Search Results for: artificial intelligence

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.

Staffing shortages are the new normal in healthcare. Most news headlines focus on gaps between the supply of providers and the growing demand for care. However, a recent survey by Experian Health, released in November 2023. shows the massive impact staffing shortages have on back office revenue cycle where these functions intersect with front-of-house patient engagement. Strikingly, the healthcare staffing shortage statistics in the survey show revenue cycle executives are 100% in agreement—staffing shortages significantly affect reimbursement workflows to the detriment of patients and healthcare employees. Experian Health's report, Short-staffed for the long term, surveyed 200 healthcare executives responsible for revenue cycle functions. The goal was to gauge the impact of worker shortages on revenue cycle management and patient engagement. While the pandemic brought these shortages into the public purview, this new data shows most providers believe healthcare staffing gaps are chronic and here to stay. These results reinforce The State of Patient Access 2023 survey, where 87% of providers blamed staffing shortages for declining access to care. As the healthcare industry continues to struggle with an ever-increasing staffing shortage, it has become increasingly evident that if left unresolved, this situation can wreak havoc on revenue cycle management (RCM). The latest survey illustrates the need for new strategies to alleviate healthcare worker shortfalls. This article explores the most recent healthcare staffing shortage statistics and some key findings from the study to help determine how healthcare providers can turn these challenges into opportunities. Experian Health surveyed 200 revenue cycle executives to determine the impact of staffing shortages on reimbursement and patient engagement. Download the report to get the full results. Finding 1: Most revenue cycle leaders believe staffing shortfalls negatively affect payer reimbursements and collections. 96% of survey respondents indicated a lack of qualified workers has a detrimental impact on organizational revenue channels. 80% say turnover in their department ranges from 11 to 40%, much higher than the national average of 3.8%. When healthcare organizations lack revenue cycle talent, they risk missing performance goals. High turnover and the departure of experienced staff create information deserts within healthcare organizations. It forces new team members to train faster, handle bigger caseloads before they're ready, and potentially burnout from stress. The pressure to do more faster creates a higher volume of preventable claims errors that lead to denials. The survey showed all these factors at play, and their negative impact on reimbursement, collections, and the patient experience. While the traditional way to alleviate staffing shortages is to increase recruiting and retention efforts, these approaches no longer work when there simply isn't enough available staff to hire and train. Healthcare organizations must consider new partnerships with technology providers who offer automation tools to streamline human workflows. Revenue cycle management software eliminates repetitive tasks and lessens errors that lead to rejected claims. Digital technology can help solve labor shortages by reducing staff workloads and improving operational performance. Automation can streamline collections by prioritizing the accounts most likely to pay. These tools help existing revenue cycle teams work more efficiently while enhancing patient encounters. Finding 2: Healthcare staffing shortages roadblock a positive patient experience. 8 of 10 survey respondents say patient experience suffers due to gaps in staffing coverage. 55% report the patient experience is most heavily affected at intake, and 50% say at appointment scheduling. Staffing shortages and turnover cause an undue burden on the healthcare workers left behind. The survey asked respondents to indicate the top pain points experienced by revenue cycle professionals, and one of the major challenges was staff burnout. Stress has a detrimental effect on patient interactions throughout the revenue cycle. The survey shows staffing shortages impede patient satisfaction in critical areas within revenue cycle functions, including: Scheduling appointments Patient registration Prior authorization Insurance coverage confirmation Patient estimates Revenue cycle interactions can be delicate, requiring extreme patience and clear communication. Healthcare organizations must provide the support their revenue cycle teams need to handle these crucial conversations appropriately. To improve the patient experience, organizations must first improve the workflows and workloads of these critical back-office teams. When healthcare organizations have the right tools to eliminate manual tasks that bog down revenue cycle staff, these professionals can spend more time on the compassionate handling of patients and their accounts. Providers have the opportunity to solve these challenges with digital patient engagement solutions that improve workflow efficiencies at every level of the revenue cycle. Patient scheduling software creates a self-service environment that 73% of healthcare customers prefer. Patient intake improves with online software that automates the tedious paperwork that tie up staff. Better technology can create price transparency without manual effort, ensuring patients understand their responsibilities up front instead of facing surprises during or after care delivery. Finally, a frictionless online payment platform allows patients to handle their obligations seamlessly without staff intervention. Finding 3: Errors arise when healthcare providers are short staffed, leading to claims denials. 70% of survey respondents say staff shortages exacerbate denial rates. 92% of survey respondents said new staff members make errors that negatively impact claims processing. Some of the most common reasons for healthcare claim denials include: Incomplete collection of claims data Coding errors Billing errors Eligibility verification errors Missed insurance verification Healthcare operations and revenue cycles are full of manual processes. RevCycleIntelligence reports one-third of prior authorizations are completed manually, and two-thirds of hospitals haven't automated any part of their denials management processes. Yet technology has made significant strides toward reducing these error-prone manual tasks. Leveraging artificial intelligence (AI), with solutions like AI Advantage™, within the complexities of claims processing could cut provider spending by up to 10% annually. Eliminating repetitive tasks with automated claims management solutions improves the lives of staff, cuts manual errors that tie up cash flow in reimbursement wrangling, and creates a better, less stressful environment for customers. Reducing the impact of healthcare staffing shortages with revenue cycle automation and technology Sometimes, 100% agreement isn't the desired outcome. In this case, the healthcare staffing shortage statistics found in the survey shows healthcare providers agree unanimously that chronic staffing shortages create a problematic environment for employees that costs revenue and patient engagement. While technology exists that can maximize revenue staff workflows to extend the reach of overburdened employees; survey participants suggest that healthcare organizations continue to approach solving these issues by adding staff.  But healthcare's staffing challenges are not new. While organizations have historically invested revenue in higher salaries and sign-on bonuses to attract staff, technology offers a new opportunity for history to avoid repeating itself. It's time for healthcare organizations to support their teams with automation. These tools alleviate mundane, error-prone tasks that tie up staff. Experian Health offers these organizations a way to improve the lives of everyone within the revenue cycle by allowing back and front-office teams to focus on patient care, rather than filling in forms. It's a more humane way to handle a very human staffing crisis. Download the survey or connect with an Experian Health expert today to learn how we can help your healthcare organization combat staffing shortages.

