Elevance Health provides useful examples of how process automation can improve healthcare claims administration and coordination between insurance payers and healthcare providers. Its initiatives involve automated claims workflows, AI-supported decision-making, electronic medical record integration and centralized data management.
For healthcare revenue cycle leaders, these developments offer practical lessons about reducing administrative costs, improving claims accuracy and preventing delays that affect reimbursement.
However, there is an important distinction. Elevance Health primarily operates as a health benefits company and payer. Its automation initiatives are not all traditional hospital revenue cycle management projects. They demonstrate how payer-side automation can influence provider billing operations, claim approvals, payment decisions and administrative efficiency.
Key Takeaways
- Elevance Health uses automation to simplify claims processing and reduce administrative work.
- Its Pega partnership demonstrates how intelligent workflows can support high-volume claims operations.
- Health OS and electronic medical record integration help reduce missing clinical information and authorization delays.
- Automation can improve provider revenue cycle performance by reducing manual follow-ups and preventable claim delays.
- Healthcare organizations should evaluate automation based on accuracy, denial reduction, processing time and measurable financial outcomes.
What Revenue Cycle Process Automation Means at Elevance Health
Revenue cycle management covers the administrative and financial activities involved in delivering healthcare and receiving payment. For providers, this includes:
- Patient registration and insurance verification
- Prior authorization and medical necessity checks
- Clinical documentation and charge capture
- Medical coding and claim submission
- Claims adjudication and payment processing
- Denial management and accounts receivable follow-up
Elevance Health operates primarily on the payer side of this process. Its automation efforts focus on making interactions with healthcare providers more efficient.
This distinction matters because a payer can improve claims processing without directly managing a hospital’s billing department. Better data exchange, faster authorization decisions and fewer incomplete claims can still improve provider revenue cycle performance.
The most useful Elevance Health process automation revenue cycle case studies demonstrate improvements in these connected administrative processes.
Case Study 1: Automating High-Volume Claims Processing
Documented implementation
One of the clearest examples involves Elevance Health’s claims examiner operations.
The operational problem
Elevance Health was processing approximately 40 million claims every month with nearly 5,000 claims examiners.
The existing process required employees to navigate multiple legacy systems and older interfaces to access information needed for claim reviews.
This created several operational challenges:
- Employees had to switch between different applications.
- Accessing member and provider information required additional steps.
- Manual validation increased processing effort.
- Training employees on multiple systems took time.
- Disconnected workflows affected the overall claims experience.
The organization needed a more consistent way to manage claims across its operations.
The automation solution
Elevance Health implemented a unified Claim Intake Workflow using an intelligent claims processing platform.
The system brought important information and processing functions into one interface.
Its capabilities included:
- Centralized access to member benefits and provider information.
- Automated claim validation and adjudication support.
- Intelligent routing based on employee skills.
- Real-time information and guided claim resolution.
- Integration with existing enterprise systems.
- AI-supported forecasting and workflow simulations.
Instead of requiring employees to move between multiple systems, the platform gave them a more consistent environment for reviewing and processing claims.
Business results
The implementation delivered several operational improvements.
| Performance area | Documented result |
|---|---|
| Monthly claim volume | Approximately 40 million |
| Claims examiners | Nearly 5,000 |
| Claims interface | One unified processing environment |
| Work allocation | Skills-based routing |
| Processing support | Real-time automation and guided resolution |
| Workforce planning | AI-driven forecasting and simulations |
The case study does not publish a specific percentage reduction in claim processing time or total labor costs. Its documented improvements focus on workflow efficiency, accuracy, employee experience and faster resolution.
Why this matters for revenue cycle teams
Healthcare organizations often invest in automation while leaving employees responsible for navigating disconnected applications.
A unified workflow can address this problem without immediately replacing existing billing or claims systems.
For a hospital or multi-location medical practice, the same principle can be applied to:
- Centralizing claim status information.
- Bringing payer responses into one work queue.
- Automatically assigning claims to the appropriate billing specialists.
- Reducing repeated data entry.
- Identifying claims that require human review.
The objective is to reduce unnecessary administrative work while keeping employees responsible for complex financial decisions.
Case Study 2: Reducing Authorization Denials Through Electronic Medical Record Integration
Measured outcome
Another important example involves Elevance Health’s Health OS platform and its integration with electronic medical records.
This initiative demonstrates how better information exchange can prevent problems before they affect claims and reimbursement.
The problem with missing clinical information
Healthcare providers frequently submit inpatient authorization requests that lack documentation required by the health plan.
