7 top healthcare revenue cycle challenges and how to overcome them

by Experian Health 6 min read April 19, 2022

7-top-healthcare-revenue-cycle-challenges-and-how-to-overcome-them

Healthcare revenue cycle challenges exist at every stage of the patient journey, beginning with patient access and extending all the way through claims, billing, payment and collections. However, digital tools and analytics can help providers tackle their top healthcare revenue cycle challenges.

“The complexity of our reimbursement structures and the complexity of billing mean a variety of aspects impact revenue cycle management,” says Tricia Ibrahim, Director, Product Management, Contract Manager, Hospital at Experian Health. “Technology, regulations, changing contractual obligations and payer policies, people, processes, billing—each of these complexities adds to the challenge.”

Revenue cycle management (RCM) issues can also lead to revenue loss if not addressed. Data and analytics, digital tools and automation can help providers manage complexity and adapt to evolving patient needs. Here are seven of the top healthcare revenue cycle challenges and how providers are taking them on:

1. Problems with patient access

Consumers accustomed to using mobile apps and online services to shop and do their banking look for seamless digital experiences when they’re choosing a provider, scheduling appointments and managing pre-appointment activities like registration and insurance verification. In a new consumer survey by Experian Health and PYMNTS, 77% of patients who were not currently using digital tools for healthcare said they would be interested in switching to a provider that offered a patient portal. The automated tools that make up your digital front door make a huge difference in how patients engage.

Together with accurate estimates and convenient payment options, digitally focused Patient Access Solutions help providers enhance the patient journey and improve registration accuracy. Manual processes require more staff time up-front; human error can lead to claim denials or billing errors later in the cycle. Automating streamlines the process. Offering patient intake software that can be accessed online or via a mobile device provides the flexible and familiar digital experience they expect in today’s world.

2. Poor collections recovery rate

As high deductible health plans have patients taking more responsibility for their healthcare costs, patients are finding it more difficult to pay. Bigger bills often translate into a greater potential for confusion, more questions about insurance coverage, and a greater need for financing options. Providers need effective collections strategies to boost revenue and lower bad debt write-offs as more focus shifts to the patient as a payer.

A patient-centered payments strategy helps patients better understand their estimated costs, insurance coverage, and payment options. To help patients navigate the financial process successfully and navigate this healthcare revenue cycle challenge, providers will need to support them with:

  • Clear, accurate estimates that show patients how much they’ll owe up-front
  • Payment options that include multiple payment methods, including cards, Apple Pay, and e-checks
  • Navigating payment plans to manage large balances
  • A process that encourages payment before service or at the point of service to reduce collections down the line

When providers have to collect, digital tools and analytics can help optimize the collections process by prioritizing accounts that are most likely to pay, automating billing and messaging workflows, and even tracking the effectiveness of outside collections agencies.

3. Billing errors

Claim denials are a drag on workflow, sending staff into a repetitive loop of claims submission, denial, correction, and delay—and throwing a wrench into revenue flow. A denied claim typically slows reimbursement by 16 days. Worse, claim denials are on the rise: 69% of healthcare leaders in an MGMA Stat poll reported that denials increased at their organizations in 2021.

Replacing manual processes with automated workflows can reduce billing errors and A/R days. Integrated claims management software reviews claims for inaccurate coding before claims are submitted, easing demands on staff time, reducing claims denials, and shortening the time between billing and payment.

4. Underpayments in payer contracts

Missed payments and underpayments can add stress and volatility to your revenue cycle. Often, the source of these problems lies in payer contract issues.

“Payers often know your book of business better than you do,” says Ibrahim. “When you’re negotiating contracts, you need to be able to go through large amounts of data quickly and efficiently, so you can come to the table armed with information. One of the services we provide is contract analysis to help providers evaluate contract terms in real dollars and cents.” For active contracts, Healthcare Contract Management helps providers track inaccurate payments and hold providers accountable.