Artificial intelligence (AI) is cropping up everywhere. But it's about to make an even bigger splash by revolutionizing how providers handle HCM (healthcare claims management). In healthcare, the claims process is a real source of frustration. Thirty-five percent of healthcare providers say they lose more than $50 million annually in denied claims. That's a lot of money lost for healthcare providers after care is delivered to their patients. As industry costs rise, healthcare claims management becomes an unsustainable financial drain for providers, who have no choice but to push these costs back to the patients they're trying to serve. Using AI for claims management has numerous benefits - and with denied claims on the rise, healthcare providers will need to incorporate this technology or risk leaving millions on the table. AI Advantage™, Experian Health's innovative predictive analytics software, uses AI in claims processing to help providers expedite reimbursement and improve cash flow. This software takes the unsolvable Gordian Knot that is U.S. claims reimbursement and untangles it for faster reimbursement, better cash flow, and less wasted time. Understanding AI in Healthcare Claims Management The odds are stacked against providers before the patient ever visits their practice. One patient claim can go through 20 or more checkpoints before the payer approves reimbursement. Denied claims are much less likely to be paid, and 89% of hospitals say denial rates are rising. An Experian Health survey said the three most common reasons for medical claim denials include: Missing or incomplete prior authorizations Failure to verify provider eligibility Inaccurate medical coding Without question, healthcare claims denial management must include better training for staff to file claims without error. Providers need accurate patient data upfront, with standardized verification processes at each step in the process.However, healthcare providers can reduce or completely avoid many common reasons for medical claim denials by using AI in claims processing. AI claims management software provides “teachable moments” for staff by sharing claims management errors at the front-end of processing before submission and possible rejection by the payer. Tom Bonner, Principal Product Manager at Experian Health, says, “Healthcare providers everywhere ask themselves: How can we reduce claims denials? But we have the technology to go even further. By using AI in claims processing, providers can avoid claims denials altogether by proactively spotting and correcting the human errors that slow down reimbursement before the claim is submitted to the payer.” Top Benefit of Using AI in Claims Processing - Providers Avoid Claims Denials AI and automation are the one-two punch providers need to improve healthcare claims processing. Using AI healthcare claims management software helps organizations avoid claim denials far upstream — before it occurs. AI Advantage - Predictive Denials is a preventative tool that proactively stops bad claims before they turn into costly denials. This AI-driven healthcare claims management software works in two key ways: By proactively identifying undocumented payer adjudication rules potentially resulting in denials. By identifying claims with a high likelihood of denial based on an organization's historical payment data. Schneck Medical Center improved their claims management processing by using AI Advantage - Predictive Denials to first identify error-prone claims. When the automated system spots the probability of a denial, it triggers an alert that routes the claim to an investigative biller. The AI carefully scrubs the claim, checking coding errors, authorization status, insurance eligibility, and more. Once the agent resolves these errors, they can successfully submit the claim to the payer. Using AI in claims processing leads to improved accuracy and fewer rejections for better revenue cycle management. After leveraging these tools for six months, Schneck Medical Center reduced denials by 4.6% on average per month. Benefit #2 - Healthcare Claims Management Software Speeds Denials Mitigation But what if a claim makes it through to the payer and they deny it? Denial management is a tedious, time-consuming process that impedes cash flow. AI Advantage - Denial Triage uses advanced algorithms to segment denials based on their potential value, allowing billers to focus first on high-value claims to maximize the revenue cycle and quickly reduce the denials queue. AI in reimbursement processing increases the speed of healthcare claims management to help staff identify and target the claims that need attention as quickly as possible without wasting time on low-value denials. By using automation and AI, healthcare providers gain better insights into their claims and denial data, resulting in improved financial performance and greater efficiency. Benefit #3 - AI Software Automates Reimbursement for Faster Payment Experian Health offers a streamlined series of standardized, automated tools to help with claims management. From registration, quality assurance, and eligibility on the front-end to claims processing and denials management on the back-end, Experian Health has full lifecycle solutions to prevent and mitigate reimbursement denials. The Experian Health intelligent ecosystem is a comprehensive solution to the untenable healthcare claims denials management process. These tools include: ClaimSource: Voted Best in KLAS Claims Management Clearinghouse 2023, this healthcare claims management software gives providers reimbursement visibility in real-time from one intelligent hub. This software helps providers handle the entire reimbursement cycle. The tool allows end-users to create custom work queues to manage claims more efficiently. It also automates claims, allowing the software to clean submissions before they send. Flagging features let billers know exactly what's wrong with a claim, so staff can repair the error. Ensuring clean claims lessens denials and improves cash flow. Claim Scrubber spots claim errors within 3 seconds, flagging the claim with an explanation of why it needs reworking. Intelligent algorithms identify undercharging to maximize payer-allowed amounts. For medical billers and coders, this tool quickly spots the root causes of claims denial, faster and more accurately than doing it by hand. Enhanced Claim Status connects billers quickly to denied, pending, returned-to-provider, or zero-pay transactions well before the EOB or Electronic Remittance Advice forms process. Instead of waiting 30- or 45 days to review a denied claim, this software lets teams see the problems online in real time. It's an immediacy that's been missing from both front- and back-end claims management processes, allowing real teaching moments for revenue cycle teams. Denials Workflow Manager: Eliminates manual processes and allows providers to optimize the claims process. Providers no longer review claims manually, instead using computer automation to optimize follow-up activities. Claims management teams can quickly identify and target the claims needing attention quickly. Powerful features leverage root cause analysis to identify trends leading to claims denials. These platforms easily integrate with existing practice management and electronic health record software. They work well together or ala carte to increase the accuracy of claims documentation to eliminate denials. A successful strategy for reducing claims denials starts with AI and automation software. Healthcare organizations can reduce the time spent processing rejections and improve A/R by flagging at-risk claims. Ultimately, healthcare claims management software solves the complexities inherent in these processes. Higher patient satisfaction and greater provider revenues are possible. Talk to Experian Health today to see AI in claims processing at work.

