Claims & Contract Management

Artificial intelligence (AI) and computer automation are finally beginning to impact healthcare. Payers are implementing generative AI to improve the customer experience. Researchers at Stanford use AI to review X-rays and detect pathologies in seconds. Today, AI and automation can remind patients about appointments and even provide a portion of their treatment via robotic surgery devices. While groundbreaking AI and automation technologies are in the news, adoption by the majority of healthcare providers has been slow despite research showing these tools could eliminate up to $360 billion in spending. It's a startling statistic that illustrates the reality of AI and automation applied to the revenue cycle: These tools quite literally can pay for themselves. The case for applying artificial intelligence and automation in healthcare Successful revenue cycles depend on thousands of daily tasks, which means efficiency lies at the heart of these endeavors. However, there are a lot of improvement to be made. Experian Health's State of Claims Survey 2022 shows the current state of the average healthcare revenue cycle: Reimbursement cycles are running longer. Claim errors are on the rise. Denials are increasing. More than one-half of U.S. hospitals reported financial losses in 2022. A 2023 America Hospital Report (AHA) report showed: 84% of hospitals admit the cost of complying with payer reimbursement requirements is increasing. 95% report spending more time on pursuing prior authorization approval. Over 50% of hospitals and health systems have more than $100 million tied up in A/R for claims six months old. These challenges stem from the increasing complexities of working with third-party payers, but also the by-hand human workflows embedded within provider revenue cycles. The State of Claims Survey 2022 showed that 61% of providers say they rely too heavily on manual processes and lack the automation they need to streamline reimbursement. As costs rise and revenue cycles tighten, there is increasing pressure to do more with less—faster. However, chronic healthcare staffing shortages have only exacerbated how hard it is for providers to get paid. Technology solves many of the problems plaguing healthcare's revenue cycle. AI and automation offer better revenue cycle management tools with fewer errors, less manual work, and more streamlined processes. How AI and automation improves revenue cycles Increasingly complicated reimbursement processes are the perfect testing ground for new technologies. These tools can improve the revenue cycle from the first point of patient contact to collections long after the procedure is over. For example, AI and automation software can greatly reduce errors and increase the accuracy of claims information before submission. When billing becomes more accurate, it lessens the volume of rejected claims, which take up an inordinate amount of staff resources and lengthen the time from service delivery to reimbursement. But AI and automation also impact the backend of the patient encounter by helping collections teams prioritize accounts most likely to pay. Four applications for AI and automation in the revenue cycle include: 1. Applying automation to patient registration The revenue cycle begins at patient registration, and that's also where providers can begin to apply technology to increase cash flow downstream. Patient registration is often cumbersome, an in-person process tied to a clipboard, paper, and open office hours. Yet Experian Health's State of Patient Access 2023 report shows that 73% of patients want to handle these processes online. Self-scheduling offers patients more flexibility for scheduling appointments when they want and on their preferred digital device. It can remove the friction from a frustratingly manual paperwork process while decreasing no-shows with automated messaging by text and email. Experian Health's automated patient scheduling software reduces time spent on traditionally manual scheduling tasks by 50%. Providers that select these tools increase their patient show rate to nearly 90%. From a revenue cycle perspective, providers that implement online self-service scheduling can see up to 32% more patients each month—which is money in the bank. 2. Finding hidden financial resources to reduce bad debt Experian Health's Coverage Discovery® automates the insurance verification process to match patients' responsibility with the best financial resources possible given their policy limits. Coverage Discovery scans proprietary databases and historical information for primary, secondary, and tertiary coverage. The platform seeks to find all available financial resources to lower the volume of accounts that end up as write-offs or in collections. In 2022, Coverage Discovery found $64.6 billion in patient coverage. In 2023, this software discovered previously unknown financial options for 32.1% of patient accounts, giving these customers more options for reducing debt. 3. Preventing denials by improving data quality Many claims are rejected by payers each day simply due to human error. Some of the most common reasons for claims errors include missing or inaccurate information caused by manual processes. From eligibility verification errors to incorrect insurance details, when paperwork is still by hand and this complex, it's far more likely to make an error than not. Experian Health's Patient Access Curator software automatically verifies eligibility and coverage while scanning patient documentation for obsolete or inaccurate data. The software leverages artificial intelligence and robotic process automation (RPA) to apply computer rigor to previously manual workflows to reduce manual errors. Significantly, this new technology performs these tasks in seconds, freeing up staff time and improving the patient experience. 4. Using artificial intelligence to prevent and mitigate denials How much does the endless pursuit of denials management tie up potential revenue? One survey showed half of hospitals report more than $100 million in delayed or unpaid claims at least six months old. The good news is that 85% of the errors that lead to denied claims are preventable with the help of existing technology. Experian Health's AI Advantage™ solution works in two critical areas to prevent denials before they happen—and correct any denied claims quickly: At the front end of the claim, by correcting errors before submission. AI Advantage - Predictive Denials spots the submissions most likely to kick back from the payer. This early warning system reduces the volume of denials by flagging claims with errors stemming from human mistakes or payer requirements changes. At the back end of the claim, for those rejected by the payer. AI Advantage - Denial Triage takes the volume of claims rejections and prioritizes them by those with the highest ROI for the provider organization. Not all denials offer the same volume or potential for revenue collection. This solution helps prioritize the highest returns quickly to increase revenue collection. Benefits of applying AI and automation to healthcare's revenue cycle There is little argument across the healthcare industry that the strategies that once worked to create a healthy revenue cycle still apply. Fortunately, today's AI and automation software allow these organizations to modernize their approach to these complexities—and win the revenue cycle game. The benefits of applying modern AI and automation tools at every point of the revenue cycle are substantial: Faster and more accurate patient scheduling and registration. No more manual data searches that tie up staff time. Fewer data entry tasks that lead to errors. Fewer claim denials. Less time spent chasing claims. Fewer days in A/R. More cash on hand. A high-performing revenue cycle is possible with the latest technology tools. Experian Health offers a suite of technology solutions that utilize artificial intelligence and automation designed to get providers paid faster, free up staff time, and improve the patient experience. Improving the revenue cycle is a necessity, and Experian Health helps healthcare organizations achieve this goal.

