Tag: ai advantage

Claims denials are a thorn in the side of any healthcare organization. Even with claims denial mitigation tools and processes in place, denials are growing. In Experian Health's State of Claims 2022 report, 30 percent of respondents said denials increased between 10% –15% annually. To combat rising denials, ensure faster reimbursements, and improve the revenue cycle, healthcare providers need new claims technology that focuses on efficiency. In this post, learn about the common challenges in traditional claims processing and how to implement automated or AI-based claims management technology to drive healthcare revenue cycle efficiency. Challenges in traditional claims processing When it comes to reimbursement, the odds of being paid do not always favor the healthcare provider. The complexity of claims makes for labor-intensive workflows in traditional reimbursement processing. Data is often culled from multiple systems, including electronic health records (EHRs), paper files, diagnoses, test results, insurance verification, and more. Providers lacking a streamlined set of workflows supported by claims technology, experience errors that can lead to denied claims. Three of the most common challenges in traditional claims processing include missing or incomplete claims information, payer-related problems, and a need for more staff, which slows down processing productivity. 1. Missing or incomplete claim information Missing data is also a huge issue in traditional claims processing. In fact, missing or incomplete data is one of the top reasons for claims denials, particularly in the area of prior authorization. These mistakes often begin upstream at the first point of patient contact and, if not corrected, snowball toward the inevitable denial. Compounding the problem is that disparate healthcare systems and workflows make it increasingly challenging to collect all the data effectively. The larger the healthcare provider, the more touchpoints for claims processing, creating back-and-forth workflows that can lead to miscommunication or the loss of information. 2. Payer-related challenges Just keeping up with changes in payer requirements is a full-time job. Payers often change reimbursement requirements, and providers aren't aware of these new adjudication rules. It requires strict monitoring of all payers, which is impossible for organizations to manage. Prior authorizations are also increasingly burdensome for providers to handle. An AMA survey found that 88 percent of physicians said these burdens were high or extremely high. Providers estimated they process 45 prior authorizations weekly, equivalent to 14 hours of staff time. 3. Reduced or new staff can't keep pace Another challenge is not having the workforce necessary to review claims to identify errors. Workforce shortages continue to impact every healthcare area. The chronic challenge of high workloads and short staffing means most teams work as quickly as possible, leading to preventable mistakes. Without advanced claim technology, staff manually handle heavy workloads, which is driving denials through the roof. The lack of staff also affects traditional claims processing by slowing denials resubmissions. A less efficient denials management process directly affects provider cash flow, creating more delays in getting paid. Resolving these challenges requires modern, advanced claims technology powered by automation and artificial intelligence (AI). By leveraging this technology for claims management, healthcare providers can solve these problems for greater reimbursement efficiency and a better bottom line. Best practices for implementing AI-based claims management technology Experian Health data shows 51% of healthcare providers currently leverage some software automation. However, only 11% had integrated AI technology into their organization. Mounting evidence suggests preventing healthcare claims denials starts with innovative AI-driven claims management technology. AI and automation applied to a claim technology solution can prevent claims denials on the front-end of the patient encounter and improve denial management on the back-end of the process. When evaluating how to implement advanced claim technology, consider these best practices: Start by identifying the pain points in existing claims processing workflows. Review claims denials and mitigation data and talk with existing staff to develop this list. If the organization leverages legacy reimbursement tools, consider how efficiency gaps affect the organization. Consider organizational goals and objectives for replacing manual workflows or upgrading legacy claims management technology. As the organization explores the benefits of advanced claim technology featuring AI, develop use cases for employing these tools for more effective claims management. Compare new product features to these real-life scenarios. Seek stakeholder feedback. All technology rollouts require significant buy-in at every level in the organization. Don't miss engaging with the boots-on-the-ground workforce using the claims technology Ensure the organization has the infrastructure to support the new platform long after it goes live. When evaluating new digital tools, keep these things in mind: Select AI-based claims technology that utilizes workflow customization to manage the entire reimbursement cycle. Seek out a solution that automatically reviews each line in a claim to check for errors so that first submissions are accurate. Leverage a system with automation features that eliminate error-prone manual processes. Choose a platform that enables denial prediction and mitigation. Find a product with denials workflows and enhanced claims monitoring functionality. AI technology is the game-changer for healthcare's skyrocketing claim denial challenges. These new tools deliver immediate value to an increasingly disjointed and complex reimbursement process. With the right technology, healthcare providers improve the claims processing efficiency to get paid faster. Transformative impact of Experian Health's advanced claims technology Experian Health is a leader in digitally transforming traditional claims processing. AI-powered