5. Changes in healthcare regulatory and compliance standards

New regulations are a constant in healthcare. However, this is one of the biggest healthcare revenue cycle challenges that providers need to keep up with. Failing to stay up to date with the ever-evolving compliance landscape can lead to claim denials, payment delays, and administrative and billing backlogs. Healthcare Regulatory Solutions, which includes systems for providing transparent, patient-friendly estimates, can make it easier to make regulatory compliance part of your regular business processes. A free No Surprises Act (NSA) Payer Alerts Portal keeps providers updated on how new NSA regulations are playing out.

6. Lack of data-driven metrics and insights

Gaining efficiencies in RCM means using analytics to provide a big-picture view of what’s happening throughout the enterprise. This perspective is not always the default in a busy healthcare practice or hospital. Yet, “Fixing claim after claim on an individual basis isn’t going to get you the efficiency you want,” says Ibrahim. “You need to identify trends to find the biggest opportunities to improve your results.”

Comprehensive data and analytics are key for providers that want to pinpoint and address areas of trouble. Here, disparate systems and siloed information can get in the way of creating the single view needed to diagnose the issues that are slowing down claims, billing, and payment. Revenue Cycle Management Analytics integrates client data with non-native standard Electronic Data Interchange sets to reveal opportunities for process improvements. By leveraging the right data, providers can optimize patient access productivity, billing efficiencies, reimbursements, and payer performance.

7. Potential security issues

Patient portals engage patients and empower them to schedule their appointments, review test results, or make payments. But as providers digitalize to improve the patient experience and boost the revenue cycle, patient identities and data may be at greater risk. Cases of medical identity theft reported to the Federal Trade Commission rose more than 532% between 2017 and 2021. Medical identity data is particularly valuable to thieves, bringing 20 to 50 times more money than data from financial sources.

Securely authenticating patients is critical as a safeguard for both providers and patients. Identity theft damages the patient experience and erodes trust, while dealing with the resource and reputational damage fraud can cause is a major potential liability for providers. Working with vendors that provide extensive Patient Portal Security and digital tools that protect patient identities without causing friction or frustration is essential to keeping patient data safe without alienating the patients in the process.

Prevent healthcare revenue cycle challenges with automation

Revenue cycle management healthcare challenges are among the great tests facing providers right now. But improvements in digital tools and analytics are helping providers keep revenue flowing while keeping both compliance and the patient experience in focus. Find out more about how Experian Health’s Revenue Cycle Management Solutions can help your organization meet the challenges of modern RCM.

