What is revenue cycle management in healthcare?

by Experian Health 8 min read September 10, 2024

what is revenue cycle management in healthcare

As economists offer up their best guesses for the US economy over the coming year, healthcare leaders know one thing for sure: no matter what happens, they need solid revenue cycle management (RCM) processes to remain financially sound and deliver high-quality care.

Revenue cycle management connects the financial and clinical aspects of care by ensuring that providers are properly reimbursed for their services, through accurate and efficient billing and claims management processes. Keeping the financial scales tipped in the right direction is a growing challenge: data from the American Hospital Association shows that payer delays and denials are driving up operational costs while slowing revenue. Many providers are turning to artificial intelligence (AI), automation and data analytics to eliminate inefficiencies and maximize reimbursement.

Factors that affect healthcare revenue cycle management

While revenue cycle math is pretty simple – money in versus money out – the reality is more complex. A tight grip on delivery costs is just one part of the equation. Most RCM efforts center around determining who owes what and collating the necessary documentation to secure prompt payment from each party. A few factors to consider include:

  • Are there reliable processes for capturing accurate patient information?
  • How quickly can coverage and pre-authorizations be verified?
  • Are claims and denials managed efficiently?
  • How easy is it for patients to understand and pay their bills?
  • Can RCM leaders monitor and analyze staff and agency performance?

Changing payer policies, patients’ financial status and data management demands add to the challenge.

The goal of revenue cycle management

To achieve the primary aim of getting reimbursed in full and on time, organizations must reduce billing errors, submit clean claims and refine operational efficiency so staff can stay laser-focused on high-value tasks. But it’s important to look beyond the spreadsheets: selecting the right tools to deliver a transparent and compassionate patient experience will boost the bottom line, too.

History and evolution of RCM

RCM has shifted from largely paper-based processes to sophisticated software-based systems in just a few decades. Few could have imagined how those early healthcare information systems of the 1970s would evolve as electronic health records, standardized coding frameworks and digital data processing came to the fore. Changes in regulation and reimbursement models furthered the need for advanced analytics. And now, the rise of healthcare consumerism drives demand for the industry to open its digital front door. Organizations that commit to digital transformation will be in a stronger position to navigate today’s RCM challenges and meet the needs of digitally native consumers.

Relationship between patient experience and RCM

Experian Health’s recently published State of Patient Access Survey 2024 reveals the extent to which the patient experience affects revenue. Integrating patient-centered principles into RCM processes improves patient satisfaction, makes it easier for patients to understand and pay their bills, and leads to better financial performance overall.

Steps in the healthcare revenue cycle

A typical revenue cycle management workflow in healthcare follows the patient’s journey. Each touchpoint in the patient’s journey is an opportunity to check that patients, payers and back-off teams have the information they need to expedite payment:

  • Scheduling – When the patient books an appointment, administrative staff verify the patient’s insurance eligibility. This is a chance to make sure pricing is transparent and give the patient an estimate for the cost of care.
  • Registration – Next, the provider captures the patients’ medical history, insurance coverage and other demographics. Correct patient information on the front end reduces the errors that cause rework in the back office.
  • Prior authorization – Front-end staff check whether the patient’s insurance provider requires prior authorization for the procedure or service they need. Skipping this step can lead to costly denials and rework.
  • Treatment and follow-up – After treatment, the back office collates billable charges and assigns a medical billing code to the claim. Accuracy is paramount, as reworking claim rejections can drain resources.
  • Claim submission – Then, the claim must be submitted to the payer. Accurate and timely submissions prevent rejections and reimbursement delays. If a claim is denied, it must be resubmitted as quickly as possible to avoid lost revenue.
  • Collections – Once the payer approves the claim, the patient’s out-of-pocket costs are calculated and billed. Providing a range of convenient payment methods will increase the likelihood of prompt payment.

Regulatory and compliance considerations

At each stage in the process, staff must stay mindful of the regulatory and compliance frameworks governing revenue cycle management. These are primarily patient-centered. For example, the Health Insurance Portability and Accountability Act (HIPAA) safeguards patient privacy and sensitive health information, while the No Surprises Act seeks to make pricing more transparent.