Nearly three out of four healthcare leaders said reducing claims denials was their highest priority in  Experian Health's State of Claims Report. But knowing how to reduce claim denials is difficult. According to the survey, 62% of providers said they had insufficient access to data and analytics, and 61% lacked automation to meet the challenges of healthcare claims management. New and emerging artificial intelligence (AI) tools aim to help providers overcome these hurdles. Makenzie Smith, Product Manager at Experian Health, shares her thoughts on how providers can harness AI tools to predict, prevent, and prioritize claim denials for better results—and why preventing claim denials is so critical now. Q1: What is the challenge for revenue cycle teams, specifically when it comes to managing claims denials? “Revenue cycle teams that want to optimize claims processing have to respond to shifting payer behaviors, including major changes in the volume of denials,” says Smith. “Payers have been able to outpace providers in adopting new technologies, including AI. Payers are able process claims in a matter of seconds. For revenue cycle teams, that means receiving a large volume of denials all at once, which can be overwhelming.” At the same time, keeping up with policy changes is more than a full-time job. “You may have 20 different payers, each with multiple plans and policies that each have their own reimbursement or clinical guidelines,” says Smith. None of these policies are static: “They're constantly changing, which creates a huge challenge for providers.” Finally, maintaining enough staff to manage increased volume is an uphill battle. “The number of team members handling denials has not grown in a proportional way. Quite the opposite: They're being asked to do more with less. As providers continue to struggle with staffing imbalances, the challenge is not only having somebody to actually sit in these seats, but also managing the constant training and retraining that goes along with it.” Q2: Why is effective denial management so critical for providers' success?  “By one estimate, half of our country's hospitals are operating in the red,” says Smith. “Healthcare finance professionals are under incredible pressure to maintain or increase their operating margins. Meanwhile, Experian Health data shows that most organizations operate with an initial denial rate of 10% to 15%, and that rate is increasing year over year. “Effective denials prevention and management allow providers to get paid appropriately for services they've already provided,” Smith continues. “Optimizing revenue, improving cash flow, and maintaining expenses all stack up to provide meaningful financial resources providers can use on essential investments in staffing, physician recruitment and retention; capital equipment; and the expansion of services or service areas.” Providers that can't maintain healthy margins may be at risk for acquisition. “[Providers' viability is] put at risk daily because they must fight for every dollar from payers,” says Smith. Q3: How is Experian Health helping providers leverage AI tools and technology to start leveling up their denial management strategies? “Healthcare claims management technology solutions should be helping to bring providers up to speed,” Smith says. “Experian Health has released two products powered by a machine learning technical enablement layer to the market this year. Providers that use ClaimSource® to manage their claims can add AI Advantage™ tools to improve the way they manage claim denials. “AI Advantage - Predictive Denials uses AI and the provider's historical claim and remit data on the most probable reasons for medical claim denials to predict when claims will deny, in real-time, prior to claim submission. Billing teams can review denial predictions within their existing claim review workflows,” says Smith. “The design is incredible, allowing teams a seamless workflow integration with almost zero additional training.” “When denials do occur,” Smith continues, “AI Advantage - Denial Triage provides a predictive score based on the likelihood of recovery. Many denial follow-up teams prioritize working denials based on the highest charge amount. While that seems like a logical approach, there's a better way: segmenting by likelihood of recovery to drive priority and accelerate cash flow and recovery rates.” Q4: How is AI Advantage different from using human intelligence to predict and triage claim denials? “In some ways, it's quite similar,” Smith explains. “I was a director of billing for several years before I came to Experian Health. Often, one of the more senior billers would come to me and say, 'Hey, we're starting to see a trend with this payer, or with this denial reason code. We probably need to talk to our payer representative about this.' AI Advantage uses machine learning to identify these trends with greater speed and effectiveness, system-wide and in real-time. “Without this tool, one biller could see a denial happening twice and think nothing of it, while the biller sitting next to them is experiencing the same thing. This technology compiles all of this information together and identifies the holistic picture, so everyone benefits and trends don't go undetected.” Using AI in claims processing can make human teams more productive; it may help them feel empowered as well. Schneck Medical Center saw an average 4.6% monthly reduction in denials after six months of using AI Advantage. “Our people spend hours and hours on the phone with insurance companies fighting for dollars on claims we believe [are payable],” says Skylar Earley, Director of Patient Financial Services at Schneck. “Any leg up we can give our team members is a big, big deal.” Watch the webinar to hear from Eric Eckhart of Community Regional Medical (Fresno) and Skylar Earley of Schneck Medical Center as they discuss how their organizations use AI tools for claims management. Q5: What types of denials can providers expect to prevent, versus those that will continue to be denied? “Overall, the answer depends on a few things: an organization's healthcare claims denial management processes and ability to change on the one hand, and payer requirements on the other,” Smith says. “Too often, providers say they're just playing the game that payers put forward, simply so they can get paid what they are contractually owed.  As an industry, we cannot continue to accept this as the status quo. We'll find ourselves and our communities in a worse position to access healthcare.” Organizations that are willing to adopt new technology and be agile with their denial strategies can reduce their denial rates, even in a constantly changing environment. “I've seen the most success in denial prevention with eligibility, authorization, and technical billing categories,” says Smith. “But AI and machine learning are opening the door for new potential strategies that are more effective, more efficient, and more productive.” Q6: Clearly, claim denials affect providers, but patients also have a stake here. How do denied claims interfere with a positive patient experience? “There's definitely a patient impact,” says Smith. “Medical billing is already confusing, and a lot of people just don't understand their insurance to begin with. Add in potential denials and bills that seem to keep coming for months and months before getting resolved, and patients are bound to feel frustrated. Getting claims right on the first submission solves many of these issues up front. It reduces anxiety and makes for a much better patient experience overall.” Adding AI to the claims management toolkit Understanding how to avoid claim denials is a priority with good reason: Minimizing denials can improve revenue, lighten the burden on staff, and even help maintain a positive patient experience. Marginal changes make a difference: Smith notes that an increase in denied claims from 10% to 12% at an organization with $500 million in gross patient revenue represents a $2 million impact. Adding AI tools doesn't eliminate all the challenges of managing healthcare claims, but it does help equip providers for the current environment—and the future. Learn more about how AI Advantage can help providers prevent denials, improve the likelihood of reimbursements, and prioritize denied claims for reworking more efficiently and effectively.

