When every dollar matters, effective denial management is essential. Healthcare organizations face rising denial rates and tighter margins, but most denials are avoidable with the right processes, analytics and automation.

Across the industry, claim denial rates have climbed into double digits in recent years (averaging about 15% of claims compared with single-digit levels only a few years ago). This reflects more complex payer rules (especially related to prior authorization) and ongoing operational gaps. The result: delayed cash, higher costs-to-collect and unnecessary administrative work. Nearly $20 billion is spent by providers each year
on reworking and appealing denials according to recent estimates.¹

Industry analyses show that ~85% of claim denials are potentially avoidable through up-front improvements.² Front-end errors, in areas like registration, eligibility and authorization are the top drivers of preventable denials; therefore, in this “first mile” of the revenue cycle is where accuracy and verification deliver the greatest impact.

How can organizations put the right safeguards in place to manage growing denials?

1. Classify denials and target the avoidable ones. Not all denials are created equal, so start by categorizing them and assigning actions to each category. For example: Avoidable denials result from process errors under your control (missing or incorrect patient coverage info, authorization mistakes, timing issues, coding inaccuracies). These should be prevented through stronger workflows and training. Situationally avoidable denials stem from nuances like payer-specific rules or documentation gaps – some may be prevented by special handling or policy adjustments. Unavoidable denials are those truly beyond provider control (e.g. non-covered services or recent payer policy changes); while they should be tracked, they won’t drive process changes. HFMA has emphasized standardizing denial definitions to help providers focus on the preventable 85% segment. By classifying denials in this way, teams can quantify the scope of avoidable revenue leakage and tackle root causes one by one, instead of treating all denials as an inevitable cost of doing business.
2. Strengthen front-end processes to “get it right the first time.” The majority of avoidable denials originate in patient access and documentation steps, before a claim is ever submitted. That means addressing the common failure points at scheduling, registration, and eligibility verification: Standardize how patient information is collected and verified. Ensure insurance coverage is active and captured correctly, and that required authorizations or referrals are obtained prior to service. Use checklists or system edits to catch missing data (like service dates or provider IDs) that cause rejections. Rigorously train staff on these policies and on the top denial reasons. Conduct regular documentation and coding audits to catch issues before claims hit the payer, and provide feedback to clinicians and coders. In short, an ounce of prevention is worth a pound of cure: an accurate, clean claim submitted today is far less costly than scrambling to fix or appeal it tomorrow.
3. Leverage automation & AI to augment your team. Rule-based automation (RPA) and artificial intelligence are changing the denial management game. Automation can take over repetitive, error-prone tasks – for example, automated insurance eligibility checks and prior auth status follow-ups, or deploying bots to retrieve claim status updates from payer portals. This ensures consistency and frees up staff time. Meanwhile, AI-driven tools are enabling a more predictive and proactive approach: advanced analytics can flag high-risk claims before submission (e.g. an AI model that learns from past denials and identifies a likely coding issue or missing modifier on a claim). AI can also help surface root causes by analyzing denial patterns hidden in large datasets, and even draft appeal letters or recommended fixes for certain denial types. Another emerging capability is AI “copilots” or assistants that make knowledge instantly accessible – for instance, staff can query an AI tool for payer-specific rules or documentation requirements in real time, getting answers on the fly instead of hunting through manuals. Together, these automation and AI solutions reduce manual workload, improve first-pass claim acceptance, and ensure that staff focus on exceptions rather than every claim. It’s worth noting that as of 2025, adoption of AI in revenue cycle is still low – only about 14% of healthcare providers have implemented AI in their claims process, according to a recent industry survey. However, the early adopters report promising results: roughly 69% of organizations using AI have seen a reduction in claim denials or improved resubmission success rates. In other words, the technology is ready and showing ROI, and we expect provider adoption to accelerate in the quest to curtail denials.*
4. Make KPIs your North Star
   A high-performing revenue cycle measures what matters and acts on it daily. Key KPIs include:
   • Clean claim rate above 95%
   • Denial Rate below 5%
   • Avoidable write-offs below 3%
   • AR over 90 days under 15–20% of total receivables
   • Denial Resolution Time under 30 days
5. Turn insight into action – use analytics to prioritize fixes
   Dashboards should visualize volumes, amounts over time (month-on-month, quarter-on-quarter, year-on-year), denial reason groups, regions, facilities, and procedure codes. Use these insights to prioritize fixes and automate the highest-impact steps. Organizations that embed analytics into daily huddles and escalation routines see faster improvements in clean claim rates and lower total cost to collect.
6. Benchmark against the best
   Top performers keep denial rates near 5% of total volume. This is possible by focusing on front-end accuracy, using payer-specific edits, and building preventive controls. Add selective automation—claim status bots, document ingestion and interpretation, and denial prediction—and you turn chronic leakage into durable revenue.