If your denial rate is climbing, the instinct is usually to hire another biller, add a follow-up queue, or push the appeals team harder, putting more people on the problem and more hours into chasing payments that should have come through the first time.
That approach is not necessarily wrong, but it treats the symptom rather than the cause. As long as the underlying workflows stay broken, the denials will keep coming.
The data on this is pretty hard to ignore right now.
The Healthcare Financial Management Association (HFMA) estimates that up to 85% of denials are preventable with better processes.[6] That means the majority of what your team is spending time on every week did not have to happen in the first place. These are not inevitable losses. They are avoidable ones, and the difference comes down to how the workflows supporting your claims process are built.
Where Denials Are Actually Born
I spent years overseeing RCM teams, and one thing became very clear. Most denials do not start in the billing department. They start much earlier, at registration, at scheduling, and at the point of service, well before a claim is ever submitted.
According to Experian Health's 2025 State of Claims report, 26% of respondents say at least one in ten denials at their organization can be traced back to intake errors, including incorrect member IDs, demographic mismatches, and coverage that was not verified on the date of service.[2] The same report found that 68% of providers say submitting clean claims is more challenging than it was a year ago.[2] These are not billing team problems. They are data quality problems that start at the front desk.
"You can have the best coders and the most experienced billers in the business. If the information coming through the front end is wrong, you are building on a broken foundation."
— Mindy Corbett, CSPO, CPC, CPB, CPPM | Founder & CEO, Revenue Optimization & Intelligence
The downstream cost compounds quickly as well. The administrative cost per denied claim reached $57.23 in 2023, up from $43.84 the year prior.[4] That number multiplies across hundreds of monthly denials. Research from the Medical Group Management Association (MGMA) also found that 65% of denied claims are never resubmitted, meaning that revenue is simply written off and never recovered.[6]
What a Denial-Resistant Workflow Actually Looks Like
Building a denial-resistant workflow is not about doing more work. It is about catching the right issues at the right time, before they become expensive. This is the framework I use when working with practices to close their most preventable denial gaps.
Gate 1: Real-Time Eligibility at Scheduling
Eligibility should be verified the moment an appointment is booked, not the morning of, not at check-in. Coverage lapses, plan changes, and inactive policies need to be caught before the patient walks in the door. Automated real-time eligibility checks eliminate this as a denial source almost entirely.
Gate 2: Clean Registration with Built-In Validation
Registration workflows should have validation logic built in, not bolted on. Required fields, format checks, and insurance ID verification should all be part of the intake process by design. The goal is to make it structurally difficult to submit incomplete data, rather than relying on staff to catch every error manually.
Gate 3: Prior Auth Tracking That Doesn't Live in Someone's Head
Prior authorization is one of the most consistently cited denial drivers. If your authorization tracking lives in sticky notes, spreadsheets, or individual staff members' memories, it will fail. A centralized, automated tracking system with expiration alerts is non-negotiable for any practice with significant auth volume.
Gate 4: Pre-Submission Claim Scrubbing
Claims should be reviewed against payer-specific rules before they go out the door, not after they come back denied. A good claims scrubber catches coding errors, missing modifiers, bundling issues, and payer-specific quirks automatically. Every denial caught here is one your team doesn't have to chase.
None of these are revolutionary ideas. The gap isn't usually knowledge, it's execution. Most practices know eligibility verification matters. The problem is that the workflow for doing it is manual, inconsistent, and easy to skip when things get busy.
A Real-World Scenario
Consider a mid-sized multi-specialty practice running about 800 claims per month with a denial rate hovering around 14%. A breakdown of their denial reasons shows that nearly a third trace back to eligibility and registration issues at the front end, including inactive coverage, incorrect member ID or policy numbers, and missing secondary insurance details.
Their billing team is spending roughly 30% of their time on rework and appeals for denials that should never have happened. The solution is not more billers. It is automating eligibility checks at scheduling, adding validation to the registration intake form, and building a simple daily audit of upcoming appointments against current coverage status.
Practices that implement these kinds of upstream workflow changes typically see denial rates drop 30 to 45 percent within the first two to three months, not because they hired anyone new, but because they stopped allowing preventable errors to reach the payer in the first place.