Payers are using automation to adjudicate healthcare claims at scale, leaving providers struggling to keep up. One major insurer was found to have denied over 300,000 claims in two months, with each one taking an average of just 1.2 seconds. Providers that continue to rely on manual claims management methods will see their margins squeezed as the denials challenge grows. The future of healthcare claims management is here - and the answer lies in artificial intelligence (AI). Providers can level the playing field by turning to AI and automation , using tools like AI Advantage™ to streamline healthcare claims management. This article summarizes a recent webinar with two early adopters, Eric Eckhart of Community Regional Medical Center (Fresno) and Skylar Earley of Schneck Medical Center, who are using the technology to prevent denials and increase collections. Small increases in claim denials can lead to major revenue loss Makenzie Smith, Product Manager for AI Advantage at Experian Health, set the stage with observations on the current state of claims management. She notes that one of the biggest challenges when it comes to denials is constantly shifting payer behavior: “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.” Two hypothetical scenarios illustrate the potential impact of just a 2% increase in denials, assuming other variables remained constant: In an organization with a gross patient revenue (GPR) of $500m, an increase in denials from 10% to 12% could squeeze operational margins from 3% to 2.6%, resulting in a drop in net income from $15m to $13m. In an organization with a GPR of $2000m, an increase in denials from 18% to 20% could wipe out a 0.35% margin completely, causing net income to fall from $7m to 0. Some providers are choosing to stick with their existing processes; changing course seems too risky within thin margins. But as Eric Eckhart points out, “the just-work-harder approach doesn't work anymore.” Providers need a more efficient way to sustain operating margins. How AI Advantage helps reduce denial volume and improve net collections AI technology is emerging as a better alternative to the status quo. By using automation and AI, providers can gain insights into their claims and denial data, resulting in improved financial performance, greater efficiency and improve the future of healthcare claims management. AI Advantage™ – Predictive Denials uses AI to identify claims with a high likelihood of denial based on an organization's historical payment data. This allows staff to intervene prior to claim submission. It identifies undocumented payer adjudication rules that result in new denials. It works within Experian Health's ClaimSource® solution to proactively flag at-risk claims, allowing teams to review them within their existing claims workflow. Key takeaways from 2 real-world examples of AI in healthcare claims management Eckhart and Earley share how they are approaching denial prevention in today's fast-changing claims environment. Below are the key takeaways from their conversation about how AI is helping to optimize reimbursement and support their teams: Providers need to move beyond the “just work harder” approach to claims management Eckhart says that staffing challenges were a major driver of his organization's early adoption of AI Advantage, as it became harder to manage the increasing rate of denials with existing resources: “I think we've all tried the “let's work very hard approach” and worked overtime for months on end, but that's just not a long-term solution. We were looking for something technology-based to help us bring down denials and stay ahead of staff expenses. We're very happy with [AI Advantage] and the results we're seeing now.” Skylar Earley agrees, saying that despite their efforts, the rate of denials stayed the same. “It's so important for us to reduce denials because costs are increasing, reimbursements are decreasing, payments are shrinking. In our smaller community, there are only so many ways to grow revenue. We've got to maximize reimbursement, however we can.” Discover how Schneck Medical Center used AI to prevent claim denials. Read the case study Seamless integration with ClaimSource® was key to staff adoption While senior leadership teams may have been on board with testing the new technology, staff members were more hesitant about the potential pitfalls of introducing a new tool. Eckhart says, “Experian were already processing our claims through Claim Scrubber, so the workflow was essentially the same. I got some pushback when I said it was AI. I think the biggest fear for my billers was that they were going to get 5000 alerts that they would have to override and ignore. But we phased it in slowly and that was a good approach.” Earley agrees: “This is probably one of the most seamless products I've seen: it's entirely in ClaimSource®. If you didn't know about it, you wouldn't know it was there. The people using the product don't toggle back and forth between screens, they don't run reports to view alerts. The product shows them what claims they need to look at.” The predictive model gives staff their time back – so savings snowball For both organizations, a big win from AI Advantage was being able to reduce denials so staff could focus on other tasks. Making better use of staff time is increasingly urgent as the growth in denied claims outpaces recruitment. Eckhart says that over the last six months, his team have saved 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.” Reducing denials with accurate predictions Eckhart and Earley report that the success of the tool comes down to the accuracy of predictions, and the fact that it uses their own data. This applies to claims submitted to commercial and government payers, including prior authorizations. For example, Schneck Medical Center is seeing an ongoing reduction in AR days, while the number of authorized outpatient visits has increased by around 2.5% since implementing the technology. In addition to improving claims management processes, AI Advantage also helps root out persistent payer errors. Eckhart says that while denials teams tend to focus on high value claims, smaller payers can sometimes make erroneous denials that add up over time. The tool brings this to light so providers can raise it with the payer and fix it going forward. The future of healthcare claims management is here Ultimately, every prevented denial means more dollars coming back to the provider, increasing their capacity to deliver high quality services. Revenue growth makes it possible to recruit more staff, reduce outsourcing, increase capital purchases, introduce new service lines, and even explore merger and acquisition strategies. Payers are already making strides in their use of AI technology and automation, but with AI Advantage, providers can process accurate claims and reduce denials at a scale and pace to match. Find out more about how AI Advantage™ is changing the future of healthcare claims management and watch the webinar to hear the full conversation on 'The Future of Claims Management. Today.'

