Tag: ai advantage denial triage

Technology has a long track record of improving patient care. But humans are now entering uncharted waters as the latest wave of digital tools impact healthcare clinical and administrative workflows. Technology advancements in artificial intelligence (AI) have spawned a fourth industrial revolution. According to the World Economic Forum, it's a time in history “that will fundamentally alter the way we live, work, and relate to one another. In its scale, scope, and complexity, the transformation will be unlike anything humankind has experienced before.” New developments in AI and automation in healthcare will offer numerous benefits to providers. The impact of recent technology advancements in healthcare is staggering. New AI and automation tools can detect human illnesses faster, monitor patients in the privacy of their homes, and streamline laborious administrative healthcare workflows to save providers up to $360 billion annually. The impact of AI and automation in healthcare is just beginning. Here are three ways these tools can help prevent and reduce claim denials, alleviate staff workloads and improve the patient experience. 1. AI and automation helps lessen claims errors Experian Health's State of Claims Survey 2022 reported that 61% of providers rely too heavily on manual processes and lack the automation necessary to streamline reimbursement. Billions of dollars are tied up in rejected claims; healthcare professionals say up to 15% of their claims are denied. However, many denials are preventable simply by eliminating human error stemming from manual workflows. When paperwork is still done by hand, mistakes in eligibility verification or incorrect insurance information are all too common. Some of the typical reasons for claims denials include data entry errors. Claims are complex, and providers handle most revenue cycle tasks manually, so it's common for incorrect insurance details, eligibility verification problems, or other inaccurate or missing information to make it through to claims submission. Far from being science fiction, the newest AI-powered administrative tools can scan patient claims data to detect errors that lead to denials. Given that diagnostic errors alone cost more than $100 billion and affect 12 million Americans annually, this new breed of AI tools offers providers a way to improve care delivery while lessening the endless hassle of claims denials. AI and automation tools can help eliminate up to errors that lead to denied claims. For example: Patient Access Curator automates insurance eligibility and coverage, scanning patient documentation for inaccurate information. The software uses AI and robotic process automation (RPA) to reduce manual errors. AI Advantage™ works to prevent denials before they happen: AI Advantage -Predictive Denials spots claim errors before submission to the payer. It's an early warning system designed to reduce denials by red flagging claims errors. But it also flags claims that fail to meet payer requirements—even if those requirements have recently changed. 2. AI and automation reduces manual processes and staff burnout Manual processes in healthcare contribute significantly to burnout, which affects nearly 50% of staff. The cost of staff burnout and preventable turnover runs around $4.6 billion annually. However, overworked staff leads to mistakes in manual processes and ultimately claim denials, so the cost of burnout directly affects the revenue cycle.Experian Health's 2023 staffing survey shows 100% of healthcare providers say staffing shortages have impacted their revenue cycle. But staff burnout and turnover affect more than reimbursement—more than 80% say it also negatively impacts the patient experience. AI and automation in healthcare can help alleviate the overwork that many staffers feel. Experian Health offers solutions to automate manual tasks, free up staff time, and reduce the volume of claims denials. ClaimSource® reduces the industry's average claims denial rate of 10% or higher to 4% or less. This software automatically scans claims, payer compliance, insurance eligibility, and patient demographics to spot the errors that lead to denials. Automating claims submission lessens the administrative burden and improves the work/life balance for overburdened staff. AI Advantage - Denial Triage covers any claims that end up rejected, prioritizing claims with the highest rate of ROI for providers. The solution uses artificial intelligence to help staff organize their efforts toward the highest revenue generating opportunities to increase revenue collection. It can lessen workloads and help teams work smarter for a higher return and better bottom line. 3. AI and automation in healthcare improves patient experiences Automation improves the patient journey. Experian Health and PYMNTS research show positive patient experience starts with self-service scheduling and registration. This kind of digital front door puts control back in the hands of patients, who are frustrated by time-consuming administrative processes. Patients have high expectations for better tech experiences throughout their healthcare encounters. Experian Health offers solutions that give customers exactly what they demand. For example: Patient Scheduling software allows 24/7 online access to appointment setting tools. In addition to making a more convenient and accessible scheduling process, this tool reduces the time it takes to set an appointment by 50%. The benefits for healthcare providers include a higher patient show rate (89% on average) and higher patient volumes (32% more patients per month). Patient Financial Advisor offers seamless, automated service estimates that go straight to the patient's favorite digital device. The tool creates a transparent payment process to help patients understand their treatment's cost and payment options. Patient Financial Advisor integrates with a secure online payment portal. These tools establish financial accountability up front while eliminating unnecessary surprises that affect the provider/patient relationship. Benefits of AI and automation in healthcare AI and automation in healthcare are changing how patients experience care delivery, how providers interact with their customers, and how clinicians manage getting paid. The benefits of using these tools include: Faster and more accurate patient diagnoses. Fewer patient readmissions and more proactive care management. Streamlined administrative tasks to reduce claims denials and improve the revenue cycle. Experian Health offers a suite of technology solutions, including a revenue cycle data curator package, to help providers get paid faster, free up staff time, and improve the patient experience. These solutions can help healthcare organizations achieve their goals by harnessing the latest AI and automation technologies to work smarter. Connect with an Experian Health expert today.