technology can increase staff efficiency at every stage of the claims management process. Experian Health's AI Advantage™, part of the Best in KLAS ClaimSource® platform, is transforming provider claims processing. This software reduces the need for additional staff by automating manual tasks. It lessens the burden on existing teams by lightening their claims processing and denials management workloads. AI Advantage has two primary solutions affecting every stage of the claims management process: Predictive Denials identify undocumented payer rules resulting in new denials. This AI-driven solution finds the claims most likely to fail, flagging them back to payment processing for correction before they're even submitted to the payer. Denial Triage manages prioritization of denied claims. Advanced algorithms in this solution identify and flag denials based on their potential value. Organizations maximize their returns on denied claims by focusing on the resubmissions with the highest financial impact. It removes the guesswork from reworking claims, lessening staff workloads by eliminating time wasted on low-value cases. Another solution, Patient Access Curator, uses AI and robotic process automation to enable healthcare staff to capture all patient data at registration, with a single click solution that returns multiple results - all in 30 seconds.  Experian Health's automated and AI-fueled advanced claim technology improves provider reimbursement efficiency at every stage of the process. The efficiency-related benefits of AI for claims management include avoiding denials, accelerating denial mitigation, and getting paid faster. To explore these tools—and their extraordinary ROI, contact the Experian Health team today.

There is growing concern that the healthcare industry needs more clinical and administrative staff to handle care demands. The crisis affects patients beyond treatment delays or lower care quality. Staff shortages in the revenue cycle create problems with patient engagement, billing, and collections. A recent Experian Health survey reveals unanimous concerns among providers about the challenges posed by workforce shortages. But what are the root causes of staffing shortages in healthcare? Is there a remedy for healthcare organizations struggling to find the talent they need? This article dives into the survey findings and the ways healthcare providers can address staffing shortages effectively. Finding 1: Staff turnover is a significant cause of healthcare staffing shortages. 80% of providers report turnover between 11-40%. Nearly one in 10 say turnover is between 41-60%. The causes of staff shortages were evident before COVID. A rapidly aging Baby Boomer population and limited availability of training in areas such as nursing led to predictions that looming staff shortages were on the horizon. The pandemic exacerbated the situation, leading to a mass exodus of workers and The Great Resignation. Some reports show healthcare lost 20% of its workforce, including 30% of nurses. Today, the average hospital turns over one-quarter of its staff annually, an increase of more than 6% from the prior year. As a result, the State of Patient Access 2023 reported nearly 50% of providers say access to care is worsening. Simultaneously, healthcare is bogged down with administrative tasks. Increasing evidence shows providers must turn to automation software to decrease human workloads and stretch small teams further. These automated tools can: Create a seamless registration process for patients to improve care access, reduce no-shows, and reduce provider administrative burdens. Provide 24/7 patient scheduling and put patients in charge with self-scheduling options Automate patient outreach to increase collections and improve communication. Improve claims management, reduce denials, and free up existing staff from manual tasks. Automation can improve the work-life balance of healthcare staff, potentially closing the revolving turnover door, one of the most significant causes of staff shortages. For example, IU Health implemented automated guided scheduling, which helped scale their operations, reduce scheduling errors and improve staff efficiency. Finding 2: Finding and hiring staff is an undue burden for healthcare providers. 73% of respondents said finding qualified staff is difficult. 61% reported that meeting entry-level staff's salary expectations is a challenge. Healthcare organizations feel the staffing crisis at every level. A recent Medical Group Management Association (MGMA) poll cited the difficulties in hiring revenue cycle staff: 34% of respondents stated hiring medical coders is their biggest challenge. 26% stated billers were difficult to find. One-third said finding schedulers and prior authorization staff is hard. Other hiring challenges included revenue cycle management (RCM) managers. When and if healthcare providers find staff, bringing them into the fold is costly. Experian Health's staffing survey showed most organizations struggle to meet the salary expectations of even the least experienced members of their teams. The causes of staff shortages can be remedied by leveraging new artificial intelligence (AI)-powered tools. Tools like AI Advantage™ can automate and transform claim denials management, a problem costing healthcare providers around $250 billion annually. Experian Health's State of Claims 2022 survey showed the most common causes of denied claims include: Missing or incomplete prior authorizations. Failure to verify provider eligibility. Inaccurate medical coding. AI Advantage reduces denial rates by scrubbing claims and flagging errors before submission. After claim submission, the software prioritizes the most high-value denials for correction to maximize revenue generation. Organizations like Schneck Medical Center use these tools to reduce denials by 4.6% each month. The facility also increased the speed of claims submissions. Tasks that used to take 12 to 15 minutes to rework now process in less than five minutes, lessening the need for hiring more staff and improving the workloads of their existing team. Finding 3: Burnout is a top contributor to staffing shortages. 