Compared to other industries, healthcare tends to be more resilient to economic turbulence. But the weight of the pandemic, labor shortages, rising costs and increasingly complex reimbursement structures are squeezing hospital margins. A Kaufman Hall National Hospital Flash Report in July 2023 found that many hospitals underperformed, and the gap between high-performing hospitals and those struggling continues to widen. Providers must find new and effective ways to improve revenue cycle management, should any new uncertainties emerge. With pressure mounting to increase efficiency and reduce expenses, more providers are turning to automation and artificial intelligence (AI) to eliminate unnecessary manual work and optimize revenue cycle management processes. For example, Stanford Health Care leveraged automation to reduce their cost to collect. Banner Health improved patient collections with transparent price estimates. Schneck Medical Center zeroed in on claims management and incorporated AI to reduce denials. In the face of a cashflow crunch, healthcare providers increasingly turn to data-driven revenue cycle management (RCM) strategies that span the entire patient journey. This article lists six of the most effective income-generating digital RCM strategies that providers are using to maximize profits. Building blocks of a healthy revenue cycle At its core, revenue cycle management is about ensuring providers are fully reimbursed for the care they provide. The true ROI is much broader – efficient financial and administrative processes for patient billing, claims management and collections contribute to better care, satisfied patients, high-performing staff and good financial health. Realizing these benefits calls for revenue cycle processes built on three principles: Efficiency – streamlining processes to reduce resource utilization across the entire billing cycle Accuracy – ensuring all patient and claims data is correct and complete to avoid denials and delays Transparency – giving patients, providers and payers relevant and timely information, so they can act with confidence in each financial transaction. To achieve this, providers are moving away from slow, costly manual systems. Digital RCM tools are becoming non-negotiable. 6 data-driven strategies for effective revenue cycle management 1. Increase efficiency in patient access Revenue cycle management starts when the patient books their appointment and ends when the final bills are settled. Claim denials and delayed payments often arise from data errors and miscommunications in the early stages of the patient journey, which means patient scheduling and registration processes are critical to streamline RCM. With automated, data-driven patient access tools, providers can simplify tasks across the patient journey, so patients can move from one stage to the next with as little friction as possible. Fewer errors mean delays and disappointment are more easily avoided. Automated registration and online self-scheduling can also lead to savings through more efficient use of staff time and reducing the number of appointment no-shows. Experian Health clients find that online tools allow them to make relatively minor adjustments to their workflows, with a major impact on productivity. 2. Deliver accurate and timely patient billing Patients want the payment process to be as painless as possible. In multiple surveys, Experian Health has found that patients are worried about the cost of care, while 63% of providers believe patients frequently postpone care because of cost concerns. Clear, comprehensive estimates, billing and collections practices can make it easier for patients to navigate their financial journey. And with the end of continuous Medicaid enrollment, it's likely that more patients will find themselves unsure of their coverage situation, and in need of greater support to manage the financial process. For Stanford Health, the key to improving revenue cycle management centered around patient billing and collections. To achieve the dual goals of improving the patient experience and increasing collections, they used data-driven insights and automation to remove uncollectible accounts, prioritize accounts with a high propensity to pay, find missing coverage and reduce the manual workload. Collections Optimization Manager helped Stanford Health identify the best possible collections strategy, by scoring and segmenting patient accounts with the highest propensity to pay. Coverage Discovery® supplemented this strategy by checking for any unidentified primary, secondary or tertiary coverages that can potentially reduce self-pay amounts and avoidable charity designations. As a result, Stanford Health achieved a $4.1m increase in average monthly payments and efficiency gains of $109k per month. 3. Provide transparent price estimates Experian Health's State of Patient Access 2023 report suggests that fewer than three in ten patients know how much their care will cost in advance, while nine in ten consider it important. Delivering accurate pre-care estimates to help patients plan for bills could therefore be an easy win to improve the patient experience and recoup more revenue. Banner Health used Patient Estimates as part of a wider strategy to improve patient collections. This solution generates detailed estimates of the patient's financial responsibility along with recommendations for payment plans and financial assistance, if appropriate. Listen in as Becky Peters, Executive Director of Patient Access at Banner Health, talks about streamlining the patient registration process and improving patient access with pre-care estimates. 4. Effective claims management Perhaps the biggest opportunity to improve revenue cycle performance lies in claims and denial management, which accounts for a major proportion of wasted healthcare dollars. Summit Medical Group Oregon–BMC paired Enhanced Claim Status with Claim Scrubber to submit cleaner claims the first time and avoid lost revenue. These tools help providers submit accurate claims and monitor claim status to prevent denials and resolve issues quickly. For Summit Medical Group, this led to a 92% primary clean claims rate, and a reduction in accounts receivable days and volume by 15%. Experian Health also offers a new solution that leverages machine learning and artificial intelligence for predictive reimbursement. AI Advantage™ uses AI to predict and prevent claim denials based on historical claims data. In the first six months, this solution helped Schneck achieve a 4.6% average monthly decrease in denials and decreased time spent on denials by 4x. 5. Easy ways to pay (plus clear pricing and payment policies) How easy is it for patients to pay? This simple but important question points to another vital element of effective revenue cycle management. A compassionate and convenient patient payment experience that matches consumer experience in other industries can encourage earlier payments. Easy digital options are especially important for millennial and younger patients: research by Experian Health and PYMNTS found that 60% of younger patients are looking for digital services. Experian Health's patient-friendly payment tools are designed to help patients navigate their financial responsibilities with confidence and ease. For example, PaymentSafe® allows providers to securely collect payments anytime, anywhere, including mobile payments and patient portals. 6. Operational efficiency with automation, data and analytics RCM processes generate vast amounts of data, providing valuable insights into the organization's operational performance, revenue trends and areas for improvement. Being able to parse and translate this data into actionable insights is essential to determine the right strategies to pursue to optimize financial performance. But this in itself can be a major lift. Revenue Cycle Analytics is a web-based tool that breaks down data into actionable insights across billing, reimbursement and payer performance, presenting KPI data via comprehensive dashboards. Effective revenue cycle management strategies from start to end From labor shortages to rising costs, healthcare providers are finding creative ways to manage cash flow. While each healthcare organization’s needs and goals are different, understanding these six key strategies of successful revenue cycle management can help hospitals manage their revenue cycles more effectively and efficiently, while responding to new uncertainties. Find out more about how Experian Health helps healthcare organizations leverage automation and AI to streamline processes and boost revenue cycle performance.