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.

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.

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.

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 media has extensively covered the healthcare workforce shortage and its impact on patient care. It's a chronic, dangerous problem that seems to worsen, despite the industry's efforts to staff up. A recent Experian Health survey found severe and long-term implications for revenue cycle management and its impact on provider and patient care. 100% of revenue cycle leaders surveyed agree the pervasive healthcare workforce shortage impacts their facility's ability to get paid. The problem isn't going away; most survey participants (69%) expect recruiting challenges to continue. Furthermore, nine of 10 survey participants admit to a double-digit turnover rate. However, the shortage of qualified labor is impacting healthcare in other areas beyond patient outcomes. The report shows the bottom line is clear: The healthcare workforce shortage impedes the industry's ability to get paid. How can providers solve this? Experian Health's survey, “Short Staffed for the Long-Term,” polled 200 revenue cycle executives to understand the impact of the hiring deficit's impact on provider cash flow. Survey Finding #1: Staffing shortages impede payer reimbursements and patient collections. 32% of survey participants said patient collections is the revenue cycle channel most impacted by healthcare workforce shortage. 22% said payer reimbursements are most affected by staff shortages. 43% said both channels were equally impactful to the healthcare revenue cycle. There was little disagreement in the survey around whether provider revenue cycle suffers from a lack of qualified staff. The debate centered on which reimbursement channel took the biggest hit. Experian Health's staffing survey revealed revenue cycle executives agree that collecting late patient payments is much more complicated now. The worker shortage impedes the ability to manage this process. In an era when many patients put off care due to high out-of-pocket costs, maximizing collections is more important than ever. Short-staffed, overworked healthcare collections teams require the time and tools to optimize the collections process by identifying the accounts more likely to pay. Patient collections teams could also benefit from software that finds financial assistance that could ease self-pay burdens. Collections Optimization Manager saves staff time by automatically determining the most suitable patient collections approach. The University of San Diego California Health (UCSDH) uses this software to segment patients by propensity to pay. It allows collections agents a more efficient, personalized approach to improve the revenue cycle and the patient relationship. From 2019 to 2021, UCSDH increased collections from $6 million to more than $21 million with this solution. Patient Financial Clearance automates screening prior to service or at the point of-service to determine if patients qualify for financial assistance, Medicaid, or other assistance programs. Kootenai Health leverages the software, which increased the accuracy of determining patient financial assistance by 88%, and saved 60 hours of staff time through automation. Together, these tools can ease the healthcare workforce shortage by optimizing and streamlining collections. Survey Finding #2: The healthcare workforce shortage contributes to increasing denial rates. 70% say escalating staff shortages increase claims denials. 92% report new staff member errors are a significant factor in delayed or declined reimbursement. Today, healthcare providers are seeing claim denials increase by 10 to 15% year over year. A lack of qualified revenue cycle staff costs billions annually in preventable revenue cycle errors. 