When information is incomplete, the request may receive a Lack of Information denial.
These denials create additional work for multiple departments.
A typical process can involve:
- A provider submits an authorization request.
- The health plan identifies missing clinical information.
- The provider receives a request for additional documentation.
- Clinical staff search patient records for the missing information.
- Staff send the requested documents.
- The health plan reviews the updated request.
This process consumes time that clinical and administrative teams could use elsewhere.
It can also delay authorization decisions and create additional follow-up work.
How Health OS automation works
Elevance Health uses Health OS to connect healthcare providers, payers and consumers through a shared digital data infrastructure.
The platform combines information from multiple sources, including:
- Electronic medical records.
- Health information exchanges.
- Claims and eligibility data.
- Admission, discharge and transfer information.
- Clinical records and patient information.
For inpatient authorization requests, electronic medical record connectivity allows affiliated health plan staff to retrieve necessary clinical information.
They can then assess medical necessity and process qualifying requests without relying entirely on providers to locate and submit missing information manually.
Results from a New York hospital system
One large New York hospital system connected with Elevance Health through the Epic Payer Platform.
The automation produced the following results for Medicaid patients in 2024:
73%
Reduction in LOI denialsFor the reported Medicaid population
300
Hours saved annuallyUp to 300 nursing hours
Reported results from one large New York hospital system during 2024. These are not universal performance guarantees.
The time savings are particularly relevant because each Lack of Information denial can require up to 15 minutes of nursing time.
Reducing these cases allows clinical employees to spend less time gathering administrative documents and more time supporting patients.
What healthcare organizations can learn
This case demonstrates that denial prevention often begins before claim submission.
Revenue cycle leaders should examine whether missing information originates from:
- Incomplete clinical documentation.
- Poor communication between EHR and payer systems.
- Delayed authorization requests.
- Manual document retrieval.
- Inconsistent patient or provider information.
When systems can exchange accurate information securely, some administrative problems can be resolved before they become denials or payment delays.
Case Study 3: Improving Claims Efficiency Through Automated Workflows and Centralized Data
Reported operational improvements
Claims processing does not end when a provider submits a claim. Providers may still need to contact the health plan, correct information, investigate pending claims and update administrative records.
Elevance Health has focused on reducing these repeated interactions through automated workflows and improved provider data management.
The challenge of administrative rework
Healthcare providers often experience delays because information is incomplete, outdated or difficult to access.
Examples include:
- Incorrect provider information.
- Missing claim details.
- Repeated requests for clarification.
- Manual updates to provider records.
- Multiple calls to resolve the same issue.
These problems increase administrative workload and make it harder for billing teams to maintain predictable cash flow.
The process automation approach
Elevance Health has introduced several improvements to its claims and provider administration processes.
These include automated workflows designed to reduce manual rework, digital tools that support faster claim processing and a centralized care provider data warehouse.
The data warehouse helps improve information accuracy and makes it easier for providers to update and manage their records through self-service capabilities.
This approach addresses a common revenue cycle problem: employees spending time correcting information that should already be accurate and accessible.
Reported improvements
Elevance Health reported the following results from its system improvements:
| Performance indicator | Reported improvement |
|---|---|
| Care provider calls | 19.5% fewer |
| Data-related pending claims | 68% fewer |
| Reporting period | 2025 |
| Data-related improvement analysis | December 2025 |
These results highlight two important areas of operational performance.
Fewer provider calls: A reduction in calls suggests that providers need fewer manual interactions to resolve administrative questions.
Fewer pending claims: Reducing data-related pending claims can help prevent unnecessary delays caused by missing or inaccurate information.
However, these figures should not be interpreted as a 68% reduction in all claim denials or a 68% improvement in hospital collections. They refer specifically to data-related pending claims.
Why centralized provider data matters
Provider information affects multiple parts of the healthcare payment process.
For example, an outdated provider record can create problems with:
- Provider identification.
- Network participation.
- Claims processing.
- Payment updates.
- Provider directory accuracy.
When provider information is maintained through a consistent digital process, organizations can reduce repeated corrections across departments.
This makes provider data management an important part of revenue cycle automation rather than simply an administrative IT project.
Case Study 4: AI-Assisted Utilization Management and Faster Authorization Decisions
Documented workflow approach
Elevance Health has also expanded its use of artificial intelligence in utilization management.
This is particularly relevant to revenue cycle operations because authorization delays can affect scheduling, clinical workflows and the financial performance of healthcare providers.