53% of poll respondents said staff burnout is a key cause of the current staff shortage. 48% said the new expectation for schedule flexibility and hybrid work models also contributes to the healthcare workforce shortage. Burnout is one of the most significant causes of staff shortages impeding high quality care and wreaking havoc on the revenue cycle. The latest data shows the percentages of clinical and administrative burnout in healthcare is approaching or exceeding 50% in most job categories: 56% of nurses report burnout symptoms. 54% of clinical staff. 47% of doctors. 46% of non-clinical staff. Cost-cutting and increasing care demands have led to increasing fatigue in healthcare staff. But technology exists to automate back office functions that could free up staff time. For example, organizations like Kootenai Health saved close to 60 hours of staff time in over 8 weeks by automating the presumptive charity process Patient Financial Clearance. Stanford Health used Collections Optimization Manager to cut 672 hours each month from overburdened back office staff. The COVID pandemic also changed expectations about how and where Americans should work. Remote work became normal; three years post-COVID, 58% of the American workforce report working remotely at least one day a week. The same data also shows that when workers have the chance to work virtually, 87% take it. Healthcare is not immune to the desire for more schedule flexibility. Becker's Hospital Review states, “Many workers desire the ability to work remotely, even if they only get the option a few days a week. Flexibility allows people to maintain work-life balance—and in a high-burnout field like healthcare, balance can be crucial.” Surveys show 31% of healthcare roles are remote full-time while 14% offer this flexibility part-time. The problem is that many healthcare positions cannot allow this flexibility—and the industry competes with others that do. To remain competitive, healthcare organizations must embrace technology to offer work flexibility. Cloud-based digital technology is beneficial in areas like the revenue cycle. For example, automated technology from Experian Health can: Use advanced analytics to streamline workflows. Facilitate patient self-service. Minimize staff time spent on manual tasks. AI-powered automation tools can lessen staff burnout by allowing them to work smarter. These tools provide the workforce with the scheduling flexibility they desire. Eliminate the causes of healthcare staffing shortages with better technology AI and automation technology in healthcare can lessen worker fatigue, lighten workloads, and give administrative workers the schedule flexibility they demand. Experian Health offers healthcare providers better technology to improve the lives of their staff, increase patient satisfaction, and generate more revenue. Download the survey or connect with an Experian Health expert today to learn how we can help your organization tackle the causes of healthcare staffing shortages effectively.

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.

By all forecasts, the healthcare worker shortage isn't going away. More than 80% of healthcare executives admit talent acquisition is so challenging it puts their organizations at risk. The latest survey from Experian Health shows complete agreement across the industry—the inability to recruit and retain staff hampers timely reimbursements. The side effects of the healthcare worker shortage are increased errors, staff turnover, and lower patient satisfaction. With the healthcare worker shortage becoming a chronic red flag on the list of industry challenges, is throwing more revenue at hiring the best answer? Experian Health's new report, Short-staffed for the long term, polled 200 healthcare revenue cycle executives to find out the effects of the continuing healthcare worker shortage on the bottom line. Respondents unanimous agreed that healthcare's recruitment problem is limiting their ability to get paid. Could investing in better revenue cycle technology to automate manual human functions be the answer to the healthcare recruiting dilemma? Effect of the healthcare worker shortage on healthcare revenue cycle Result 1: Providers losing money and patient engagement simultaneously. 96% of respondents said the healthcare worker shortage negatively impacts revenue. 82% of survey participants said patient engagement suffers when providers are short-staffed. Experian Health's latest survey showed almost unanimous agreement that the revenue cycle suffers significantly when providers are short-staffed. The only area of disagreement among revenue cycle leaders is whether patient collections or payer reimbursements are affected the most by the industry's lack of human talent. As revenue cycle teams struggle to cover their workload, the need for speed increases manual error rates. The Experian Health survey showed that 70% of revenue cycle teams say healthcare worker shortages increase denial rates. This finding reinforces an earlier survey showing nearly three of four healthcare executives place reducing claims denials as their top priority. As errors snowball, patient engagement and satisfaction begin to decline. Data entry errors impact claims submissions, resulting in billing mistakes that confuse and frustrate patients. Data errors often start at patient registration and persist through claims submission, creating denial reimbursement snarls and tying up cash flow. With the average denial rate above 11%, that's one in every 10 patients facing uncertainty around whether their bill will be paid. What's worse is that Experian Health's State of Claims Report shows denial rates increasing. While providers are leaning into increasing recruiting efforts to find the employees they need, is staffing up even possible in an era of chronic labor shortages? Technology offers healthcare providers new ways to handle revenue cycles without hiring more staff. For example, patient access software reduces registration friction, where up to 60% of denied claims start. Patient scheduling software automates access to care and gives customers greater control over their healthcare journey. It's a digital front door that engages patients with online options for managing care. On the backend of the revenue cycle, automation also offers a way to decrease reliance on manual labor to handle claims submissions. Automating clean claims submissions alleviates the denials burden, freeing up staff time and provider revenue streams.  