35% of healthcare leaders admit losing more than $50 million yearly on denied claims. The complexities of the revenue cycle particularly challenge new staff; 92% of survey respondents say errors are common. Denied claims ripple across the revenue cycle, tying up staff time and provider cash flow. Ultimately, it is patients and staff who suffer. When hospitals experience restricted cash flow, it can hamper their ability to effectively deliver the highest quality care. When staff stretch to their limit due to the healthcare workforce shortage, they may make more errors, burnout, or quit. Automating the claims process is a necessity in this challenging environment. Tools like ClaimSource® and Claim Scrubber can catch errors before submission, reducing undercharges and denials. Franklin Healthcare Associates, a 100-provider, four-location practice, used Claim Scrubber to reduce accounts receivable (A/R) by 13%. As claims volume grew, the practice decreases its full-time employee (FTE) requirements by leveraging this automated tool. It's one clear example of how technology can stretch staff farther to improve the bottom line. Survey Finding #3 Staffing deficits aren't going away. Close to 70% of respondents believe revenue cycle staffing levels will continue as a problem into the future. Staff turnover is a contributing factor; 80% said their organization's turnover revenue of cycle management staff is between 11-40%. Experian Health's survey confirms that healthcare teams struggle to find qualified staff. Staff turnover is a significant contributor to a revolving hiring door. One survey showed the average hospital turnover rate is 100% every five years. Traditional solutions to the problem include throwing more money into salaries, bonuses, or other perks. Overtime is a go-to remedy for the chronic healthcare worker shortage. But these approaches strain the provider bottom line. A recent Kauffman Hall survey shows: 98% of healthcare providers have raised minimum wage or starting salaries. 84% offer signing bonuses, and 73% offer retention bonuses. 67% experienced wage increases of more than 10% for clinical staff. The American Hospital Association (AHA) states, “Hospitals also have incurred significant costs in recruiting and retaining staff, which have included overtime pay, bonus pay and other incentives.” But what if recruiting isn't the answer to the healthcare workforce shortage at all? Artificial intelligence (AI) and automation software can help cut costs and lessen the workload of existing staff. The latest data suggest providers could save close to $25 billion annually (one-half of what they spend on administrative tasks) if they leveraged these tools. Experian Health's  AI Advantage™ uses powerful algorithms to automate manual claims processes to reduce denial and lessen the volume of tasks for revenue cycle staff. The software works in two critical areas: Predictive Denials proactively cleans claims before they are submitted. The software flags claims at risk of denial, allowing manual intervention for a clean submission—with no denials. Denial Triage manages denied claims by identifying the highest value reimbursements to maximize cash flow. Instead of chasing low-value claims or those least likely to pay, the software prioritizes where revenue cycle staff should spend their time for the greatest return. Schneck Medical Center saw significant ROI from this software in just six months. AI Advantage helped the facility reduce denials by an average of 4.6% per month. Claims corrections that took up to 15 minutes in the past now take under five minutes. Better software can do more than help hospitals get paid faster. Automating revenue cycle management processes frees up staff time. More time and less pressure mean fewer mistakes. Automation can ease the impact of the healthcare workforce shortage Two of the most pressing problems hospitals face today are the healthcare workforce shortage and revenue cycle impediments that keep them from getting paid. These challenges interconnect, and providers can solve them both with better technology to automate time-wasting manual functions. AI and automation in healthcare can cut costs and reduce staff burnout. Deploying revenue cycle software to automate billing, claims management, and collections could save $200 billion to $360 billion in spending in this country. These numbers are real. But so are the numbers showing increasing claims denials, staff burnout, turnover, and difficulties recruiting in the healthcare field. Today, the answer for hospitals to get paid faster is to leverage modern technology to improve the revenue cycle. Learn more about how Experian Health's revenue cycle management solutions can help automate common processes, and download the new survey to see the latest healthcare staffing shortage stats.

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.