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Key takeaways: Revenue cycle teams can use automation to reduce repetitive work and apply AI where data-driven prediction, matching or prioritization can improve a workflow. Experian Health’s 2025 State of Claims survey found that 41% of providers now face denial rates of 10% or higher, while 68% say submitting clean claims is more challenging than a year ago. Patient Access Curator™ (PAC) uses AI to support front-end data validation and insurance discovery, while AI Advantage™ helps teams predict denial risk and prioritize denial follow-up. Artificial intelligence (AI) and automation can support administrative work in healthcare. In the revenue cycle, teams depend on accurate information, timely decisions and efficient follow-up to keep claims moving. In revenue cycle management, AI and automation can help organizations reduce manual checks, find data gaps, predict denial risk and prioritize work queues. These tools are most useful when they support staff judgment, payer expertise and compliance oversight. They can handle repetitive, data-heavy tasks so staff can focus on exceptions and decisions that need human review. In 2023, McKinsey & Company reported that research suggests effectively deploying automation and analytics could eliminate $200 billion to $360 billion of spending in U.S. healthcare. For revenue cycle leaders, the practical question is where to apply those capabilities first. The case for applying AI and automation in healthcare Revenue cycle teams juggle many daily tasks. Staff collect and verify patient information, confirm eligibility, identify the right payer, submit clean claims, monitor status, work denials and manage collections. Small data gaps at the beginning of the process can create downstream rework and delays. Rework also consumes staff time, adding to these operational pressures. As costs rise and revenue cycles tighten, there is increasing pressure to do more with less. Experian Health’s 2025 State of Claims survey found that 54% of providers say claim errors are increasing and 90% of claim denials are reworked with at least some human review before resubmission. Providers are also managing broader financial and administrative pressures. The American Hospital Association has reported that prior authorization requirements, claim audits, denials and other payer policies add administrative burden and cost for hospitals and health systems. These requirements also consume staff time to appeal denials and manage payer processes. AI and automation are different but complementary. Automation follows defined rules to complete repeatable work. AI models can identify patterns in data, predict risk and help teams decide where to focus attention. When used together, they can support more consistent revenue cycle workflows. How AI and automation can support revenue cycle workflows Revenue cycle management automation and AI are most useful when tied to a specific workflow and a measurable operational problem. The goal is to help teams act earlier, reduce avoidable rework and focus staff time where judgment is needed most. For example, automation can complete rule-based eligibility checks. AI can help identify claims with a higher likelihood of denial. In insurance discovery workflows, AI can also help identify coverage that wasn’t captured at registration. When these tools fit into existing workflows, they can support more consistent decisions and reduce manual work. Three practical applications include: 1. Improving front-end data quality with Patient Access Curator Patient and coverage information collected early in the revenue cycle can affect downstream claim outcomes. Incomplete or outdated demographic details, eligibility responses, coordination of benefits or Medicare Beneficiary Identifier information can create problems that lead to claim delays or denials later in the cycle. Experian Health’s Patient Access Curator helps prevent claim denials by validating demographics, eligibility, insurance discovery, coordination of benefits and Medicare Beneficiary Identifier data in seconds. PAC’s AI and machine learning capabilities help improve match accuracy, coverage sequencing and data confidence by writing the validated data back into the host system and sequencing payers before the claim is created. This automates work that would otherwise require manual coverage checks. 2. Using insurance discovery to find coverage not captured at registration When active coverage isn’t identified during registration, claims may be delayed or submitted with incomplete insurance information. Insurance discovery looks for coverage that may not have been captured during registration. Patient Access Curator includes insurance discovery as part of its front-end validation workflow. It can help identify and correct missing or incorrect insurance information so claims can be submitted with more complete coverage data. 3. Using AI to prevent and prioritize denials Even with strong front-end processes, some claims still require additional attention. AI can help claims teams decide which claims to review before submission and which denials to work first after payer response. Experian Health’s AI Advantage supports two denial management use cases:1. AI Advantage – Predictive Denials uses a client’s historical claims data and Experian’s knowledge of payer rules to identify claims with a high likelihood of denial before submission so teams can take corrective action.2. AI Advantage – Denial Triage uses AI to segment denials and identify those with the highest potential for reimbursement. This approach can help teams prioritize with more confidence. Rather than treating every claim or denial the same way, teams can use predictive models to focus on the work that needs the most attention. Potential benefits of AI and automation in the revenue cycle A high-performing revenue cycle depends on timely, accurate and consistent work. AI and automation can help providers modernize that work without losing the expertise of the people who manage complex payer and patient situations every day. When applied to the right workflows, these tools can help organizations: Reduce manual data searches that take staff away from higher-value work Improve front-end data quality before claims are created Identify missing or incorrect coverage information earlier Spot claims that may be at higher risk of denial Prioritize denied claims by potential reimbursement Reduce rework caused by inaccurate or incomplete information Give staff more consistent information for follow-up decisions A focused AI strategy starts with the workflow problem, uses data that is relevant to that problem and keeps staff in control of judgment-based decisions. A more proactive approach to revenue cycle management Revenue cycle teams can move from reactive work toward a more proactive approach: catch errors earlier, validate coverage before claims are created and prioritize the claims and denials that need the most attention. Experian Health offers revenue cycle solutions that use AI and automation in targeted ways to support front-end data quality, reduce rework and manage denials. Patient Access Curator supports registration and coverage validation, while AI Advantage supports denial prediction and triage. Learn more about Experian Health’s Patient Access Curator and AI Advantage.

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