How manual authorization creates delays
Before a procedure or certain other services can be performed, providers may need approval from the patient’s health plan.
The administrative process can require staff to:
- Review the patient’s medical records.
- Identify relevant clinical information.
- Compare documentation with medical policies.
- Submit authorization requests.
- Respond to requests for additional information.
- Monitor approval status.
When these tasks require repeated manual handling, the process can delay care and increase administrative costs.
How AI supports the process
Elevance Health uses AI for selected utilization management requests.
The technology identifies and matches relevant information from patient medical records against applicable medical policies and clinical guidelines.
When the required criteria are met, the request can be routed to an automation engine for approval.
This enables qualifying requests to receive touchless approval without requiring the same level of manual processing.
The company has explained that this can help providers move toward same-day scheduling rather than waiting days for an administrative response.
An important safeguard is that AI does not automatically make prior authorization denial decisions. Denials continue through the appropriate clinician-led review process.
Implications for provider revenue cycle management
Faster authorization decisions can help providers reduce financial uncertainty before delivering services.
For example, an outpatient surgical center may need authorization before scheduling a procedure.
If the process is delayed, the center may experience:
- Rescheduling and administrative work.
- Additional patient communication.
- Delayed service delivery.
- Uncertainty about payment eligibility.
- Additional work for authorization specialists.
Automating appropriate approval workflows can reduce these problems.
However, providers must still verify that authorization requirements are satisfied and maintain appropriate clinical documentation.
Case Study 5: AI-Based Provider Data Management and Administrative Accuracy
Provider data quality is another important part of Elevance Health’s automation strategy.
Healthcare organizations exchange large amounts of provider information through spreadsheets, templates, system exports and other formats.
Manually reviewing and updating this information can create errors.
Incorrect records can affect provider directories, claims administration and payment-related processes.
The automation process
Elevance Health uses AI-powered tools to analyze, standardize and correctly file provider information within its systems.
The process helps address inconsistencies across incoming data formats.
Instead of relying entirely on manual review, AI supports the identification and organization of provider records.
This work forms part of a broader provider directory accuracy initiative.
Reported results
In a February 2026 interview, Elevance Health described achieving more than 90% accuracy in provider information through this work.
Improved provider data can support:
- More accurate provider directories.
- Better information consistency.
- Fewer administrative corrections.
- More reliable claims processing.
- Timelier payment-related updates.
The result is important because provider data is used across several connected healthcare processes.
An inaccurate record can create problems long after the information originally entered the system.
Practical application for healthcare providers
Hospitals and medical practices can apply the same principle to their internal provider master data.
For example, an organization can automate checks for:
- Missing National Provider Identifier information.
- Inconsistent provider names.
- Incorrect practice locations.
- Outdated contact details.
- Incomplete enrollment records.
Automated checks should flag questionable records for review rather than changing important financial or credentialing information without appropriate controls.
What These Automation Cases Reveal About Revenue Cycle Management
The five examples show that process automation can improve different stages of healthcare administration. They also demonstrate why organizations should look beyond the number of automated tasks.
The most important improvements come from connecting information, reducing repeated work and resolving problems earlier.
Comparison of the documented initiatives
| Initiative | Main problem addressed | Reported outcome |
|---|---|---|
| Unified claims workflow | Disconnected claims systems | One processing interface for approximately 40 million monthly claims |
| Health OS and EMR integration | Missing clinical information | 73% fewer LOI denials in one hospital system |
| Claims efficiency | Repeated provider interactions | 19.5% fewer provider calls |
| Centralized claims data | Data-related pending claims | 68% reduction |
| AI utilization management | Manual authorization reviews | Touchless approvals for qualifying requests |
| AI provider data management | Inconsistent provider information | More than 90% information accuracy |
The outcomes come from different initiatives and reporting periods. They should not be combined into one overall performance figure.
The connection between payer automation and provider revenue
A health plan and a hospital have different financial responsibilities.
A payer manages benefit administration, claim adjudication and payment decisions. A provider manages patient billing, charge capture, claim submission, collections and accounts receivable.
However, their workflows are connected.
Consider a simplified example:
- A patient receives treatment at a hospital.
- The hospital submits an authorization request when required.
- The health plan reviews the available clinical information.
- The hospital provides additional documentation if needed.
- The service is delivered and the provider submits a claim.
- The payer processes the claim and determines payment.
- The provider reconciles the payment and follows up on any outstanding balance.