AI and automation could cut US healthcare spending by up to 10% – a promising figure for hospitals operating on razor-thin margins. Despite the potential for cost savings and revenue growth, investing in AI can seem risky while the technology feels relatively new. But as denial rates increase, staff shortages persist, and payers race ahead with their own AI-led efficiencies, investing in AI and automation could help healthcare providers increase efficiency and reduce manual workloads, while improving the patient experience. In a recent podcast interview, Johnathan Menard, VP of Analytics at Experian Health, talked to Andrew Brosnan of Omdia about how providers can use AI and automation in healthcare to reduce admin costs and tackle staff burnout, while maximizing the ROI on new technology. This article sums up the key takeaways. “AI and automation are gaining momentum in the healthcare revenue cycle, but there remains untapped potential” For healthcare leaders, maintaining the financial health of their organization is critical to serving their communities. Menard sees untapped potential to use AI to improve financial prospects by automating and eliminating administrative tasks within the revenue cycle: “There are many repetitive, tedious tasks involving large amounts of data that's already collected, and mostly structured and standardized. That can be organized and analyzed with AI to help improve efficiency and accuracy.” Automation is a well-established route to lowering manual workloads, increasing efficiencies and generating data for better decision-making. AI takes this a step further. For example, Experian Health's flagship AI platform, AI Advantage™, can parse an organization's data to identify and predict patterns in payer behavior. It translates this data into insights that help providers boost profitability and improve the staff and patient experience. Menard explains why claims management is a prime use case for AI: “Last year, the average denial rate was already above 11%. That's 1 in 10 patients potentially having to deal with uncertainty about who will pay the bill, when they should be focusing wellness. That's where we see Experian Health being able to lean in and drive value and change in the healthcare industry with AI.” “Cost is the biggest barrier to AI and automation adoption in healthcare – but can be offset with the right data” Despite the potential upside, healthcare still lags other industries when it comes to implementing AI. Menard says that workforce costs are the biggest barrier to adoption: “In healthcare, it's not just a matter of implementing the technology or solution, but also maintaining it on a yearly basis with talent. Organizations are going to have to recruit an AI-competent workforce.” He says that providers may struggle to offer competitive salaries to attract staff with this skillset, but there are other ways to offset cost concerns. One example is working with a trusted third-party vendor to choose the best-fit AI solution for their organization. These vendors can leverage economy of scale, data and lessons learned in other markets to help providers deliver new models of care: “At Experian Health, we have health data spanning eligibility and benefits, address, identity, claims remittance payments. We have insights on 300+ million consumers and 126 million households. We're able to offer providers one of the most holistic views of today's health care consumer. It gets really exciting when you think about partnering with providers to augment their capacity to deliver a different style of care.” “Providers need to make sure staff see the benefits of AI and automation” Menard notes that successful implementation of AI needs staff buy-in: “Providers need to make sure staff see the benefits of what this technology can bring. They must also make sure they give them the proper training on how to embrace these capabilities. They do not replace your job; they augment you to do more, or they allow you to focus on doing the right thing, not the right thing that needs their specific level of expertise.” AI Advantage is a prime example, reducing the admin burden for staff, who can then focus on higher priority tasks. The solution takes a two-pronged approach to help staff reduce claim denials and maximize reimbursement: AI Advantage – Predictive Denials synthesizes historical and real-time claims data and payer decisions to flag claims that are likely to be denied. This allows staff to intervene and make necessary amendments prior to submission. AI Advantage – Denial Triage performs a similar function for claims that do end up being denied. It helps staff eliminate time spent on low-value denials by guiding them resubmissions that are most likely to be reimbursed. Schneck Medical Center and Community Regional Medical Center (Fresno) are seeing the benefits of AI Advantage. Watch the on-demand webinar to hear about their results. Moving beyond proof of concept Menard acknowledges that providers need to feel confident in a tool's ability to deliver before they make an investment, especially if they are operating on single-digit margins: “You can't do that without the proof of concept. There are too many competing priorities, especially in the revenue cycle, and healthcare leaders need to be laser-focused and very confident in their decision-making.” In part, this is what Experian Health is looking to do with AI Advantage. By demonstrating the power of AI to reduce costs and alleviate staff pressures within claims management, it can act as a springboard for smarter automation across other revenue cycle operations. Menard believes that as AI adoption expands, it will become faster, easier and cheaper to develop solutions at scale: “That's why we built the AI Advantage platform – to launch other products in the future and solve other issues throughout the healthcare journey. We talked about automation, adoption and healthcare. To me, the best way to automate a process is to eliminate the need for it in the first place.” Find out more about how AI and automation in healthcare can reduce costs, prevent staff burnout and help providers prepare for future challenges.