February 24, 2021

Claim denial is one of the biggest hurdles that affect the financial stability of healthcare providers. Every year, they deny an average of 10-15% claims, where the reasons vary from technical issues to simple administrative denials. This puts the providers at risk of losing money, thereby negatively impacting cost efficiency, as the average cost of reworking a claim at USD 25 can quickly multiply if denials continue to pile up.

Healthcare organizations lose about 6-8% of their overall revenue annually owing to improper handling of denials. Such claims need to be carefully filtered out and processed before draining the healthcare service providers’ finances. Accordingly, root cause analysis is essential for identifying denial causes and implement necessary changes to prevent them from occurring again. An effective and efficient way of managing claim denials can help drive revenues, along with improved patient satisfaction.

Reasons for denials

Some of the primary reasons that contribute to claim denials include improper registration (10-15%), eligibility verification (23%), missing data (14%), and pre-authorization errors (12%). In addition to revenue losses, extended Accounts Receivables cycles of over 90 days, and thousands of hours lost in additional administrative work and appeals, create complexities for providers. Claim denials can be attributed to any of the following causes:

  • Eligibility Verification/Pre-Insurance Verification: This is crucial to avoid claim rejections, and it must be the first step in determining the service charges. Failing to obtain prior authorization for the service can result in claim denial.

  • Missing Information: Even if a single required field such as plan code, modifier, or address is left blank accidentally, it can result in the denial of a claim.

  • Error in Medical Billing Code: With medical billing codes continually changing and adjusting to new services and new technology, another common reason for insurance claim denials is errors in medical billing codes at the time of filing the claim.

  • Inappropriate Time for Claim File: Each insurance company has a different billing cycle. If a provider files a claim at the wrong time in the payers’ billing cycle, it could lead to insurance claim denials.

  • Duplicate Claim or Service: Duplicates – claims resubmitted for a single encounter on the same date or same provider for the same beneficiary and same service component – are among the biggest reasons for claim denials.

  • Out of Network Provider: Insurance providers change and adjust their network regularly. If a provider falls out of the network at any point, their claim may be denied.

This is where analytics can bring efficiency by helping healthcare organizations predict denials and resolve problems before the claims are submitted, leading to cost benefits and higher revenue. Analytics plays a pivotal role in building reliable business intelligence for assessing the success of claims denial prevention.

Denial management using AI

To gain profitability and success and establish financial stability, healthcare providers must embrace the digital era and adopt technologies like machine learning (ML) and artificial intelligence (AI), which can ensure 90% of denials can be prevented. Through continuous pattern mining, AI engines look for missing/incorrect documentation before the organization sends out the claim to the insurance provider, thus reducing denials. AI-based claim denial management strategies can help teams understand, which denials are more likely to be resolved faster, thereby empowering providers with improved accuracy, favorable outcomes, and an accelerated cash flow.

In addition, AI predictive rules can help determine the next best action based on the date of service checks, eligibility benefits verification, and Current Procedural Terminology mismatch checks. With the ability to train itself, such a system can also log clear details about the stages and reasons for the denial, which further helps in curating recommendations for upstream process improvements.

To Summarize

When implemented right, AI could prove to be a significant technology-powered break as it helps streamline the denial processes and reduces the number of denials. By optimizing denial management, such an intelligent platform paves the way for data integrity and accuracy, and ultimately, the organization’s financial success.

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Sumit is a result-driven professional with over 16 years of experience in client relations, solution and accounts management. He has managed the transformation journey, business intelligence, data architecture, and operations for large hospitals and physicians. He is an MBA from Symbiosis University and has played multiple roles aligned with the healthcare domain.