AI-Powered Networks: How Automation Is Redefining Claims Efficiency
Written by: Carrie Murphy, Director of Solutions Management, Veradigm, and Cheryl Reifsnyder, PhD
The pace of regulatory change has accelerated since the pandemic, leaving healthcare organizations struggling to keep up. Providers must manage multiple payment systems, each with its own rules, metrics, and incentives. Meanwhile, claims denial rates have increased; one survey found that nearly 15% of all private payer claims are initially denied—including some that were, theoretically, pre-approved. Denial rates are even higher for Medicare & Medicaid claims.
Complex reimbursement processes are increasing both administrative burden and financial pressures. Payers and providers are forced to invest excess time and resources trying to achieve the same goal of clean, accurate payments.
In the face of these changes, traditional claims workflows are no longer adequate. Encumbered by inefficient legacy systems and manual processes, they’re often time-consuming and error-prone. The result? Increased denials and slower payments.
This is why introducing Artificial Intelligence (AI) into claims workflows is producing such remarkable results. AI is transforming claims processing. As AI moves the reimbursement system from manual and reactive to proactive, intelligent, and automated, it benefits both providers and patients.
Keep reading to learn how!
Why traditional claims workflows fall short
Traditional claims workflows are limited by the numerous steps that most practices still perform manually, steps such as patient insurance verification, prior authorization, and delivering attachments with claim submissions.
Insurance verification
Manual insurance verification is inefficient and error-prone. Mistakes can be costly, especially when they result in denials. One study found that 27% of denials originate during patient registration and insurance eligibility checks. Approximately 86% of these are potentially avoidable.
Prior authorization
Payers frequently require clinicians to obtain prior authorizations (PAs) for patients. Unfortunately, PA requirements vary significantly among payers. Providers must juggle inconsistent PA workflows; inconsistencies mean PA requests are often returned with requests for additional information. Each rejection creates delays and adds to providers’ administrative burden.
Inconsistencies in payers’ PA requirements prompt many providers to conduct PA requests manually. The Council for Affordable Quality Healthcare (CAQH) estimates over half (51%) of the 182 million PAs commercial payers handle each year are conducted manually.
However, manual PA requests further increase physicians’ administrative burden and can delay patient treatments.
Attachments
About 4% (or 80 million) of the estimated 2 billion-plus claims payers receive annually require attachments with supporting information. The 2022 CAQH Index Report revealed that 76% of these attachment transactions were processed manually.
Here, too, manual processes require more time and expense for both payers and providers; can introduce errors; and can cause significant treatment delays for patients. On the other hand, automating the attachment process could save providers 4 to 5 minutes per transaction while also decreasing errors. This, in turn, reduces the number of claims needing to be reworked.
The costs of inefficiency: Denials, delays, and burnout
Although some practices have begun incorporating automation into the claims submission workflow, many providers and staff resist the switch. Some are unwilling to front the implementation costs associated with using a new system; others prefer the familiarity of existing manual processes.
However, the cost of continuing inefficient processes far outweighs the cost of implementing a new claims management system.
Dirty claims & denials
Clean claims are defined as claims submissions that:
- Contain complete and accurate patient information and insurance details,
- Include all necessary supporting documentation,
- Are accurately coded,
- Comply with payer-specific requirements, and
- Comply with relevant healthcare regulations.
Clean claims are essential for accurate and timely reimbursement; however, in a recent survey, 63% of providers reported greater difficulty submitting clean claims now than a year ago.
Fewer clean claims mean denial rates are higher—which means more claims that need to be resubmitted. Ninety percent of those resubmissions are reworked manually.
The ripple effects of denials
Each reworked claim is estimated to cost providers from $25 to $57. However, the costs of denials extend beyond their financial impact. Disputed denials require an average of 3 rounds of insurer review, each lasting from 45 to 60 days. These rounds of review significantly delay payment; providers are often unable to recoup costs for 6 months after providing services.
Delays can also lower patients’ overall satisfaction and trust in the healthcare system, and payment uncertainty causes many to delay follow-up care. According to the Commonwealth Fund, 46% of Americans skip or delay care due to coverage concerns.