The relationship between hospitals and payers has often carried an undercurrent of tension. Stacks of paperwork, complex claims rules and manual adjustments are a recipe for disrupted cash flow and time-consuming rework. With profit margins hanging in the balance, providers need the reimbursement process to move forward without a hitch. To the relief of revenue cycle managers, recent developments in digital technology are paving the way for more effective claims management. Case in point: Experian Health's recent acquisition of Wave HDC, which brings together a suite of advanced patient registration solutions for faster and more accurate claims management at the front end of the process. Shifting sands in the hospital-payer relationship could increase denials For healthcare organizations, getting paid in full- and on-time hinges on seamless communications with payers. Any missteps can lead to revenue losses, with denied claims and delayed payments being the outcomes providers most want to avoid. Payers will automatically deny claims that have errors or missing information, while disputes and slow processing times can seriously hamper a hospital's cash flow. The sources of potential conflict have been pretty steady over time, stemming from complex billing processes, frequent changes to payers' requirements, and a lack of standardization between payers.  Tension created by the cost of services and the need to control healthcare costs is a constant in the revenue cycle. Recently, a major shift in dynamics has occurred with the widespread adoption of artificial intelligence by payers. This enables them to process – and deny – claims with unprecedented speed and scale, leaving providers struggling to catch up. On a recent webinar, Makenzie Smith, Experian Health Product Manager for AI AdvantageTM, explained how this change was reshaping the relationship between payers and providers: “So many payer decisions are now being driven by artificial intelligence. Insurers are reviewing and denying at scale using intelligent logic, leaving providers fighting harder for every dollar… Many revenue cycle managers will stick in their comfort zone because operating margins are tight and changing course seems risky. But given this change in payer behavior, the cost of staying the course could put organizations at risk.” How AI-powered revenue cycle management solutions help close the gap between payers and providers Providers are increasingly leveraging digital technology to level the playing field with payers. Integrated software and automation give revenue cycle management teams the right data in the right format and at the right time to respond to queries promptly and accurately. These solutions enable teams to work more efficiently, so they can process more claims in less time. Experian Health's flagship AI-based claims management solution, AI AdvantageTM, is a prime example. This tool predicts and prevents denials by identifying patterns in payer behavior and flagging claims with a high probability of denial so specialists can intervene before the claim is sent to the payer. This works alongside ClaimSource®, which automates clean claim submissions at scale. Using a single application, all claims are prepared and submitted with all necessary documentation, reducing the risk of denial due to missing or inaccurate information. Integrating Wave HDC's data capture technology for comprehensive claims management In November 2023, Experian Health acquired Wave HDC, which specializes in using AI-guided solutions to capture and process patient insurance data at registration with unrivalled speed and accuracy. This gives Experian Health clients access to a single denial management solution, known as Patient Access Curator. This new technology is a single click solution that spans eligibility verification, coordination of benefits, coverage and financial status checks with near-100% accuracy in less than 30 seconds. Crucial registration data can be captured in real time as soon as the patient checks in for an appointment, with no need to chase and update data post-registration. A single inquiry can search for all the essential insurance and patient demographics instantly, enabling better use of staff resources and smoother communications with payers. Tom Cox, President of Experian Health, says the move “allows us to quickly scale our portfolio with advanced logic and AI-powered technology to help solve one of the biggest administrative problems providers face today, which is claim denials.” Accurate patient data from the outset is key to preventing downstream denials, many of which originate in patient access. By reducing errors and enabling faster processing times, this comprehensive approach to denial management will help strengthen the relationship between providers and payers, ensuring timely payments and clean claims. Contact Experian Health today to find out how AI and automation can help build a successful relationship between providers and payers – and drive down denials.

