Denial Analytics: Using data to improve processes

Just as provider organizations accepted that private payers were denying 15% of healthcare claims, the Kaiser Family Foundation came out with a new number.

As of this year, HealthCare.gov payers now deny 19% of in-network claims and 37% of out-of-network claims. These figures amount to a combined average of 20% of all claims.

Shortfalls at these levels cut deep into net revenue. In an aggressive merger and acquisition environment where provider organization P&Ls get scrutinized closely, you bet partners, investors, and lenders are looking into a provider organization’s denial management process and their success in attaining a high clean claims rate. 

They know that payers have unleashed AI on denials, finding every tiny misstep to justify rejecting a claim. 

The good news is that – with proactive denials recovery – more than half of denials can be overturned. Denial analytics—conducted either manually or with AI- and automation-supported software—can reveal exactly where breakdowns are occurring, which payers and codes are driving preventable denials, and which process changes or documentation fixes will have the greatest financial impact. By turning detailed insight into targeted action, provider organizations can systematically raise their clean claims rate, accelerate cash recovery, and transform denial management from a reactive chore into a strategic source of revenue integrity.

Here, you can review how to use denial analytics to improve your first pass clean claims rate,  reinforce net revenue, and lift denials burden from staff. 

 What is denial analytics?

Denial analytics is the process where staff and/or software mine historical and real-time claim data to surface patterns—such as recurring authorization gaps, coding errors, or payer-specific edits—that predict which submissions will be rejected. When these insights are fed back into the claims-management workflow, the system can automatically flag high-risk claims for correction or apply rule-based edits at the point of entry, turning a reactive appeal process into proactive prevention. In other words, claims management supplies the data and execution engine, while denial analytics provide the intelligence that guides which claims need intervention and how to fix them—closing the loop between insight and action.

A proactive denials analytics program helps your revenue cycle team pinpoint the root causes of claim denials, helping to prevent future rejections and recover lost revenue. By analyzing denial patterns and identifying trends, providers can make targeted improvements in billing practices, documentation, and workflow, thus increasing clean claim rates and cash flow. 

Denial analytics benefits

Here are the top benefits you can expect from conducting robust denial analytics–whether manually with your existing staff or with software.

• Root-cause visibility: Denials analytics break down precisely why claims are being rejected, enabling targeted fixes rather than broad, guesswork interventions. Win staff buy-in for workflow changes when you back up requests with data analytics insights.  
• Prevention of repeat errors: By identifying patterns and trends, analytics help staff proactively address the most common denial causes before the next claim is submitted.
• Faster cash recovery: Analytics spotlight low-hanging fruit among denied claims, so billing teams can focus appeals on those most likely to be paid quickly.
• Better staff productivity: Automated sorting and prioritization of denials reduce manual hunting, ensuring teams spend their time where it matters most.
• Strong contract negotiations: Analytics provide concrete evidence of payer behavior and denial volume, arming providers with data for better rate and policy discussions.
• Improved compliance: Denials analytics flag gaps in documentation and authorization, helping prevent regulatory penalties and audit take-backs.
• Higher clean claims rate: With insight-driven workflow changes, providers can increase the proportion of claims paid on first submission, reducing rework and write-offs.

Taken together, these benefits make denial analytics a powerful tool for transforming financial performance and operational efficiency in any provider organization.

How to execute denial analytics with manual processes

Sophisticated RCM platforms crunch denial data for provider organizations, but if your organization still processes denials manually (as 50% today do), you can still build insightful analytics with billing system export, spreadsheet software, and disciplined workflow. Use the steps below to manually create action-ready denial intelligence.

1. Export the right raw data

• Pull 6–12 months of 835 remittance files or denial reports from your practice-management/billing system.
• Include at minimum: payer name, patient MRN, DOS, CPT/DRG, billed charge, allowed amount, denial code (CARC/RARC), and adjustment dollar value.

2. Normalize Payer Codes

• Copy the data into Excel or Google Sheets.
  
  
• In a separate tab, build a mapping table that translates each payer’s proprietary denial descriptions into standardized CARC categories (e.g., CO-197 = Authorization Required).
• Use VLOOKUP/XLOOKUP to append the standardized category to every denied claim.

3. Create the core analytics views

• Denial Rate by Segment
  
  • Pivot by payer, service line, location, and denial category.
  • Calculate denied $ ÷ total billed $ to spot hotspots.

• Pareto chart of top denial reasons - Sort denial categories by dollar impact and build a cumulative-% column; the first 5–7 reasons usually drive 80% of lost revenue.
• First-pass yield trend - For each month, divide number of claims paid on initial submission by total claims submitted. Plot the line to see performance over time.
• Appeal win-rate dashboard - Add a column for final disposition (paid, partial, lost). Pivot by denial type to find which appeals are worth the effort.

• Aging & work-queue report - Filter denied claims by status date to show items >30, >60, >90days since denial. Highlight those nearing timely-filing limits.