With the ability to be applied across many different areas – from disease prediction to claims management and administrative tasks – data and analytics in healthcare is booming. In fact, according to a Grand View Research report, the global market for data analytics was valued in 2022 at $35 billion and is expected to increase at a compound annual growth rate of 21.4% until 2027. So, why the rapid growth? How can healthcare data analytics be used across the healthcare revenue cycle? The role of data and analytics in healthcare Historically, there has been a large amount of healthcare data being generated, but the industry has struggled to properly leverage this data into useful insights that improve patient outcomes, operations, or revenue. Today, with increasingly advanced data analytics, healthcare providers are using real-time data-driven forecasts to stay nimble and pivot quickly in rapidly changing healthcare and economic environments. And there is more data collaboration between healthcare organizations to convert analytics-ready data into business-ready information, thanks to the ability to automate low-impact data management tasks. Data-derived intelligence is also now easier to share with colleagues, third parties and the public. Types of healthcare data analytics methodologies and tools Healthcare data analytics involves several different types of methodologies and tools – all of which can be applied to various aspects of revenue cycle management. For example, descriptive analytics allows organizations to review data from the past to gain insights about previous trends or benchmarks. Predictive analytics, on the other hand, uses modeling and forecasting to help predict future results. When a strategic course of action is needed based on certain data inputs, prescriptive analytics is used. If a provider wants to take a deep dive into raw data to uncover patterns, outliers, and interconnection, they may employ discovery analytics. There are also generally three categories of technology-driven tools that can help collect and convert raw data into usable insights during the revenue cycle, including: Solutions that gather data from a wide variety of sources, such as patient case files, machine-to-machine data transfers, and patient surveys Programs designed to scrub, validate, and analyze data in response to a specific question being researched Software created to leverage the results produced by the analysis into actionable suggestions that be applied to meet specific goals Applying data analytics to maximize revenue “There are many things driving near-constant change in the healthcare revenue cycle, including shifting reimbursement, evolving value-based payment models, growing regulatory pressures, and increasing provider risk and patient responsibility,” says John Menard, VP of Product, Analytics, at Experian Health. “Healthcare organizations are also adapting to value versus volume reimbursement models, requiring revenue cycle leaders to lean into leveraging data analytics to improve not just operational efficiency, but patient financial experience and quality outcomes as well." Here's a closer look at how data analytics can help with revenue cycle management: Assessing patient finances From registration to collections, data analytics can play a key role at every step of the patient journey – and revenue cycle. Not only can the right data analytics tools help healthcare organizations better assess a patient's individual financial circumstances, but they can also help providers create accurate estimates and payment plan recommendations. Data-driven technology can help providers reduce surprise billing through more transparent pricing, helping patients navigate the cost of care and providing more timely patient communication. Digital solutions can help improve the patient financial journey by: Providing a self-service patient portal – With a solution like PatientSimple, patients get convenient 24/7 access to self-service account management tools. They can use the online portal to log into their healthcare account to securely process payments, request or review payment estimates, and schedule appointments. The portal also provides patient access to pricing information, plus the ability to apply for financial assistance or set up payment plans. With easy-to-use patient online tools, patients are more likely to meet their self-pay responsibilities and providers get paid more quickly as a result. Offering payment solutions – To collect payments with confidence, healthcare providers can utilize comprehensive data collection and advanced analytics through a digital solution like Patient Financial Clearance. With this solution, providers use a patient's financial data to quickly assess a patient's propensity and likelihood to pay prior to treatment. When appropriate, providers can then offer empathetic financial counseling and connect those that potentially qualify to financial assistance programs. By applying data analytics to this payment solution, healthcare organizations can increase point-of-service collections while reducing bad debt—in real-time. Providing patients with more accurate estimates – A recent Experian Health study found that 4 in 10 patients said they spent more on healthcare than they could afford. However, when patients know the expected cost of their care up front, they feel more empowered and make better decisions. Patient Estimates lets providers create more accurate estimates, eliminate manual tasks and improve patient satisfaction. Plus, it allows providers to automate and standardize their price transparency practices, which can help healthcare organizations meet regulatory requirements, create a more positive patient experience and increase revenue at the point of service. Reduce denied claims According to Experian Health's 2022 State of Claims survey, denied claims are on the rise with 42% of providers reporting that denials increased in the past year. 47% of respondents also said improving clean claims rates was a top pain point. Digital solutions can help providers reduce denied claims and increase revenue by: Automating claims management – With a solution like ClaimSource®, providers can automate their claims management systems – helping to ensure claims are clean before they are submitted to a government or commercial payer. Using an automated solution also allows providers to streamline the claims management process from a single web application. With ClaimSource, providers can easily analyze claims, payer compliance and insurance eligibility. Plus, it allows staff to prioritize their workload and focus on high-impact accounts – resulting in claims denial rates of just 4% compared to the industry average of more than 10%+. Optimizing efficiencies through artificial intelligence – Incorporating artificial intelligence (AI) into an automated claims management solution enhances the claims process in two key moments: before claim submission and after claim denial. AI Advantage™ integrates seamlessly with ClaimSource to continuously learn and adapt to ever-changing payer rules. The solution features two AI offerings, AI Advantage – Predictive Denials and Denial Triage, which can be customized to prioritization thresholds. Verify insurance and patient information Missing patient healthcare data can be a headache for providers to hunt down but looking for active coverage is often necessary. Providers must contend with a range of factors impacting patient coverage – including forgotten coverage, inadequate coverage, patients being misclassified as self-pay and regulatory changes, particularly with Medicaid and Medicare coverage. Implementing digital solutions can help providers use data to verify and find missing patient health insurance coverage, optimize patient collections, and boost revenue by: Utilizing automated, real-time insurance verification – Verifying patient coverage prior to service using a digital solution, such as Experian Health's Insurance Eligibility Verification. This tool can help providers experience fewer payment delays and claim denials. Plus, verifying insurance with automated insurance eligibility and benefits data improves cash flow, reduces claims denials and speeds up payments, including Medicare reimbursements. Patients also feel empowered with accurate payment estimates and accelerated registration, leading to a better patient experience overall. Improving collections with better data – With Collections Optimization Manager, providers can screen out bankruptcies, deceased accounts, Medicaid and other charity eligibility ahead of time. Through targeted collection strategies, providers can leverage actionable insights to focus on high-value accounts. Plus, predictive algorithms and data-driven rules help providers route and distribute accounts to the right collectors and agencies, controlling overall collection costs. This solution also connects providers to live support from an experienced optimization consultant that will help develop a tailored collection strategy through data evaluation and industry knowledge. Finding unidentified coverage – In 2022, Coverage Discovery tracked down previously unknown billable coverage in 28.1% of self-pay accounts, finding more than $64.6 billion in corresponding charges. Providers can use Experian Health's Coverage Discovery solution at any point in the revenue cycle to look for previously unidentified coverage – maximizing insurance reimbursement revenue and reducing accounts sent to collections, charity, or bad debt. Coverage Discovery also automates self-pay scrubbing and proactively identifies billable Medicare, Medicaid, and private insurance options, using a mix of search, historical information, proprietary data sources and demographic validation. See how the right data and analytics can help providers better understand their patients, streamline operations, and improve revenue.