Contracts govern the revenue cycle, but negotiating contracts and ensuring compliance can feel increasingly unmanageable as mergers and acquisitions, ongoing staffing challenges, and the sheer volume of contracts, plans, and provisions make contract management a massive project for healthcare providers. Tricia Ibrahim, Director of Product Management at Experian Health, shares her insights on a challenging environment heading into 2024. Providers are grappling with mounting complexity, an explosion of data, and continuing pressure to maximize efficiency and revenue. But, according to Ibrahim, healthcare contract management software is evolving to meet these challenges—and helping providers find clarity amid the complication. Q1: What are the major challenges with healthcare contract management as we move into 2024? “I think what clients are most concerned with, especially leading into 2024, is the complexity of payer contracts,” says Ibrahim. A typical provider may manage hundreds or thousands of contracts, each one with a range of plans and provisions that affect the bottom line. “Being able to negotiate better contracts is a key concern,” says Ibrahim, “but clients increasingly feel outgunned and overwhelmed by the amount of information involved.” Accessing and analyzing data effectively is more critical than ever. “When providers come together with payers to negotiate contracts, it can be difficult for them to evaluate the contract that the payer is putting in front of them,” in part because it's hard to know how their current contract is performing or how contract provisions will play out in dollars and cents, Ibrahim explains. “Underpayments and denials are a constant struggle. Also, providers need to understand how volume and patient mix will factor in.” Contract management has a direct effect on revenue and the bottom line. Negotiated terms may or may not cover actual costs. A small change in terms might have an outsized effect due to high volume. Denied claims, underpayments, downcoding and late payments can slow the revenue cycle and reduce the amount of revenue providers receive. “At the same time, we're also starting to see a greater interest in collaboration between providers and payers,” says Ibrahim. “Having additional visibility allows both parties to have more meaningful discussions and move toward solutions that work for everyone.” Q2: What are providers doing to take on these challenges? “Many providers are investing in technology,” says Ibrahim. “A 2023 analysis by Bain & Company found that 80% of healthcare executives had accelerated software and IT investment over the past year in response to mergers and acquisitions, staffing shortfalls, and an increasing need for efficiency.” As contract management becomes more complex, providers are also reaching for more powerful healthcare contract management software tools to manage data—and leverage it to negotiate contracts effectively and monitor contract compliance over time. Q3: How can healthcare contract management software like Experian Health's Contract Manager and Contract Analysis help providers negotiate better contracts? “Having meaningful information backed by data changes the dynamic,” Ibrahim says. “It allows you to have a more strategic conversation. You can say, 'You're supposed to pay us 45 days from the receipt of the claim, but it's been taking 140 days.'” Data provides objective information and can point the way toward measurable improvements going forward. “Our Contract Analysis module allows for the provider to audit payer contract performance,” says Ibrahim. That's not only helpful for tracking what's happened to date; it's also useful for projecting how a new contract might work going forward. “We're able to use historical claims to create scenarios that show how a new contract would affect payment. Sometimes, payers will keep reimbursement rates the same where you have a lot of volume and give you an increase where you don't. When you use our solution to run these types of analyses, you get a more effective understanding of proposed terms.” Q4: Once contracts are in place, how can healthcare contract management software help providers improve compliance? “Detailed analysis is key, and small discrepancies can have a significant impact,” says Ibrahim. “One of our clients, a large academic provider on the medical group side, spotted a trend where they were being underpaid by 10 cents to 50 cents on their EKGs. These kinds of variances typically go unnoticed, but they found 20 or 30 claims to submit.” The payer acknowledged the underpayment and issued the few dollars' difference. “Then the provider decided to look at their contract to see how far back they could appeal. It turned out they were able to go back a significant amount of time. When they added up the underpayments, it equated to $850,000. They ended up settling for $750,000,” Ibrahim says. OrthoTennessee, a Knoxville-based orthopedic practice with multiple locations and more than 50 physicians, uses Experian Health's Contract Management software for healthcare to find inaccuracies, make appeals, and audit contracts at scale. Using Experian Health's Contract Management platform, OrthoTennessee had an 86% success rate for appeals in 2022. “That's the power of the solution: You can really identify trends,” says Ibrahim. Monitoring compliance is a continuous effort: “We’ve done a lot of work with our clients to understand what their evolving needs are. We’ve been named Best in KLAS [by healthcare IT research firm KLAS] multiple years in a row. That recognition has centered around engagement—being engaged with our clients, so we understand what the trends are, what challenges they’re facing, and how we can help solve problems in the most efficient manner.” Q5: What role do regulations play in shaping contract management solutions? “Regulation drives different reimbursement methodologies, [such as] bundled payments or value-based care,” says Ibrahim. “Part of our challenge is making sure we are always evaluating new regulations and ensuring that our system is agile enough to support these new methodologies. “Because regulation never stops, it actually drives a lot of the innovation we do. The No Surprises Act, which came into effect in 2021, requires providers to provide patients with a good faith estimate of costs. We've been able to help clients establish an estimated median rate, which can be useful for estimates that involve non-contracted payers.” As an additional benefit, healthcare contract management software also helps providers spot opportunities. “One of our clients identified 26 plans with enough volume to support additional contracts,” says Ibrahim.  “Providers can even use these solutions to evaluate whether a market exists for a new piece of technology to deliver state-of-the-art care. Understanding performance is a powerful tool.” Q6: Early in our conversation, you said there was a growing interest in collaboration among providers and payers. What does it mean to take a collaborative approach in this context? “I think it's really important for providers and payers to have collaborative communication, to engage in productive conversations where they can work together instead of against each other,” says Ibrahim. “That's how we're going to deliver more integrative care and reduce costs. It’s how we’re going to arrive at coverage options that work for all parties, by developing good relationships between providers and payers. “For our part, Experian Health is continuing to expand Contract Manager to provide data analytics that clearly show the cost of care and the expected reimbursement for various types of services, so providers can evaluate contract performance, identify potential areas of improvement, and have meaningful conversations with payers. “At the end of the day, we all have a common goal: delivering appropriate care at the right time for patients,” Ibrahim concludes. “To progress toward that goal, payers, providers and partners like Experian Health are going need to work together.” These conversations start with a common set of data, so that everyone at the table understands where the opportunities to collaborate and improve may lie—and where the path forward may begin. Learn more about Experian Health's Healthcare Contract Management software and how it can help your organization negotiate and manage contracts effectively and efficiently, even in an increasingly complex environment.