Failure to adhere brings severe reputational and financial risks, as made painfully clear by recent headlines about the cost of cyberattacks within the industry.

Common challenges in healthcare RCM

For most providers, avoiding the cycle of claim denials and rework is the biggest challenge. A survey of 1300 hospitals found that denials by commercial payers had increased by 20.2%, while Medicare Advantage denials had increased by 55.7% between January 2022 and July 2023. Reliance on inefficient manual processes to track and monitor claims does little to help. A 2023 CAQH report shows that switching from manual to electronic claim status inquiries could reduce the time spent on each transaction by 17 minutes, saving the medical industry more than $3.2 billion overall.

Providers are also collecting increasing sums from self-pay patients. Financial pressures and uncertainty around coverage mean many patients cannot fully cover their medical expenses. Improving their financial journey with accurate upfront estimates, clear and compassionate communications, and convenient payment methods will accelerate payments. Unfortunately, there’s still some way to go: the State of Patient Access Survey 2024 found that 64% of patients had not received a cost estimate before care, and of those that did, 14% reported final costs that were much higher than expected.

Financial impact analysis

To track the financial effects of these challenges, healthcare organizations should identify key performance indicators (KPIs) aligned to their specific priorities. Conducting real-time monitoring and analysis of patient access, collections, claims and contract management metrics can flag up opportunities to prevent revenue leakage and maximize income.

Read more about how to identify the right KPIs for your revenue cycle dashboard.

4 ways to improve revenue cycle management in healthcare

When it comes to implementing specific revenue cycle management solutions, the following four tactics are likely to yield the greatest return on investment:

  1. Automate Access
    A healthy revenue cycle begins with quick, accurate and efficient patient access systems. Automated, data-driven workflows reduce the errors that lead to denials and rework. Online scheduling allows patients to easily book appointments, while solutions like Patient Access Curator use AI to capture all patient data at registration with a single click.
  1. Increase collections
    Maximizing patient collections while fostering a positive patient experience can be a delicate balance. Patient access staff must be the patient’s advocate, while ensuring the organization collects what’s owed. Giving patients upfront estimates of their financial responsibility and offering appropriate financial plans makes it as easy as possible for them to pay. Collections Optimization Manager allows providers to focus their efforts on the right accounts, through highly predictive patient segmentation.
  1. Streamline claims
    Automating claims management is another way to use technology to accelerate reimbursement. Claims management software verifies that each claim is coded properly before being submitted. Encounters can be processed in real-time with automatic alerts to flag any issues before the claim is submitted. Experian Health’s flagship AI Advantage™ solution helps predict and prevent denials by checking claims before they are submitted and calculating the probability of denial. It evaluates and segments denials that occur based on the likelihood of reimbursement following resubmission, and prioritizes the work queue so staff make the best use of time.
  1. Increase reimbursement
    Healthcare organizations that don’t stay current on payer policy and procedure changes risk payment delays and lost revenue. Providers and payers must be on the same page to quickly resolve mismatches between expected and actual reimbursement amounts. Automated payer policy and procedure change notifications help providers strengthen relationships with payers and avoid payment delays.

How healthy is your revenue cycle? Our revenue cycle management checklist helps healthcare organizations catch inefficiencies and find opportunities to boost cash flow.

Case studies

  • See how automated revenue cycle solutions helped Stanford Health optimize their patient collections strategy.
  • See how Schneck Medical Center prevents claim denials with AI AdvantageTM
  • Hear how UC San Diego Health used automation to improve patient billing and drive collections.

Getting the most out of revenue cycle management software

These case studies demonstrate that a successful revenue management strategy has three essential ingredients: data, software and training. Experian Health’s “Best in KLAS” revenue cycle management solutions are built on proven technology and proprietary databases, to help staff find new opportunities to bring in revenue. Experienced consultants are on hand to guide staff and ensure workflows are set up for the best results.

The future of RCM

Whatever the economic outlook, technology’s defining role in the future of revenue cycle management is undisputed. Payers are already leveraging AI to their advantage, and patients have come to expect convenient digital transactions—any providers that fail to embrace AI and automation-based RCM solutions will fall behind the competition.

Learn more about how Experian Health’s revenue cycle management solutions generate more revenue for healthcare organizations.

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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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