If the authorization or claims process becomes faster and more accurate, the provider may spend less time resolving administrative issues.
This is why payer-side automation can have a meaningful effect on provider revenue cycle performance even when the technology does not directly manage hospital billing.
How Healthcare Organizations Can Apply These Automation Lessons
The practical value of Elevance Health process automation revenue cycle case studies is not limited to large insurance companies.
Hospitals, physician groups, outpatient centers and healthcare billing departments can apply similar principles to their own operations.
The best approach is to identify where administrative work creates delays and then select automation based on the underlying problem.
1. Automate repetitive eligibility and authorization checks
Insurance eligibility and authorization verification are common sources of administrative work.
A healthcare organization can use automated workflows to:
- Retrieve available insurance information.
- Verify coverage before scheduled services.
- Identify missing authorization requirements.
- Track authorization status.
- Alert employees when additional documentation is needed.
These processes can reduce manual verification work and help identify problems before services are delivered.
2. Connect EHR and billing systems
Disconnected clinical and billing systems can create gaps between completed services and submitted claims.
A better integration process should transfer relevant information between systems without requiring employees to enter the same details repeatedly.
For example, when a clinical encounter is completed, the appropriate documentation and charge information should become available to the billing workflow.
This can support:
- More complete charge capture.
- Faster claim preparation.
- Reduced manual data entry.
- Better visibility into unbilled services.
- Fewer missing-information errors.
3. Use automated claims work queues
Billing teams often manage hundreds or thousands of claims at different stages.
A centralized work queue can organize claims according to their current status.
Useful categories include:
- Ready for submission.
- Awaiting documentation.
- Rejected by the clearinghouse.
- Pending payer review.
- Denied.
- Awaiting payment.
- Requiring appeal or follow-up.
Automation can assign routine tasks, identify aging claims and notify the appropriate employee when action is required.
Complex denials and disputed claims should remain under qualified human review.
4. Improve provider and patient data accuracy
Incorrect patient demographics, insurance details and provider records can create avoidable billing problems.
Organizations should introduce automated validation at the point where information enters their systems.
For example, a patient registration workflow can flag missing insurance information before the encounter reaches the billing department.
This is generally more efficient than discovering the same problem after a claim has been rejected.
5. Measure automation through financial and operational KPIs
Automation should be evaluated through measurable improvements rather than the number of tasks completed by software.
Important revenue cycle metrics include:
| KPI | What it measures |
|---|---|
| Days in accounts receivable | How long payments remain outstanding |
| First-pass claim acceptance rate | Percentage of claims accepted without initial rejection |
| Denial rate | Percentage of claims denied by payers |
| Clean claim rate | Percentage of claims submitted without identified errors |
| Days to bill | Time between service delivery and claim submission |
| Authorization turnaround time | Time required to receive an authorization decision |
| Cost to collect | Administrative cost of collecting payments |
| Net collection rate | Percentage of collectible revenue actually collected |
These metrics help determine whether automation is improving the financial performance of the organization.
Which Revenue Cycle Processes Should You Automate First?
The Elevance Health process automation revenue cycle case studies highlight several technologies and operational approaches. However, not every healthcare organization needs to implement all of them.
A small physician practice may have different priorities from a large hospital system.
The right investment depends on transaction volume, administrative costs, existing software, claim problems and available technical resources.
Compare the main automation options
| Automation approach | Best suited for | Main consideration |
|---|---|---|
| Robotic process automation | Repetitive tasks across existing applications | Can be sensitive to interface changes |
| EHR and billing integration | Clinical-to-billing information exchange | Requires reliable system connectivity |
| AI-assisted document processing | Extracting information from medical and billing documents | Requires accuracy checks and human oversight |
| Intelligent claims workflows | Claims routing and adjudication support | Needs clear business rules and exception handling |
| AI-assisted denial analytics | Identifying denial patterns and root causes | Depends on reliable historical data |
| Provider data automation | Maintaining accurate provider records | Requires validation and governance |
Which process should you automate first?
Choose eligibility verification when:
- Staff repeatedly check insurance coverage manually.
- Missing insurance information creates preventable denials.
- The organization processes a high volume of patient registrations.
Choose authorization automation when:
- Authorization requests regularly delay scheduling.
- Staff spend significant time collecting clinical documents.
- Requests frequently remain pending because information is incomplete.
Choose claims workflow automation when:
- Employees move between multiple payer portals.
- Claims require repeated manual status checks.
- Billing specialists spend too much time on routine follow-ups.