Experian Health ranked #1 in Best In KLAS for our ClaimSource® claims management system and Contract Manager and Analysis product – for the second consecutive year. The rankings were revealed in the annual 2024 Best in KLAS Awards – Software and Services, published on February 7, 2024. The Awards recognize the top software and services vendors that are helping American healthcare professionals deliver the best possible patient care, based on feedback from thousands of providers. Experian Health topped the list in two categories: ClaimSource ranked #1 in Claims Management and Clearinghouse. This automated and scalable solution reduces denials and increases revenue through a single application. The addition of an artificial intelligence component this year (AI AdvantageTM) is helping providers cut denial rates to just 4%, compared to an industry average of more than 10%. Contract Manager and Analysis ranked #1 in Revenue Cycle: Contract Management. This product levels the playing field with payers by monitoring compliance with contract terms and recovering underpayments. It also arms providers with financial models of proposed contracts, so they can negotiate more favorable terms. Case study: See how Hattiesburg Clinic in Mississippi uses ClaimSource to automate claims management and reduce denials. The awards come as the industry grapples with ongoing staffing challenges and rising claim denials. In Experian Health's 2023 report on the healthcare staffing crisis, 100% of respondents saw staffing shortages affect revenue cycle management and patient engagement. As the pressure continues, revenue cycle technology offers a way to increase efficiency and improve financial performance.  “Healthcare professionals face immense pressures, ranging from financial strains to staffing shortages and the very real issue of clinician burnout,” says Adam Gale, CEO and Founder of KLAS Research. “We want to provide actionable insights that will ultimately alleviate burdens and enhance clinician success.” For Tom Cox, President of Experian Health, the awards reflect a continuing commitment to help providers optimize operations and patient engagement using data-driven insights and technology. “This recognition from KLAS recognizes our dedication to deliver innovative solutions that not only improve the financial health of providers but also the patient experience. Receiving this award two years in a row is an honor as we remain steadfast in our commitment to simplifying healthcare through technology.” Find out more about how ClaimSource and Contract Manager and Contract Analysis helps healthcare organizations increase efficiency and boost financial performance.

Racing against the clock to troubleshoot billing issues, claims bottlenecks and staffing shortfalls are just part of an average day for healthcare revenue cycle managers. It's hard enough to maintain the status quo, never mind driving improvements in denial rates and net revenue. With integrated artificial intelligence (AI) and automation, many of these challenges in revenue cycle management (RCM) can be alleviated – and with just a single click. Real-time coverage discovery and coordination of benefits software reduces errors and accelerates accurate claim submissions. This eases pressure on busy RCM leaders, so they have the time to focus on improving the numbers that matter most. Top challenges in revenue cycle management Efficiency is the currency of revenue cycle management. Maximizing resources is not just about keeping dollars coming in the door but about making the best use of each team member's time and expertise. The ever-present call to “do more with less” is probably the biggest challenge. Breaking that down, some specific concerns that consume more time and resources than RCM managers would like, are: Complex billing procedures: With hundreds of health payers operating in the US, each offering different plans with different requirements, providers have their work cut out to ensure claims are coded and billed correctly. Any errors in verifying a patient's coverage, eligibility, benefits, and prior authorization requirements can lead to delays and lost revenue. More claim denials: Inaccurate patient information and billing codes guarantee a denial. Beyond the rework and revenue loss, denied claims leave patients with bills that should not be their responsibility to pay, causing confusion, frustration, and higher levels of bad debt. Garbage in, garbage out. Patient payment delays: A few years back, patients with health insurance represented about a tenth of bills marked as bad debt. Now, this group holds the majority of patient debt, according to analysts. The rise in high-deductible health plans combined with squeezed household budgets means patients are more likely to delay or default on payments. Providers must be on the lookout for ways to help patients find active coverage and plan for their bills to minimize the impact of these changes. How can AI-powered revenue cycle management solutions help? The Council for Affordable Quality Healthcare (CAQH) annual index report demonstrates how much time can be saved using software-based RCM technology. Case in point: switching from manual to automated eligibility and benefits verification could save 14 minutes per transaction. This adds up quickly when daily, monthly, and yearly transactions are factored in. Predictive analytics can be used to pre-emptively identify and resolve issues and support better decision-making, giving providers a head start on those elusive efficiency gains. Three specific examples of how automation, AI and machine learning can streamline the front-end and solve challenges in revenue cycle management are as follows: 1. Upfront insurance discovery to find and fill coverage gaps Confirming active coverage across multiple payers gives patients and providers clarity about how care will be financed. But this can be a resource-heavy process when undertaken manually. Coverage Discovery uses automation to find missing and forgotten coverage with minimal resource requirements. By unearthing previously unidentified coverage earlier in the revenue cycle, claims can be submitted more quickly for faster reimbursement and fewer write-offs.With Experian Health's recent acquisition of Wave HDC, clients now have access to faster, more comprehensive insurance verification software solution. The technology works autonomously to identify existing insurance records for patients with self-pay, unbillable, or unspecified payer status and correct any gaps in the patient's coverage information. The patient's details are updated automatically so that a claim can be submitted to the correct payer. 2. Real-time eligibility verification and coordination of benefits As it gets harder to figure out each patient's specific coverage details, it also makes sense to prioritize automated eligibility verification. Eligibility Verification uses real-time eligibility and benefits data to confirm the patient's insurance status on the spot.Similarly, Wave's Coordination of Benefits solution, now available to Experian Health clients through Patient Access Curator, integrates directly into registration and scheduling workflows to boost clean claim rates. It automatically analyzes payer responses and triggers inquiries to verify active coverage and curate a comprehensive insurance profile. This means no insurance is missed, and the benefits under each plan can be coordinated seamlessly for more accurate billing. 3. Predictive denials management to prevent back-end revenue loss Adding AI and machine learning-based solutions to the claims and denials management workflow means providers can resolve more issues pre-claim to minimize the risk of back-end denials. Use cases for AI in claims management might include: Automating claims processing to alleviate staffing shortages Reviewing documentation to reduce coding errors Using predictive analytics to increase operational efficiency Improving patient and payer communications with AI-driven bots All of these contribute to a front-loaded denials management strategy. While prevention is often better than a cure, AI can be equally effective later in the process: AI AdvantageTM arms staff with the information they need to prevent denials before they occur and work them more efficiently when they do.Whatever new challenges may pop up on the RCM horizon, AI and automation are already proving their effectiveness in helping providers save time and money. But more than that, they're giving busy RCM leaders the necessary tools to start future-proofing their systems for persistent and emerging RCM challenges. Learn more or contact us to find out how healthcare organizations can use AI and automation to manage current revenue cycle management challenges with a single click.