Many hospitals and health systems are rethinking their responses to the growing challenge of healthcare claims management. After all, claims are becoming increasingly more complex. Payer policy edits are changing at a scale not seen before. And the legacy of the pandemic continues to take a toll on administrative workflows. In Experian Health's State of Claims survey 2022, providers reiterated the urgent need to optimize claims management – and the mountains of wasted dollars that are the by-product of preventable denials. Could artificial intelligence (AI) and machine learning (ML) be the key? What does the future of healthcare claims and AI look like? The internet is buzzing with excitement about the AI revolution, but the adoption of AI technology in healthcare has been slow, compared to other industries. Providers may be unclear about implementing AI effectively or struggle to see a route around barriers to adoption. This includes concerns around legacy systems and data interoperability. That said, the uptake of AI in healthcare shot up by 167% between 2019 and 2021, as organizations spotted opportunities to leverage new technology to reduce denials, optimize processes and identify patterns. Now, the AI genie is out of the bottle. As the trend continues to grow, providers that fail to embrace these technological advances risk falling behind as their competitors race forward. This article looks at AI's role in the future of healthcare claims management, and specifically, how it can help providers streamline claims processing, recoup more revenue and gain a competitive edge. The growing challenge of healthcare claims management In Experian Health's State of Claims Survey 2022, providers said reducing denials was their number one priority. It's clear to see why. There have been more than 100,000 payer policy changes between March 2020 and March 2022. Staffing shortages continue to put pressure on both front-and back-office teams. Increasing patient volumes and changes to insurance coverage means more claims to process – with more complexity to boot. Looking ahead, providers need to find more efficient ways to manage and utilize increasing volumes of claims data to alleviate staffing pressure, improve productivity and future-proof against unexpected events. Failure to do so could be an expensive mistake, especially when margins are already tight and the economic landscape remains shaky. Digital claims management: from process-automation to pattern-spotting The survey suggests providers are increasingly turning to automation to improve claims management, with 78% saying they were likely to replace their current solution to achieve lower denial rates in the coming year. Upgrading claims technology, automating the tracking of payer policy edits, and automating patient portal claims reviews were the top three strategies for reducing denials. Automation can generate years of ROI by executing repetitive and error-prone administrative tasks at speed and at scale. A few examples of automation in action are tools like: ClaimSource®, which manages the entire claims cycle, creating custom work queues and automating the claims process for greater efficiency and accuracy. Claim Scrubber, which automatically reviews every line of every claim to check for errors, so claims are clean the first time, prior to submission.  Denials Workflow Manager uses automation to help providers eliminate manual processes, prevent errors and increase reimbursement. AI takes this a step further, by analyzing vast amounts of information to find patterns and make predictions that support better, faster decision-making. Clarissa Riggins, Chief Product Officer at Experian Health explains why providers should embrace AI in claims and denials management: "Claims submissions and managing claims after denial are highly manual processes – and they are both extremely error-prone. AI/ML can learn from the data patterns in your claims to provide insights on where your claims are being denied most frequently. These solutions can also provide decision support to staff to help them to prioritize the work within their current claims processes, to avoid unnecessary denials in the first place and then to optimize their work to ensure a cleaner claim rate." While many providers see the potential of AI to streamline claims operations, prevent denials and accelerate reimbursement, others are hesitant to invest or are stumped by logistical barriers. Legacy technology, data compatibility issues and staff skills gaps can all put the brakes on AI implementation. But the AI train is showing no signs of slowing, and providers that fail to jump aboard could get left behind. With the right tools and an experienced vendor, implementation can be simplified. AI Advantage™ – the engine for predictive denials and denials triage Experian Health's new AI-powered denials management solution uses a two-pronged approach to predict, prevent and prioritize denials. First, AI Advantage – Predictive Denials identifies claims that may be at risk of being denied, based on analysis of historical payment data and payer decisions. This gives staff time to intervene and make any necessary amendments before the claim is submitted. The second element, AI Advantage – Denial Triage, applies an algorithm to segment denials based on the likelihood of reimbursement. This means staff can focus on high-impact resubmissions, rather than simply prioritizing high-value claims that may or may not be paid. Rob Strucker, Product SVP at Experian Health, explains that AI Advantage™ is continuously learning in real-time, so that predictions are increasingly accurate: “We look at the provider's own information for this type of service for this payer, and how those claims have been adjudicated. From that, we can score each claim in terms of its probability of being denied or claimed, and then based on that probability score, trigger an appropriate alert.” How Schneck Medical Center optimized healthcare claims management with AI Advantage™ AI Advantage™ proved to be the solution Schneck Medical Center was looking for when they set out to reduce denials. Within six months, Experian Health's AI-powered solution enabled Schneck to reduce denials by an average of 4.6% each month. Staff reported that the probability thresholds calculated by AI Advantage™ were highly accurate, facilitating a more efficient approach to reworking claims. Processing time was cut from 12 to 15 minutes to less than 5 minutes per claim. Clarissa Riggins says that AI Advantage gives staff confidence that they're spending their time on the right tasks: "When you have an algorithm that can evaluate the probability that a denial will be overturned, you can make sure that staff are working on the claims with the most potential for yield. Taken together, these solutions can help ensure that hospitals and health systems are getting paid for the good work they do in delivering care." Thanks to the tool's predictive capabilities, staff now have the insights (uncovered from within their own data) to prevent denials before claims are submitted, and to speed up rework should any be denied. As claim denials continue to increase in number and complexity and healthcare costs continue to grow, providers are feeling the impact on their revenue and margins. AI can ease the pressure by optimizing the healthcare claims management process. Find out more about how AI Advantage™ can help providers improve healthcare claims management and prevent costly claim denials.