Choose EHR and billing integration when:
- Clinical information must be entered into billing systems manually.
- Charge capture is delayed.
- Completed services are not consistently transferred into billing workflows.
Choose denial analytics when:
- Denials are increasing.
- The organization cannot identify recurring denial reasons.
- Managers need better visibility into payer-specific problems.
Five questions to ask before purchasing automation software
Before selecting a platform, revenue cycle leaders should evaluate five areas.
1. Does it integrate with existing systems?
Check compatibility with the organization’s EHR, practice management software, clearinghouse and payer connections.
A solution that creates another disconnected system may increase administrative work instead of reducing it.
2. Can it handle exceptions?
Not every claim follows a predictable path.
The software should identify incomplete records, conflicting information and unusual claim situations. It should route these cases to qualified employees rather than process them blindly.
3. Can the organization measure financial improvements?
Ask vendors to demonstrate how their solution will affect measurable indicators such as denial rates, days in accounts receivable, cost to collect and staff productivity.
Avoid relying exclusively on projected savings or general efficiency claims.
4. Does it protect sensitive healthcare information?
Healthcare organizations must consider HIPAA requirements, access controls, audit logs, encryption, vendor agreements and applicable security responsibilities.
Automation does not remove the organization’s responsibility to protect patient information.
5. Is the implementation financially justified?
Consider the complete cost of ownership, including:
- Software licensing.
- Integration and implementation.
- Staff training.
- Ongoing maintenance.
- Vendor support.
- Compliance and security reviews.
A smaller automation project with a measurable operational benefit may be a better starting point than a costly enterprise-wide transformation.
A practical implementation sequence
For organizations that are new to revenue cycle automation, a phased approach can reduce implementation risk.
- Identify the biggest operational bottleneckReview claim denials, pending claims, authorization delays and manual staff activities.
- Establish baseline performanceRecord current processing times, error rates, staff hours and collection metrics.
- Select one high-volume processStart with a repetitive workflow that has clear rules and measurable outcomes.
- Run a controlled pilotTest the automation with a limited group of users or transactions before expanding.
- Compare results and expand graduallyMeasure actual improvements against the original baseline and address exceptions before scaling.
This approach helps organizations avoid paying for technology that does not solve their most expensive operational problems.
Frequently Asked Questions
What is Elevance Health’s approach to revenue cycle process automation?
Elevance Health focuses on improving claims administration, provider data accuracy, clinical information exchange and authorization workflows. Its approach combines automated processes, AI-supported tools and connected healthcare systems.
How many claims does Elevance Health process each month?
Elevance Health’s documented claims automation case study reports approximately 40 million claims processed monthly. Its unified claims workflow helps employees manage this volume through centralized information and automated processing support.
How did Elevance Health reduce authorization denials?
Through electronic medical record integration, Elevance Health helped a large New York hospital system retrieve missing clinical information automatically. The implementation reduced Lack of Information denials by 73% for Medicaid patients in 2024.
What role does AI play in Elevance Health’s automation strategy?
AI supports claims processing, utilization management, provider data validation and workflow optimization. It helps identify relevant information, organize administrative tasks and route qualifying authorization requests for automated approval.
What can hospitals learn from Elevance Health process automation revenue cycle case studies?
Hospitals can learn to prioritize accurate data exchange, automated authorization workflows, centralized claims management and early identification of billing problems. These improvements can reduce repetitive administrative work and help prevent avoidable delays.
Does revenue cycle automation eliminate manual billing work?
No. Automation can handle repetitive activities such as eligibility checks, document processing, claims routing and status updates. Employees are still needed for complex denials, payment disputes, unusual claims and decisions requiring professional judgment.
What are the most important revenue cycle automation KPIs?
Important measurements include:
- Claim denial rate.
- First-pass claim acceptance rate.
- Days in accounts receivable.
- Authorization turnaround time.
- Clean claim rate.
- Cost to collect.
- Staff productivity.
Organizations should establish baseline measurements before implementation to determine whether automation produces meaningful improvements.
Is AI automation suitable for every healthcare organization?
Not necessarily. AI automation is most useful when an organization has reliable data, repeatable workflows and sufficient transaction volume. Smaller practices may benefit more from basic eligibility verification and billing integration before investing in complex AI platforms.
The most important lesson from Elevance Health’s approach is that successful revenue cycle automation starts with better-connected information and well-designed workflows. Healthcare organizations should identify their biggest administrative bottlenecks, automate suitable repetitive processes and measure the resulting improvements before expanding their investment.