Result 2: Staffing shortages heavily impact payer reimbursement and patient collections. 70% of those saying payer reimbursement has been affected the most by staff shortages also agree that escalating denial rates are a result. 83% of those saying patient collections have been affected most by staff shortages also agree that it’s now harder to follow up on late payments or help patients struggling to pay. Addressing healthcare staffing shortages is crucial for providing quality patient care, maintaining financial stability, and maximizing reimbursement in the complex healthcare reimbursement landscape. Staff shortages lead to reduced productivity within healthcare facilities, and existing teams may need to take on extra work to fill the gap. Overworked staff may be more prone to errors, leading to claims denials. Medical Economics says manual collections processes suffer due to the healthcare worker shortage. They state, “Mailed paper statements and staff-dependent processes are significantly more costly than electronic and paperless options, yet the majority of physicians still primarily collect from patients with paper and manual processes.” Technology exists for self-pay receivables that allow patients easy online payment options. Experian Health's Collections Optimization Manager offers powerful analytics to segment and prioritize accounts by their propensity to pay and create the best engagementstrategy for each patient segment. Advocate Aurora Healthcare took control of collections by using this tool and automated their collections processes, so that existing staff could focus on working with the patients who had the resources to handle their self-pay commitments. The software's automation and analytics features allowed the provider to experience a double-digit increase in collected revenues annually. Patients also benefit from collections optimization software. For example, Kootenai Health qualifies more patients for charity or other financial assistance with Experian Health's Patient Financial Clearance solution. In addition to automating up to 80% of pre-registration workflows, the software uses data-driven insights to carve out the best financial pathway for each patient. It's a valuable tool for overburdened revenue cycle teams that struggle to collect from patients. Kootenai Health saved 60 hours of staff time by automating these manual payment verification processes. Result 3: Recruiting alone isn't solving the healthcare worker shortage. Healthcare hiring is a revolving door, with 80% reporting turnover as high as 40%. 73% said finding qualified staff is a significant issue. A significant contributor to the healthcare worker shortage is the grim reality that these organizations are losing human resources to burnout and stress. Being short-staffed drags down the entire organization, from the employed teams to the patients they serve. But it's impossible for recruiting alone to fix the problem when more than 200,000 providers and staff leave healthcare each year. A recent study suggests that if experienced workers continue to leave the industry, by 2026, more than 6.5 million healthcare professionals will exit their positions. Only 1.9 million new employees will step in to replace them. The news worsens with the realization that nearly 45% of doctors are older than 55 and nearing retirement age. Artificial intelligence (AI) and automation technology in healthcare can cut costs and alleviate some of the severe staff burnout leading to all this turnover. However, one-third of healthcare providers have never used automation in the revenue cycle. A recent report states that providers could save one-half of what they spend on administrative tasks—or close to $25 billion annually—if they leveraged these tools. For example, Experian Health's Patient Access solutions can automate registration, scheduling and other front-end processes. AI can also help increase staff capacity and output without adding work volume. Experian Health's AI Advantage™ solution works in two critical ways to help stretch staff and improve their efficiency: The Predictive Denials module reviews the provider's historical rejection data to pinpoint the claims most likely to bounce back before they are submitted. The tool allows the organization to fix costly mistakes before submission, eliminating the time spent fighting the payer over a denial. The claims go in clean, so the denial never happens. The revenue cycle improves, saving staff time and stress. Denial Triage focuses on sorting denied claims by their likelihood to pay out. The software segments denied claims by their value so internal teams focus on remits with the most positive impact on the bottom line. Instead of chasing denials needlessly, this AI software allows revenue cycle teams to do more by working smarter. Revenue cycle technology to fill healthcare worker shortage gaps There is no question that the healthcare worker shortage is causing a significant burden on patients and providers. Experian Health's Short-staffed for the Long Term report illustrated the effect of this crisis on the healthcare revenue cycle, patient engagement, and worker satisfaction. Technology can solve staffing challenges by allowing the healthcare workers we do have to spread further and work more efficiently. AI and automation technology in healthcare can cut costs, alleviate staff burnout and can even help healthcare providers retain their existing workforce. By implementing these new solutions, healthcare providers can help stop the bleeding of existing staff that contributes to the healthcare worker shortage, while improving the efficiency of the revenue cycle. These tools save time and money and improve the lives of everyone touched by the healthcare industry. Contact Experian Health to see how your healthcare organization can use technology to help eliminate the pressures of the healthcare worker shortage.

