leads to inefficiencies and revenue loss, impacting financial and clinical performance.
  • Claim denials are a major source of revenue leakage, often neglected due to their complexity and the pressure on billing teams.
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Fixing the billing problem isn’t just about collecting more money. It’s about restoring trust and predictability to the business of care.

Every health care executive knows that the business of health care is as complex as the care itself. Hospitals and medical practices rely on revenue cycle processes that have to translate clinical activity into financial reimbursement, a process that is supposed to be systematic, standardized, and precise. But the reality is very different, because achieving medical billing accuracy and consistency remains nearly impossible, even for the most advanced organizations.

Beneath the surface of modern health care operations is a deep and persistent inefficiency that silently erodes profitability, obscures performance metrics, and ultimately undermines patient care. This is not just a technology problem, nor is it just a staffing problem. It is a systemic problem, one that starts with how the health care system itself defines, codes, and reimburses for care provided.

The systemic complexity of the billing system

At the heart of this problem lies the Current Procedural Terminology (CPT) code set. These five-digit numerical codes are the universal language of medical billing in the United States. Each represents a specific medical service, surgical procedure, or diagnostic test. There are over 10,000 active CPT codes, and the American Medical Association updates them annually, sometimes multiple times a year.

Each change ripples across billing departments, electronic health record systems, and payer contracts. Keeping up is not just difficult; it’s practically impossible without constant oversight and creates significant staff support challenges. Layered on top of this complexity is a fragmented payer landscape. Every insurer, whether national or regional, maintains its own fee schedule. This means that the same CPT code can be reimbursed at different rates depending on the payer, the provider’s contract terms, or even the patient’s insurance plan type.

The result is a reimbursement matrix so intricate that it’s impossible for any billing department to maintain perfect accuracy in real time. Providers, uncertain about what they will be paid, err on the side of overbilling. It’s a defensive position born not from greed but from self-protection. Underbilling results in a permanent loss of revenue, as insurers will only paywhat is billed. Overbilling, by contrast, can be corrected downward by the payer. This practice of overbilling has become systemic and masks a much larger issue: the near-total absence of billing performance transparency.

The illusion of financial clarity

For most health care organizations, the only visible metric of financial success is the bottom line, aka the total revenue collected over time. Few executives have a clear understanding of how much of that revenue is being lost to inefficiencies, errors, or denials.

What makes all of this more challenging is that even the largest health care systems that are armed with sophisticated revenue cycle management software struggle to answer fundamental questions such as:

  • What is our true billing accuracy rate?
  • How much of our revenue is lost to denials or underpayments?
  • Which payers, codes, or departments contribute most to revenue leakage?

When these questions can’t be answered, financial performance becomes reactive rather than strategic. Executives then make decisions based on incomplete data, while systemic inefficiencies continue to compound year after year. The most significant and least visible contributor to this revenue leakage is the insurance claim denial.

Denials: The silent killer of revenue

A denial occurs when an insurance company refuses to pay for a submitted CPT code. This happens for a number of reasons, including missing documentation, incorrect modifiers, expired authorizations, or payer-specific rule changes. Regardless of the cause, denials represent a serious and often underestimated threat to revenue. Despite the fact that a significant number of claims are denied on the first pass, only a portion of those are eventually recovered. Yet a significant amount of claims, often more than 50%, are never resubmitted at all.

In practice, denial remediation is one of the most neglected areas of the revenue cycle. Not because billers don’t care, but because they are forced to make choices under pressure. Billing teams, often understaffed and overburdened, must triage their work. First-pass claims are faster, cleaner, and more predictable, so they take priority. Denials, on the other hand, are complex, time-consuming, and uncertain. Even after hours of effort, a denial may turn out to be legitimate and unpayable.

This reality drives a quiet but widespread behavior; denials are swept under the rug. They are written off, ignored, or buried within aggregate reporting, which is a part of the inaccuracy of revenue. The result is that most health care organizations don’thave visibility into their denial performance metrics, leaving executives unaware of the full extent of their revenue loss.

The metrics that matter

To take control of denials, health care leaders must first establish data visibility. Four core metrics define denial performance and should appear on every executive dashboard:

  1. First Pass Denial Rate – The percentage of first-pass claim CPTs that are denied.
  2. Denial Recovery Rate – The percentage of denied CPTs that are ultimately paid after resubmission.
  3. Denial Resubmission Rate – The percentage of denied CPTs that are resubmitted for payment.
  4. Denial Resubmission Success Rate – The percentage of resubmitted denials that result in payment.

Tracking these metrics over time provides a factual basis for diagnosing problems and improving processes. Without them, every discussion about revenue performance remains speculative. It’s worth noting that these are not just operational metrics—they are also strategic metrics. They measure not only the efficiency of billing staff but also the quality of clinical documentation, payer relations, and revenue cycle governance.

Reframing the role of the executive

Health care leaders can no longer afford to view billing as a back-office function. It is a strategic capability and a determinant of both financial and clinical performance. Executives should demand transparency from their billing operations and ensure that denial data is integrated into financial reporting. They should invest in intelligent automation and AI-driven denial solutionsthat learn from historical claim outcomes, predict risk patterns, and flag errors.

Equally important, leaders must foster a culture of data-driven accountability. Billing performance should not be a mystery but a shared priority across finance, operations, and clinical teams. Just as quality of care is measured, reported, and optimized, so should the quality of billing. Ultimately, financial health and clinical health are tied together.

The strategic imperative for the future

The U.S. health care system is entering a period of major transformation thanks to rising costs, shrinking margins, and the growing pressure for transparency. Amid these challenges, revenue integrity will determine which organizations thrive and which struggle to survive. Those who master billing accuracy will not only safeguard their margins but will also gain a powerful advantage: the ability to make decisions based on reliable, actionable data.

Fixing the billing problem isn’t just about collecting more money. It’s about restoring trust and predictability to the business of care. Because when providers have confidence in their revenue, they can reinvest in people, technology, and patient services. They can also plan strategically instead of reactively and focus on what truly matters—delivering exceptional care.

Ultimately, billing accuracy isn’t just a financial goal. It’s a leadership responsibility. And it starts with one question every healthcare executive should be able to answer: Do we actually know how accurate our billing really is?

Dalton Han is the co-founder of Red Sky Health, creators of a proprietary AI platform called Daniel that makes recommendations to reduce claim denials. Daniel identifies claims issues, provides guidance to fix them, and programmatically resubmits the claim. Formed by healthcare and technology startup veterans, the Company’s mission is to combat health insurance claim denials and ensure proper compensation for medical services. The ultimate focus is to help patients receive the full scope of care they deserve. To learn more, visit them at RedSkyHealth.com or follow them on LinkedIn.

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