Healthcare is a challenging profession. Providers understand that their mission of care delivery is fueled by the revenues they capture; after all, it is the business of healthcare. However, capturing revenues through the claims management process is burdensome and complex. Denials are all too common, hampered by inefficient workflows and manual tasks. As a result, it slows down reimbursement and impacts revenue. Moving toward reliable claim acceptance requires the strategic use of automation and technology to reduce denials. These initiatives accelerate the cycle of payments, improve cash flow, and ease strains on existing staff. This article takes a deep dive into the challenges of healthcare claims processing and strategies to help providers transform the claims management process. Challenges of healthcare claims processing The healthcare claims management process desperately needs modernization and optimization. Last year, an Experian Health survey showed that three out of four providers say reducing claims denials is their top priority. What's making it so difficult for providers to get paid? The healthcare reimbursement journey Let's start with the typical claims management process. Step 1: Prior authorization The first issue is that most generally accepted standard practices in healthcare claims processing create a long journey for provider reimbursements. This journey starts even before patient care, at eligibility and preauthorization. The American Medical Association (AMA) states, “Prior authorization is a huge administrative burden for physician practices that often delays patient care.” While prior authorization may help insurance companies reduce the cost of “unnecessary” treatments, the data shows it's having the opposite effect on the providers themselves. An AMA physician survey shows that 86% of prior authorizations lead to higher overall utilization of services. The practice doesn't appear to help patients, either; the AMA says 94% of doctors report care delays related to prior authorization, and 82% say patients abandon their treatment plans due to prior authorization struggles. Step 2: Data capture The second part of healthcare claims processing begins after the patient encounter. It involves many manual tasks, often leading to errors and claim denials. Intake and billing specialists must gather data from multiple sources for coding claims, including electronic health records (EHRs), physician notes, diagnosis codes, paper files, and the patients themselves. These workflows require significant manual data entry and review, which is impacted further when codes or insurance reimbursement requirements are out-of-date in provider systems. A recent survey shows that 42% of providers report code inaccuracies, and 33% say missing or inaccurate claims data as the top reasons for rejected claims. Step 3: Processing claims denials Post-submittal, there's more work when claims bounce back. It's part of the claims management process with the most inefficiencies and friction, costing the average provider millions annually. Healthcare providers experience Experian Health survey—but that number is rising. Responses from Experian Health's State of Claims 2022 report revealed that 30% of respondents experience denials increases of 10 to 15% annually. In June 2022, Experian Health surveyed 200 revenue cycle decision-makers to understand the current state of claims management. Watch the video to see the results: These challenges illustrate the need for modern and optimized healthcare claims processing. With this lens in place, healthcare providers can apply more effective claims management strategies to increase claims accuracy and reimbursement and reduce denials. Innovating your claims management strategy Healthcare professionals and organizations can proactively address challenges in the claims acceptance process by implementing effective strategies to optimize revenue cycle management. This effort should include the following: A cohesive and comprehensive claims management processNew approaches to outdated claims management workflows will address gaps, inefficiencies, and errors. Upgrading to a turnkey insurance claims manager can reduce denials and speed up claims processing. Address data quality and consolidationThe sheer volume of data required for healthcare claims processing increases the risk of errors. If the data isn't accurate at the front end, it's a fast track to denial. But claims go through multiple touch points in disparate systems without a single source of control and oversight. Organizations can employ standards for data intake to reduce inaccurate or incomplete patient information and duplicates and leverage technology to aggregate data from the multiple sources needed for claims processing. Implement best practices for denial workflowsClaim denial management on the backend of healthcare claims processing is even more challenging than capturing patient data at the front end of the encounter. Managing claims denials is time-consuming, and delays reimbursements, but denial workflow technology can streamline all follow-up activities. With this support, billers have less administrative work and can stretch farther, alleviating the burden of staffing shortages. Deploy tools for analysis and prioritizationA claims management platform can automatically analyze the components of each claim. With this information, the technology can prioritize denials workloads so high-impact accounts get the most attention. Upgrade claims technology automation with artificial intelligence (AI)Providers can transform claims management with a technology update. According to the State of Claims report, almost half of organizations replaced legacy healthcare claims processing technology in the past year. A vital component of this upgrade includes expanded automation capabilities that stretch the workforce further. Solutions like AI Advantage™ can help speed up the claims management process by predicting and preventing denials. Add prior authorization softwareAnalysis suggests that healthcare could automate up to 33% of manual tasks. Research on the benefits of automation showcases its potential for decreasing errors and other reimbursement obstacles. With prior authorization software, task assignment is seamless, and AI adds even more functionality with predictive capabilities. Accelerate claim follow upMonitoring claim status is another aspect of the payment ecosystem that heavily impacts provider cash flow. Technology automates much of this workflow. Organizations can adopt functionality that eliminates manual follow-up tasks to accelerate an unwieldy process. These solutions enable providers to respond quickly to issues, enhancing productivity beyond basic ANSI 277 claims status responses. Technology is the unifying thread behind a cohesive claims management strategy for any healthcare provider struggling with a high rate of denials. While 61% of providers lack automation in the claims/denials process, increasing evidence shows these tools drive revenue cycle efficiencies that transform claims denials management. Forward-thinking organizations like Summit Medical Group Oregon—Bend Memorial Clinic (BMC) leverage Enhanced Claim Status and Claim Scrubber to achieve a 92% primary clean claims rate. Schneck Medical Center uses AI Advantage to denials by an average of 4.6% each month. Implementing effective claims management strategies Strategies rooted in reliable, practical technology transform the claims management process. Healthcare organizations benefit from AI-driven automation solutions as part of an overarching claims management strategy that streamlines workflows, reduces denials, and boosts cash flow. Experian Health offers a portfolio of provider claims management tools to help organizations realize effective claims management process improvements to get paid faster. Learn more about the No. 1 Best in KLAS 2023 Claims Management and Clearinghouse tools or contact us to see how Experian Health can help improve your claims management processes.