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.

Today, U.S. healthcare providers struggle with three significant challenges affecting care delivery—each resulting from chronic healthcare workforce shortages. Ultimately, these challenges threaten the fiscal health of the country's most critical care safety nets. Over 80% of the healthcare C-suite say the chronic staffing shortage creates significant risk for their organizations. The effects of healthcare staffing shortages are severe - Experian Health's recent survey of revenue cycle leaders found these executives unanimously agreed that staffing shortages impact cash flow, patient engagement, and the work environment of their current staff. Experian Health’s new survey, Short Staffed for the Long-Term, polled 200 revenue cycle employees to determine the effects of healthcare staffing shortages on patients, the workforce, and their facilities. What did these teams say about the healthcare workforce shortage and the state of care delivery? Find out by downloading the full report. Healthcare providers experience a vicious cycle, and the effects of healthcare staffing shortages can be seen in many different areas. For example, it makes it harder for existing team members to register patients on the front end of the encounter. On the back end, revenue cycle staff face higher workloads and stress leading to preventable reimbursement claims errors and missed collections opportunities. Ultimately, that stress leads to staff turnover, exacerbating the healthcare workforce shortage. This article dives into three effects of healthcare staffing shortages and how providers can combat them. Result 1: Short-staffed providers struggle with reimbursement and cash flow. 70% of respondents who say staff shortages affect payer reimbursement also report escalating denial rates. 83% report it's harder to follow up on late payments or help patients struggling to pay their bills. Costs are up, and cash flow is down. Claims denials are increasing by 15% annually. Reimbursement rates continue to decline even as denials rise and patient debt increases. These are the revenue cycle challenges healthcare providers face on top of the chronic healthcare staffing shortage. Healthcare organizations must look for new ways to improve reimbursements while engaging patients and staff to benefit everyone involved. Experian Health's Short Staffed for the Long-Term report noted two of the most significant revenue channels for healthcare providers, claims reimbursement and collections, are experiencing significant challenges. Reimbursement denials tie up cash flow in an endless cat-and-mouse game of revenue collection. HealthLeaders termed 2023 as, “the year of reducing denials for revenue cycle.” Their statistics further reinforce Experian Health data correlating increasing denial rates with the healthcare staffing shortage. Simultaneously, healthcare providers find it harder to collect from patients. High self-pay costs lead to lower patient collection rates. One study showed patient collections declining from 76% in 2020 to 55% in 2021. Providers desperately need a more patient-centered collections process that helps these customers understand their cost obligations and payment options. Integrating automated collections solutions can also help providers do more with less. Healthcare stakeholders must collaborate to devise innovative solutions that prioritize workforce augmentation and streamline financial workflows. Technology can solve these problems by automating manual revenue cycle processes that lead to delayed reimbursements. New solutions that use artificial intelligence (AI) software can help in other areas (like claims denials) to save staff time and reduce workloads. Result 2: A lack of staff directly impacts successful patient engagement. Surveyed staff say 55% of patients experience engagement issues at scheduling and intake. 40% say patient estimates suffer, leading to potential miscommunications in credit and collections. Experian Health's The State of Patient Access, 2023: The Digital Front Door reported patients and providers believe healthcare access is worsening. 87% of providers in the survey blamed the effects of healthcare staffing shortages. Earlier data from ECRI shows patients wait longer for care, and nearly 50% of providers say access is worse. Over 100 academic studies in the past two decades confirm the correlation between poor patient health outcomes and industry staff shortages. Existing staff members may take on heavier workloads to cover gaps in patient care. The resulting fatigue can impact the quality of care delivery. When healthcare organizations are short-staffed, each team member may spend less time with patients, resulting in rushed assessments and potentially missed diagnoses. Staff shortages can impact every phase of the patient journey, beginning with patient scheduling and potentially delayed essential medical services. On the backend, patients