Tag: artificial intelligence

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.

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.

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.

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.   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.'  

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.

Artificial intelligence (AI) is changing the healthcare industry. From disease detection to chatbots, AI is having a significant impact on the way healthcare providers operate and deliver care to patients. Additionally, AI is transforming the revenue cycle management process by automating tasks, such as claim denials management. By leveraging AI tools, healthcare providers can reduce the time and resources required for manual claims processing, ensuring that claims are paid faster and with greater accuracy. As claim denials continue to rise by 10-15%, healthcare organizations continue to grapple with the adverse effects on their finances. That's why Experian Health created AI Advantage™ – an innovative solution that helps providers with better claim denial management. The first component, AI Advantage – Predictive Denials, proactively identifies claims that are at high risk of being denied, so providers can edit the claim prior to submission. The second component, AI Advantage – Denial Triage, steps in after claims have been denied to identify those with the highest potential for reimbursement. Schneck Medical Center is one example of a healthcare organization that has seen significant results from implementing AI Advantage. After just six months, they successfully reduced denials by an average of 4.6% each month. Corrections that would previously have taken their organization 12 to 15 minutes to rework could now be processed in under 5 minutes. With AI Advantage, healthcare organizations can improve their claim denials management processes, increase efficiency, and reduce administrative costs. The solution's ability to prevent and reduce claim denials in real time can help healthcare providers maximize revenue while delivering high-quality patient care. As healthcare organizations continue to face mounting financial pressures and staffing shortages, AI-powered solutions will be increasingly important in helping them navigate these challenges and achieve long-term success. Learn more about how healthcare organizations can begin their journey towards improving efficiency and reducing claim denials with AI Advantage.