Like many other sectors, healthcare providers are increasingly turning to automation and artificial intelligence (AI) to get more accurate data and better insights. However, the pace of change is somewhat slower in healthcare, due to legacy data management systems and data silos. As efforts to improve interoperability progress, providers will have more opportunities to deploy AI-based technology in innovative ways. This is already evident in claims management, where executives are keeping an ear to the ground to learn of new use cases for AI to help maximize reimbursements. This article looks how AI and automation can help providers address the problem of growing denials, and how Experian Health's new solution, AI Advantage™, is helping one particular provider use AI to reduce claim denials. Using AI and automation to address the claims challenge Experian Health's 2022 State of Claims survey revealed that reducing denials was a top priority for almost three quarters of healthcare leaders. Why? High patient volumes mean there are more claims to process. Changing payer policies and a changing payer mix layer on complexity. Labor shortages mean fewer hands on deck to deal with the workload, while rising costs and tighter margins mean the stakes are higher than ever. Manual claims management tools simply cannot keep up, resulting in lost time and revenue. Automation and AI can ease the pressure by processing more claims in less time. They give providers better insights into their claims and denial data, so they can make evidence-based operational improvements. AI tools achieve this by using machine learning and natural language processing (NLP) to identify and learn from patterns in data, and synthesizing huge swathes of data to predict future outcomes. While AI is ideal for solving problems in a data-rich environment, automation can be used to complete rules-based, repetitive tasks with greater speed and reliability than a person might be able to achieve. Discovering new use cases for AI in claims management Providers are finding new applications for AI as utilization becomes more widespread. Some examples of different use cases include: Automating claims processing to alleviate staffing shortages: AI tools can use natural language processing (NLP) to extract data from medical records and verify accuracy before adding the information to claims forms. This saves staff significant amounts of time and effort. Augmenting staff capacity and creating an efficient working environment can also help with recruitment and retention. Reviewing documentation to reduce coding errors: AI can perform the role of a “virtual coder,” using robotic process automation and machine learning to sift through medical data and suggest the most appropriate codes before claims are submitted. Using predictive analytics to increase operational efficiency: One of the most effective ways to improve claims management is to review and learn from past performance. AI can analyze patterns in historical claims data to predict future volumes and costs, so providers can plan accordingly without simply guessing at what's to come. Improving patient and payer communications with AI-driven bots: The claims process requires large amounts of data to be exchanged between providers, payers and patients. AI-driven bots can be used to take care of much of this, for example by automatically responding to payers' requests for information during medical necessity reviews, or handling basic inquiries from patients. Case study: How Community Medical Centers uses AI Advantage to predict and prevent claims denials Community Medical Centers (CMC), a non-profit health system in California, uses Experian Health's new solution, AI Advantage, which uses AI to prevent and reduce claim denials. Eric Eckhart, Director of Patient Financial Services, says they became early adopters to help staff keep up with the increasing rate of denials, which could no longer be managed through overtime alone. “We were looking for something technology-based to help us bring down denials and stay ahead of staff expenses. We're very happy with the results we're seeing now.” AI Advantage reviews claims before they are submitted and alerts staff to any that are likely to be denied, based on patterns in the organization's historical payment data and previous payer adjudication decisions. CMC finds this particularly useful for addressing two of the most common types of denials: those denied due to lack of prior authorization, and those denied because the service is not covered. Billers need up-to-date knowledge of which services will and will not be covered, which is challenging with high staff turnovers. AI Advantage eases the pressure by automatically detecting changes in the way payers handle claims and flagging those at risk of denial, so staff can intervene. This reduces the number of denials while facilitating more efficient use of staff time. Eckhart says that within six months of using AI Advantage, they saw 'missing prior authorization' denials decrease by 22% and 'service not covered' denials decrease by 18%, without any additional hires. Overall, he estimates that AI Advantage has helped his team save more than 30 hours a month in collector time: “Now I have almost a whole week a month of staff time back, and I can put that on other things. I can pull that back from outsourcing to other follow-up vendors and bring that in house and save money. The savings have snowballed. That's really been the biggest financial impact.” Hear Eric Eckhart of Community Medical Centers and Skylar Earley of Schneck Medical Center discuss how AI Advantage improved their claims management workflows. AI AdvantageTM: two steps to reducing claim denials AI Advantage works in two stages. Part one is Predictive Denials, which uses machine learning to look for patterns in payer adjudications and identify undocumented rules that could result in new denials. As demonstrated by CMC, this helps providers prevent denials before they occur. Part two is Denial Triage, which comes into play when a claim has been denied. This component uses advanced algorithms to identify and segment denials based on their potential value, so staff can focus on reworking the denials that will make the biggest impact to their bottom line. At CMC, denials teams had previously focused on high value claims first, but found that smaller payers sometimes made erroneous denials that could add up over time. AI Advantage helped root these out so Eckhart's team could resolve the issue with payers. Integrated workflows reveal new applications for AI and automation AI Advantage works within ClaimSource®, which means staff can view data from multiple claims management tools in one place. In this way, AI Advantage fits into the same workflow as tools that providers may already be using, such as Claim Scrubber, Enhanced Claim Status and Denials Workflow Manager. These integrations amplify the benefits of each individual tool, giving healthcare providers better insights into their claims and denials data. With richer data, organizations will find new ways to leverage AI to increase efficiency, reduce costs and boost revenue. Discover how AI Advantage, Experian Health's new claims management solution, can help providers use AI to reduce claim denials.