4. Interpret & act

• Target the highest-dollar denial categories first; design coder education or front-end edits for those specific errors.
• Funnel denials with historically high appeal success (>50%) to staff for aggressive follow-up; write off chronic low-win categories sooner.
• Track first-pass yield monthly; if it doesn’t rise after a fix, your root-cause hypothesis was wrong—re-examine the data.

5. Keep the loop tight

• Review the pivot tables in a 30-minute huddle each week with coding, billing, and front-office leads.
• Document every workflow tweak you implement and mark the go-live date. Look for improvement in the following cycle.
• Refresh the raw data export monthly so your analytics stay current.

6. Upgrade gradually

• Once the manual process proves ROI, justify low-cost add-ons such as an Excel Power Query dashboard or a lightweight BI tool (e.g., Google Looker Studio).
• When budget allows, migrate to purpose-built denial-analytics software to automate data pulls, normalization, and real-time alerting.

By structuring exports, standardizing codes, and applying basic spreadsheet pivots, providers and MSOs can uncover the same high-value insights that automated platforms surface—turning denial data into measurable revenue gains without waiting for a big IT purchase.

Denial analytics with AI- and automation-assisted software

While manual denial analytics can uncover valuable trends and root causes, the process is often slow, labor-intensive, and limited by what staff can track and interpret on their own. Upgrading to software platforms that conduct denial analytics ensures you can move beyond reactive firefighting to proactive, scalable denial prevention and revenue recovery. 

The software platforms that most often handle denial analytics are claims management or revenue cycle management (RCM) software, both of which are purpose-built to ingest, normalize, and analyze claim data, denials codes, and remittance advice from payers Advanced contract management platforms also incorporate denials analytics to compare payouts against contract terms, standalone contract management systems typically focus on contract lifecycle and compliance rather than deep denial pattern analysis. Contract management features add extra value for underpayment recovery and payer negotiations.

Robust denial management software cross-references a granular contract library with claims and remittance feeds to surface several core categories of denial intelligence. 

Denial management software provides: 

1. Granular denial trending.

• Tracks denial counts and dollars at the charge level across CPT®/HCPCS, DRG, payer, site, and provider dimensions.
• Compares each denial to the exact contracted fee schedule stored in RevFind, separating true non-covered services from underpaid or mis-adjudicated claims.

2. Root-cause & pattern detection

• Group denials by ANSI adjustment/remark code, then highlights concentration hot-spots (e.g., “CO-197–Authorization Required” spikes for one payer/location).
• Dashboards let users slice by time period to see whether payer policy changes or internal workflow shifts drove the uptick.

3. Automated work-queue assignment

• Newly identified denials are auto-routed to customizable queues—by denial reason, payer, facility, or dollar value—so specialists tackle the highest-impact items first.
• Each queue tracks appeal status and aging, turning denial follow-up from ad-hoc spreadsheets into a closed-loop process.

4. Contract & appeal leverage

• Because contract management software marries denial data with contractual terms, users can instantly calculate the revenue at stake for any recurring denial reason and export evidence packets for payer disputes or renegotiations.
• “What-if” modeling shows how fixing a particular root cause—or winning a contract carve-out—would flow to top-line revenue.

Putting Denial Analytics Data Into Action

Turning sophisticated denial analytics into tangible results starts with translating insight into targeted workflows. Use granular trending and root-cause detection to pinpoint where denials concentrate—whether by payer, procedure, or code—and share these findings with your coding, billing, and front-office teams. Assign responsibility for critical denial categories, and implement tools like automated work-queue assignment to ensure the most impactful issues get immediate attention.

Next, leverage contract comparisons and “what-if” scenarios to prioritize disputes, appeals, and negotiation strategies that directly improve revenue. Track changes after each process update, monitor appeal status in real time, and refine your approach as new denial patterns emerge. By embedding these data-driven tactics into everyday operations, your organization moves from reactive denial management to proactive revenue recovery and greater long-term financial health.

MD Clarity delivers the denial analytics that stops revenue leakage

Provider organizations contend with shrinking reimbursements, rising expenses, complicated denials, inconsistent payer requirements, and a jumble of technologies that make every dollar harder to capture. By deploying AI- and automation-powered denial analytics, organizations can transform this complexity into a powerful engine for cash flow.

Physician groups and MSOs reach their full potential when every acquisition, clinic, and service line operates on a unified, high-efficiency revenue cycle. MD Clarity’s RevFind contract management platform empowers you to actively manage denials, appeals, contract discrepancies, and underpayments. With RevFind, you gain precise visibility into which payers are denying specific CPT codes and exactly how much revenue is held up by each denial, while automated account labeling and bulk work queues make appeal delegation seamless and efficient.

If your organization lacks internal resources for overturning key denials, our denial recovery specialists step in to craft targeted appeals that drive higher success rates, clear out backlogs, and relieve your team’s workload. Leveraging RevFind’s detailed analytics, they identify and capture reimbursement opportunities that often go unnoticed by even experienced RCM teams. This comprehensive approach to underpayment and denial recovery helps you maximize revenue—enabling investment in new equipment, clinician recruitment, and community care initiatives.

Want to experience a fully integrated revenue recovery strategy? Schedule a demo today.

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