suffer when the pressure staff members feel to work faster causes preventable errors leading to healthcare claim denials. Collections suffer, as frustrations mount, and healthcare staff waste time on patients who are simply unable to pay. The adverse effects of staffing shortages in healthcare weaken with technology to improve the patient experience at every stage of their encounter. Better technology lessens the burden of care for staff by automating mundane administrative tasks so every provider can focus on serving patients—not filling out forms. Improving patient engagement starts at the beginning of the healthcare encounter. For example, patient scheduling software can create a seamless online experience that halves appointment booking time. More than 70% of patients say they prefer the control these self-scheduling portals offer, putting access to care back in their hands. Patient payment estimation software creates much-needed healthcare price transparency, improving satisfaction by eliminating financial surprises after treatment. These solutions, combined with automated revenue cycle management software, can streamline healthcare processes and improve patient experiences. Result 3: Overwork is the norm as staff work environments decline and turnover increases. 37% of survey respondents report issues with staff burnout. 29% list the departure of experienced staff as one of their top challenges. Whether in frontend care delivery or backend revenue cycle, overworked and stressed healthcare professionals are more susceptible to making mistakes, diminishing the overall quality of the patient experience. The attention to detail, a critical component in a complex, high-stakes business, may be compromised due to the strain on the existing staff. When a healthcare organization is short-staffed, it increases the stress on the existing employees. In turn, this contributes to higher turnover rates. Job dissatisfaction and increased stress levels create a challenging work environment, perpetuating the cycle of staffing shortages. Recruiting and training new staff to fill these gaps further exacerbate the strain on existing teams. One area that is critically impacted by staffing shortages is seen in claims management, as claim denials continue to increase, which cost American healthcare providers an estimated 2.5% of their gross revenues annually. Billions of reimbursement dollars logjam in the endless cycle of claims submissions, rejections, and manual mitigations. In 2022, the cost of denials management increased by 67%. Revenue cycle staff, stretched to their limits by staffing shortages, will likely continue to make preventable mistakes during patient intake and claims submission. However, automating claims management with a solution like ClaimSource® can help lower denial rates and ease this burden.  This solution delivers increased operational efficiencies and effectiveness by prioritizing claims, payments and denials so that users can work the highest impact accounts first. Other solutions, like Claim Scrubber, can improve claim accuracy before submission, by submitting clean and accurate claims every time. These technologies enable healthcare providers to reduce claims denials while relieving some of the terrible pressure felt by their financial teams to work harder and faster. By automating clean claims submissions, healthcare organizations free up their teams to focus on taking better care of patients—and themselves. Healthcare staffing shortages + manual revenue cycle = Unsustainability What happens to a process that heavily relies on human labor—when there aren’t enough people to go around? In the case of the healthcare revenue cycle, it means staffing shortages heavily impact a hospital's ability to collect revenue. Medical Economics reports that 78% of providers still conduct patient collections with traditional paper statements or other manual processes. In an era of talent shortages, these manual processes bog down the entire organization with no relief in sight. Overwork leads to burnout, a significant problem in the industry that also contributes to staff turnover. But this is exactly how digital technology can solve the healthcare staffing shortage. While AI and automation can’t help providers find the staff they need, it can eliminate manual tasks and reduce errors that lead to more work, staff burnout, and patient care disruption. McKinsey says automation can eliminate approximately half of the activities employees now perform. It could considerably improve the work environments for revenue cycle staff, allowing them to focus on high-value tasks, and engage patients in more caring and personalized experiences. Experian Health offers providers proven technologies to increase revenue, improve patient care, and lessen the strain on existing staff, to combat the effects of healthcare staffing shortages. Contact Experian Health today to get started.

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.