The complexities of healthcare claims management are a widespread, costly issue. While the American Medical Association (AMA) blames prior-authorizations as the main cause, it's clear that hospitals struggle to collect on predicted revenues often for months after they provide the service. It's not a sustainable situation as the costs of care delivery increase, staffing shortages drive up labor overhead, and inflationary pressures stretch healthcare providers to their breaking point. There is no question the claims denial process is ripe for innovation – and that's where artificial intelligence (AI) comes in. A 2022 Experian Health survey shows over one-half of healthcare providers increasingly turn to AI-driven healthcare claims management software to reduce claim denials. Tom Bonner, Principal Product Manager at Experian Health, says, “Adding AI in claims processing cuts denials significantly. AI automation quickly flags errors, allowing claims editing before payer submission. It's not science fiction – AI is the tool hospitals need for better healthcare claims denial prevention and management.” Common reasons for medical claim denials Revenue cycle leaders place healthcare claims management as their number one issue in 2023. Experian Health's survey showed the three most common reasons for medical claim denials were: Needs more data and analytics to identify submission issues. Manual claims processing and a lack of automation. Insufficient training for staff. The sheer volume of changes to CPT codes is another issue affecting HCM or healthcare claims management. Experian Health identified more than 100,000 payer policy changes from March 2020 to March 2022. These shifts necessitate a never-ending cyclic need to train new staff, increase the risk of claim rejections, and slow down manual workflows in healthcare claims denials management. How can healthcare providers improve claims processing and overcome these challenges? Real-life ROI with AI in claims processing AI in claims processing solves these and other common revenue cycle problems. This technology is the innovation healthcare providers need to reduce denials and increase cash flow. AI can help at every point in the revenue cycle continuum, from improving the accuracy of payer data upfront to ensuring a clean claim and even targeting denials that yield the highest return. What real-life lessons does AI in claims management teach healthcare providers? Experian Health's new AI-powered solution includes AI Advantage™ - Predictive Denials and AI Advantage™ - Denial Triage, which is geared towards helping healthcare organizations reduce claim denials. Within six months of using AI Advantage, Schneck Medical Center reduced denials by an average of 4.6% each month. Claim corrections that formerly took up to 15 minutes to correct cut to just under five minutes. Even smaller ambulatory clinics like Summit Medical Group Oregon benefit from automating healthcare claims management. After implementing Experian Health's claims management software, the provider saw an immediate reduction in claims denials. Today, they boast a 92 percent clean primary claims rate. These results are typical across healthcare organizations that implement AI in claims processing. But what does the software do to clean up the complexities of claims management processing? How to avoid claim denials with AI In 2022, Experian Health surveyed 200 revenue cycle leaders around the country and identified technology shortfalls as a significant contributor to claims denials: 62% reported they lacked the data analytics to identify submission issues. 61% said manual processes and a lack of automation were significant problems. 33% suggested their healthcare claims management software was outdated or inadequate. Healthcare claims management upgraded with the inception of AI-driven healthcare claims management software. The benefits of these tools lie in their ability to predict potential issues before they occur by analyzing claims and providing a probability of denial that allows the end user to intervene and determine the appropriate collection. AI can also assist in identifying inaccurate claims, improving claims processing accuracy and revenue cycle management. By using automation and AI together, healthcare providers can gain better insights into their claims and denial data, resulting in improved financial performance and greater efficiency. Tom Bonner says, “AI in claims processing maximizes the benefits of automation for better claims processing, better customer experiences, and a better bottom line for healthcare providers.” How does healthcare claims denial management software work to improve the revenue cycle? AI identifies and prioritizes high-value claims after denial AI in claims processing goes beyond automating process-driven manual tasks. It also removes the guesswork from healthcare claims management. For example, staff is often left guessing which denied claims are the low-hanging fruit that they should process first. Staff must decide which denied claims have a higher likelihood of reimbursement and a higher dollar value to maximize their efficiency. Why would healthcare providers leave these high-value/high-return claims to a manual “best guess” estimation process? Yet that is standard operating procedure in most hospitals. AI in claims processing identifies and prioritizes high-value claims automatically. Experian Health's AI Advantage - Denial Triage goes to work when a claim is denied by identifying and intelligently segmenting denials based on potential value so that staff focuses on resubmissions with the most significant bottom line impact. This intelligent segmentation removes the guesswork, alleviates staff burdens, and eliminates time spent on low-value denials. But the front-end work AI software completes during healthcare claims management may be even more valuable. AI can prevent claims denials from occurring at all. AI proactively stops claim denials from occurring AI Advantage - Predictive Denials uses AI to identify undocumented payer adjudication rules that may result in new denials. It identifies claims with a high likelihood of denial based on an organization's historical payment data and allows them to intervene before claim submission. Experian Health also has other automated solutions that help facilitate claims management. ClaimSource® helps providers manage the entire revenue cycle by creating custom work queues and automating reimbursement processing. This intelligent healthcare claims management software ensures clean claims before they're submitted, helping to optimize the revenue cycle. The software also generates accurate adjudication reports within 24 to 72 hours to speed reimbursement. ClaimSource ranked #1 in Best in KLAS 2023, precisely for its success in helping providers submit complete and accurate claims. This tool prevents errors and helps prepare claims for processing. Because the claims are error-free, providers can optimize the reimbursement processes and get their money even faster. AI optimizes the claims process Another Experian Health solution, Enhanced Claim Status improves cash flow by responding early and accurately to denied transactions. This solution uses RPA to give healthcare providers a leg up on denied, pending, return-to-provider, and zero-pay transactions. The benefits include: Provides information on exactly why the claim denied. Speeds up the denials process. Automates manual claims follow-ups. Integrates with HIS/PMS or ClaimSource Automation frees up staff to focus on more complex claims. Denials Workflow Manager integrates with the Enhanced Claim Status module to help eliminate manual processes, allowing providers to optimize claims submission and maximize cash flow. How to reduce claim denials with AI and Experian Health There's no question that healthcare claims denials management is an unwieldy, time-consuming, and ever-changing process. Reimbursement is complex on its own, but human error plays a large part in missed opportunities and lost revenue. With AI in healthcare claims management, the revenue cycle streamlines and transforms. Any healthcare provider seeking faster reimbursement and a better bottom line knows that improving claims management is critical to better cash flow. AI healthcare claims management software offers provider organizations a way to achieve these goals. Contact Experian Health today to reduce claim denials and improve your claims management process with AI Advantage.