The Role of AI and Automation Here
This is where AI starts to earn its place as a practical tool rather than a buzzword. Payers are already using AI to find reasons to deny claims faster. From 2022 to 2024, denials triggered by requests for information increased by 9%, and Medicare Advantage denials jumped 4.8% in a single year.[1] The playing field is shifting, and practices that are still managing this manually are at a structural disadvantage.
According to Experian Health's 2025 State of Claims report, of the 14% of providers currently using AI in their claims process, 69% report it has reduced denials and/or improved resubmission success rates.[2] The tools are working for those who have adopted them. The challenge is that adoption remains low, largely because practices are unsure where to begin.
The right starting point is not an all-in AI transformation. It is automating the specific, high-volume, rule-based tasks that are currently consuming staff time and generating preventable denials, such as eligibility checks, authorization tracking, claim scrubbing, and denial pattern analysis. Starting there, building traction, and expanding from a foundation that is already working is a much more sustainable path forward.
Where to Start This Week
If you are wondering where to actually begin, here is a practical starting point. Choose one of the four gates above and audit it honestly.
Pull your top 10 denial reasons from the last 30 days. Sort by volume. What percentage trace back to eligibility, registration, or authorization issues? If it's more than 20%, your front-end workflow is your biggest lever.
Map out how eligibility is currently being verified. Is it automated? Manual? When does it happen? At scheduling, at check-in, or both? Are there gaps on same-day appointments or walk-ins?
Check your first-pass resolution rate. This is the percentage of claims paid on the first submission without any rework. Industry benchmark is 95% or above. If you're below that, you have a workflow problem worth solving, and now you have a number to improve against.
Ask your billing team where they spend most of their rework time. The answer will almost always point directly to the workflow gap that needs fixing first. They know where the problems are. The question is whether the systems have been built to address them.
Denial-resistant workflows do not happen overnight, and they do not require a full system overhaul to start making a difference. One gate, fixed correctly, can meaningfully change your numbers within a billing cycle.
In Issue #02, we will dig into automation that actually sticks, including how to implement workflow automation in a way your team will actually use, and what separates the tools that get abandoned six months in from the ones that become part of how the practice runs.
- Becker's Payer Issues (May 2025). Claims denial rates up, prior auth denials down in 2024. Becker's is one of the most widely read trade publications in healthcare administration, covering revenue cycle, payer policy, and hospital finance. Data cited from Kodiak Solutions, a healthcare analytics firm that analyzes claims data from more than 2,100 hospitals and 300,000 physicians. beckerspayer.com →
- Experian Health (September 2025). State of Claims 2025: The denial problem (and is AI the answer?) Experian Health is a division of Experian, a global data and analytics company. Their annual State of Claims survey is one of the most comprehensive industry benchmarks available, drawing on responses from 250 healthcare professionals and claims data across thousands of provider organizations. experian.com →
- OS Healthcare (2025). Denial Rates Are Climbing: What Revenue Cycle Leaders Should Be Watching in 2025. OS Healthcare is a revenue cycle management services firm. This article synthesizes recent denial trend data from multiple industry sources, including Kodiak Solutions and CMS, and is useful as a consolidated overview of current denial drivers. os-healthcare.com →
- Aptarro (December 2025). 50+ US Healthcare Denial Rates & Reimbursement Statistics for 2026. Aptarro is a healthcare revenue intelligence platform. This resource compiles denial rate statistics from more than 50 cited sources, including CMS, HFMA, Kodiak Solutions, and Experian Health, and is one of the most comprehensive aggregations of current denial data available. aptarro.com →
- MedViz AI (September 2025). Top 5 Claim Denial Triggers in 2025 & How to Prevent Them. MedViz AI is a healthcare technology platform focused on denial prevention and claims intelligence. This article provides a practical breakdown of the most common denial triggers, including eligibility errors, coding mistakes, and timely filing issues, along with prevention strategies. medviz.ai →
- Healthcare Financial Management Association (HFMA) / Medical Group Management Association (MGMA), cited via Legacy Consulting Services (March 2025). The HFMA is the leading professional association for healthcare finance, with over 100,000 members. The MGMA is the premier association for medical practice administrators and executives. Both organizations are widely considered the benchmark sources for RCM performance data in the industry. legacyconsultingservices.com →
Ready to audit your denial workflow?
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