Administrative burden & clinician burnout
Most clinicians rank administrative burden as their number 1 contributor to workplace stress.
The increased difficulty of submitting clean claims, plus the resulting increase in denials, have correspondingly increased clinicians’ administrative responsibilities. A recent poll found clinicians spend nearly 28 hours weekly on administrative duties. Medical staff spend even longer, about 34 hours a week. As a result, 82% of clinicians and 81% of medical staff report symptoms of burnout.
How AI and automation are transforming claims processing
According to a recent survey, the top 3 causes of claim denials are:
- Missing or inaccurate patient data (50%)
- Prior authorization (65%)
- Incomplete or inaccurate patient registration data (32%)
All 3 occur at the front end of the revenue cycle—highlighting the need for innovative solutions early in the revenue cycle. By addressing issues early in the cycle, solutions could significantly increase a practice’s clean claims rate, or the percentage of claims processed accurately on first submission.
Increasing clean claims rates
The Healthcare Financial Management Association (HFMA) recommends practices have a 98% clean claims rate; however, a recent MGMA report reveals an average clean claims rate of 92% for single-specialty practices.
AI and machine learning algorithms can help increase your clean claims rate by:
- Learning from historical claims data to predict denials before they occur—and continuing to refine prediction accuracy over time
- Identifying and flagging missing or inconsistent information
- Suggesting corrections tailored to payer-specific patterns
AI solutions can address issues prior to claims submissions by validating data, ensuring compliance, and thus reducing errors. This leads to fewer denials, less time and energy required to rework or fight denied claims, and speedier reimbursement.
Streamlining workflows and reducing administrative burden
AI can also help practices automate the claims management process, increasing workflow efficiency and reducing administrative load. The 2024 CAQH Index Report found that automating claims submission workflows helped avoid $222 billion in administrative costs in the U.S.
Automation not only improved efficiency and reduced costs: It also gave clinicians more time for patient care, increasing job satisfaction and reducing burnout.
Veradigm Payerpath: Intelligent automation
Veradigm Payerpath is an award-winning revenue cycle management solution that helps practices leverage intelligent automation to achieve higher clean claims rates and faster reimbursements. Payerpath’s collection of AI-driven abilities enables practices to refine the claims management process, reducing rejections and denials, improving claims accuracy, and accelerating payments. These AI-powered capabilities include:
- Real-time eligibility verification: Payerpath instantly confirms patient coverage, preventing eligibility-related claim rejections.
- Pre-submission validation: Payerpath uses AI to check for missing and inaccurate data, helping practices identify and correct coding and data entry errors.
- Dynamic payer rules: Automatic software updates capture ongoing changes in payer policies.
- Predictive denial management: Payerpath analyzes historical claims data to identify high-risk claims, so issues can be addressed before submission.
- Integrated revenue cycle tools: Integrated tools enable practices to manage claims editing, denials, billing, collections, and patient engagement through a single solution.
With Veradigm Payerpath, clients achieve an average first-pass clean claims rate of 98%. The result? Faster reimbursements, a more predictable revenue stream, and reduced administrative burden for both clinicians and staff.
Reaching a brighter and more connected future
Additional regulatory changes are on the horizon to further improve healthcare interoperability, such as the Interoperability and Prior Authorization final rule (CMS-0057-F) from the Centers for Medicare & Medicaid Services and interoperability-supporting technology standards HL7 and Fast Healthcare Interoperability Resources (FHIR). As these changes are implemented, payer-provider networks will grow even more intelligent and more responsive. Healthcare organizations that embrace current AI innovations will be best positioned for success in the future.
Solutions such as Veradigm Payerpath drive greater claims accuracy, faster payments, and stronger payer-provider collaboration throughout the claims management process. Using AI and intelligent automation, Payerpath can redefine the payer-provider relationship, empowering healthcare practices to thrive in the face of an increasingly complex healthcare ecosystem.
Contact us today to learn how Veradigm Payerpath can help your practice transform your revenue cycle.