With artificial intelligence (AI) continuing to dominate conversations among healthcare's strategic thinkers, it's clear that recent innovations in this field could herald a step-change in healthcare delivery. AI's ability to mimic human intelligence and machine learning (ML)'s capacity to learn from vast amounts of data means these technologies are fast becoming indispensable tools for healthcare leaders who want to optimize operations. Understanding how they work – and where to apply them for maximum impact – will be crucial to stay ahead of the competition as the revenue cycle landscape evolves. This article breaks down the what, why and how of AI technology in healthcare, and includes a look at Experian Health's new AI-based claims denial solution, AI Advantage™. Understanding machine learning and AI in healthcare The terms “machine learning” and “artificial intelligence” are often used indiscriminately, but what do they mean in a healthcare context? Generally speaking, AI is a machine's ability to perform cognitive functions that would normally be associated with humans, such as interacting with an environment, perceiving information, and solving problems. It can spot patterns, learn from experience and choose the right course of action to achieve a desired outcome. This includes natural language processing, robotics and machine learning. In healthcare, AI might be used to transform diagnosis through the analysis of medical images, expedite drug discovery by monitoring side effects, improve the safety and efficiency of surgery through robotics, and support patients to take ownership of their own health through health monitoring and wearables. Machine learning is a broad term that covers the processes used to extract meaning from (usually large) datasets to create and train a predictive model. It will look for historical patterns in input and output that a human eye might miss, and generate recommendations based on outcome parameters defined by the user. For example, it can look at patients' electronic health records to identify those who may be at risk of specific medical conditions so they can be offered appropriate advice. Another useful application is in predicting service demand, for more efficient appointment scheduling and resource allocation. Further subsets of machine learning include supervised learning, where training data is labelled with the desired outcomes that the algorithm should aim to detect, and unsupervised learning, which has no predefined targets and is useful for discovering patterns, insights and anomalies. Unlocking the AI Advantage™: how AI can reduce claim denials and improve financial performance The transformative potential of ML and AI technology in healthcare isn't limited to clinical decision-making and patient engagement: optimizing revenue cycle operations is a particularly attractive place to leverage the technology. It can be used to identify and reduce billing errors, enhance coding accuracy, and predict revenue leakage. This results in faster payments, better use of staff time and fewer claim denials. However, Experian Health's State of Claims 2022 survey revealed that while 51% of providers were using automation, only 11% of providers had integrated AI technology into their claims processes. Experian Health's new AI-based claims solution is specifically designed for those looking to take the next step to leverage AI to predict and prevent denials. AI Advantage takes a two-pronged approach to reduce the risk of denials and expedite any rework that may be needed. AI Advantage – Predictive Denials examines claims before they are submitted and calculates the probability of denial, based on thresholds set by the provider. It incorporates historical payment data and undocumented payer claim processing behavior to evaluate individual claims in real-time, with a level of speed and accuracy that would be unachievable using manual processes alone. High-risk claims can be edited before submission to reduce the risk of denial. AI Advantage – Denial Triage evaluates and segments denials based the likelihood of reimbursement following resubmission and prioritizes the work queue based on financial impact. It learns from payers' past decisions to formulate recommendations with increasing accuracy. This means staff can eliminate guesswork and focus their attention on the denials that will be most likely to yield results. See how Experian Health's AI-powered solution works to reduce and prevent denials. Challenges to watch out for when implementing AI While the benefits are clear, the rise of AI in healthcare applications also brings some challenges. Here are some key questions to consider for smooth implementation: How reliable is the data underpinning AI technology? AI tools are only as good as the data they're analyzing. Without high-quality, structured data, they will be unable to make accurate predictions. Providers need to ensure that data is available in a usable format and free from errors. Partnering with a reliable third-party vendor can help ensure all the relevant boxes are ticked. Does the technology integrate easily with existing workflows and software systems? Integrating new tools with the existing RCM infrastructure can be complex. Organizations often have legacy systems that may trigger interoperability issues, limiting effective data exchange and requiring staff to log in to multiple interfaces. A single vendor solution can mitigate for this. For example, AI Advantage fits together seamlessly with the industry-leading claims processing tool, ClaimSource®. Experian Health's consultancy team are also on hand to ensure smooth implementation. Does the software protect data privacy and security? Healthcare data is subject to multiple privacy and security regulations, such as HIPAA. Any new technology that processes data must comply with regulations and industry best practice. Being able to reassure patients that their data is safe is also an important driver of patient loyalty. What does the future hold for AI technology in healthcare? Looking ahead, the role of ML and AI in both patient-facing healthcare processes and revenue cycle operations is only going to grow. Predictive analytics will give staff increasingly powerful insights and recommendations to maximize reimbursement, while minimizing the burden on the workforce. Emerging technologies such as robotic process automation and natural language processing will offer more sophisticated and comprehensive workflow solutions, while AI's ability to continually learn and improve means providers that leverage AI will be better placed to make full use of their data and adapt to evolving trends and challenges. Discover how AI Advantage™ is helping Experian Health's clients transform their healthcare operations.