Could the era of manual claims processing be coming to an end? Experian Health's State of Claims 2022 survey revealed that more than half of healthcare providers have embraced advanced automation, freeing up staff from time-consuming and inefficient manual tasks. Automation has dominated as the key strategy used by providers to reduce denials in the previous 12 months. This evident optimism about technology's ability to address challenges in the claims process suggests that automation is here to stay. However, while automation has cracked open the doors to more efficient claims processing, the predictive power of artificial intelligence (AI) in claims processing can unlock exponentially higher rates of reimbursement. Providers may be increasingly aware of the benefits of automation, but many have yet to step into the world of AI. This article considers the advantages to be found in layering AI technology on top of automated claims processing and looks at how two new AI solutions are helping providers reduce denials and expedite payments.  How automation helps with claims processing Healthcare organizations with automated claims processing report improvements in speed, accuracy, financial performance and patient experience. For example: Automated claims management solution ClaimSource® helped Hattiesburg Clinic in Mississippi accelerate cash flow, reduce denials to 6.1%, and expedite claims from secondary and tertiary payers. Summit Medical Group Oregon used Enhanced Claim Status and Claim Scrubber to reduce accounts receivable days by 15% and achieve a first-time pass-through rate of 92%. These tools improve efficiency across the entire claims cycle by automating repetitive tasks, executing effective workflows and generating data-driven insights into root causes of denials so staff can prioritize high-impact tasks and errors are far less likely. Industry reports corroborate these positive results: CAQH reports that the medical industry could save as much as $22.3 billion per year through further automation. Unlocking the untapped potential of AI in claims processing Despite automation's impressive results, claim denials remain a thorn in the side of many revenue cycle leaders. This is where AI can help, thanks to its ability to predict and respond to payer behavior and claims data. But while 51% of survey respondents were using automation, only 11% had introduced AI-based technology to their claims process. For the AI-curious, combining automation and AI could be a good starting point to supercharge claims processing. AI technology can predict potential issues before they even occur by analyzing claims and denials and making suggested corrections or interventions in real-time. It can also assist in identifying fraudulent claims and denials, leading to improved 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. What does that look like in practice? More efficient and accurate claims predictions Automation can relieve staff of manual data handling activities, increasing the speed and accuracy of claim processing, from patient intake through scrubbing, submission and adjudication. AI enables staff to perform remaining tasks with greater confidence and accuracy. They no longer need to wonder, “which claim should I rework first?” – AI has the answer. Without AI, the logical approach would be to rework what appear to be the highest-value denials first. But in many cases, these aren't the ones most likely to result in reimbursement. AI can help staff prioritize by analyzing historical payment data and undocumented payer adjudication rules to flag denials that are most likely to be paid. This is exactly how AI Advantage™ – Predictive Denials works. Experian Health's new AI-based solution checks for any changes to the way payers handle denials and assesses these against previous payment behavior. Providers can set their own threshold for the probability of denial, and if the solution determines that a claim will exceed this threshold, it alerts staff so they can act quickly and decisively before the claim is submitted. Schneck Medical Center was an early adopter of this tool and used it to complement their existing claims workflow (built around ClaimSource®). Within six months, they saw average monthly denials drop by 4.6%. Predictive alerts allowed staff to focus efforts on submitting clean claims the first time, so both the number of denials and hours spent reworking them were drastically reduced. “Learning” from denials data to drive financial performance By definition, automated claims processing systems will repeat the same tasks over and over. This is great for operational efficiency but has limited capacity to handle variation. A major advantage of an AI-based solution is its capacity to “learn” and predict, so each claim can be individually assessed and directed to the most appropriate workflow. AI Advantage™ – Denial Triage uses advanced algorithms to identify and intelligently segment denials so that providers can prioritize accordingly. Just as Predictive Denials uses historical payment data to predict the claims that may be at risk of rejection, Denial Triage learns from payers' past decisions to predict the denials that are most likely to be reimbursed if reworked. Read more about Schneck Medical Center's experience with AI Advantage. How does using AI benefit healthcare staff? The use of AI in claims management can be met with different reactions: some staff are enthusiastic about the prospect of having manual tasks taken off their plate and being able to use their time more effectively. Others may be concerned about the impact of AI on jobs and recruitment. The reality is that many providers face ongoing staffing shortages, and therefore have little option but to augment their existing teams with new technology. Maintaining pre-pandemic headcounts in light of post-pandemic work patterns and budgets may not be possible. Automation and AI can resolve these short-term challenges while generating a positive ROI in the long term, as the volume and complexity of claim denials continue to grow. As noted in the State of Claims 2022 report, technology should no longer be viewed as a threat to jobs, but as a way of making life easier for staff. Automation and AI work hand in hand to execute tasks that many staff find time-consuming and laborious, leaving the more stimulating and high-value tasks for the human workforce. Improving operational performance can therefore have a positive effect on job satisfaction and retention. The integration of AI in claims processing is not about replacing human expertise, but about harnessing the power of AI-powered algorithms to enhance efficiency and minimize denials. The optimal approach lies in combining the strengths of automation, AI and staff. Automation handles repetitive processes, AI expedites decision-making, and human expertise brings contextual understanding and empathy to the process. Learn more about how Experian Health can help organizations utilize AI in healthcare claims processing with AI Advantage.