Tag: ai advantage

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

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

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

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

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

As 2023 draws to a close, revenue cycle leaders are in planning mode, reviewing financial performance, and gearing up for resource allocation negotiations in the new year. What should they be prioritizing? Three of Experian Health's senior executives share their healthcare predictions for 2024 based on the latest healthcare trends, and the steps providers can take to maximize reimbursements in the year ahead. Healthcare prediction #1: “Staffing shortages will persist, driving demand for technology-based solutions over traditional HR tactics” According to Jason Considine, Chief Commercial Officer, the healthcare staffing shortage is unlikely to let up any time soon: “In our recent survey, we found that 100% of respondents are seeing ongoing shortages affect revenue cycle management and patient engagement. There's an urgent need to address the problem, but too many providers are relying on traditional recruitment approaches that won't give them the longer-term resilience they need. Heading into 2024, providers should leverage technology and data to alleviate the burdens on front and back-end operations, and drastically improve efficiencies. This will better protect providers from the talent pipeline fluctuations that cause major disruptions.” This healthcare prediction for 2024 is based on Experian Health's staffing survey that was relased in 2023. Participants in the survey agreed that the staffing crisis would continue, expressing concerns about its impact on revenue and patient engagement. For many, the culprit is high turnover rates. More than four in ten said turnover in their administrative teams exceeds 25%. Given the difficulties in finding skilled candidates and addressing staff burnout, it seems clear that traditional HR-based strategies will fall short. Despite this, salary increases, cross-training and incentives remain go-to responses. Responding to the survey findings, Considine says, “It's time to look at the many areas where automation – and even artificial intelligence – can stabilize, improve and optimize understaffed functions.” One use case for artificial intelligence is in claims management. Experian Health's AI Advantage™ solution uses historical and real-time claims data to identify claims that may be at risk of being denied. This allows staff to zero in on those claims and ensure all information is correct and complete before submission. It integrates seamlessly with ClaimSource® to augment the claims workflow, so staff can focus on claims and denials with the highest likelihood of payment. As well as alleviating pressure on staff, it reduces costs and maximizes reimbursements, helping providers to protect margins during uncertain times. See how AI Advantage helps healthcare organizations reduce and prevent claims denials. Prediction 2: “Patients' changing digital expectations will prompt more providers to adapt (and those that don't will risk losing market share)” Clarissa Riggins, Chief Product Officer, says that patients are increasingly likely to expect a better “digital front door” experience, and will start to look elsewhere care if they encounter too much friction: “Patients have increasingly high expectations for easy and efficient tech-enabled solutions when it comes to accessing healthcare services. They seek convenient self-scheduling options, accurate cost estimates, and the ability to pre-register through their smartphones. We're seeing a continuing trend in the number of patients who say they'd switch providers if the digital front door isn't open.” That healthcare trend was evident in Experian Health's State of Patient Access 2023 survey, which showed that 56% of patients who had seen a deterioration in the patient access experience would switch providers because of it. Demand for more digital options can be tracked back to the “Amazon effect” and the rise of online retail environments that give consumers convenience and choice at the tap of a button. Indeed, healthcare providers stepped up during the pandemic to deliver flexible, contactless care, so patients have seen that it's possible. With digital transactions now well-established, patients will find it surprising to be asked to fill out paper forms at the registration desk or have limited online payment options in 2024. Riggins says providers must update their technology or risk being left behind. “Clients who are making the switch to digital patient access offerings tell us they don't want to look stuck in the 90s. They want a more contemporary patient experience that's smoother and more efficient for both patients and staff.” To open the digital front door and kepe up with healthcare predictions in 2024, Riggins recommends prioritizing self-service and digital options for patient registration, scheduling and billing inquiries. Prediction #3: “More patients are struggling financially, so providers will need to do more – and sooner – to help them manage bills” Victoria Dames, Vice President of Product Management, says that with household finances under pressure, patients will remain anxious about the cost of care: “The earlier providers can give patients clarity, the better for all involved. Creating a convenient and transparent patient collections experience should begin during patient onboarding, so patients can start to plan. With integrated patient access software, providers can deliver a more compassionate and efficient collections process, which supports patients while accelerating the revenue cycle. They don't have to choose between prioritizing revenue and patient experience – patient access technology delivers on both.” Recent Experian data suggests that many Americans are not confident in their financial literacy. This does not bode well for their ability to navigate the increasingly complex processes involved in healthcare billing. The troubling health consequences are already evident: a 2023 Gallup poll revealed that record numbers of patients were putting off medical care because they were worried about the cost. Anything providers can do to simplify the payment process is going to improve access to care and minimize bad debt, as noted in Dames' healthcare predictions for 2024. Dames says the collections effort should be viewed as an ongoing interaction with patients, beginning in patient access: “Patient access is where providers begin collecting data, confirming insurance eligibility, and providing accurate patient estimates. Completing these actions successfully at the beginning of the patient journey, with compassionate and frictionless patient interactions, can facilitate payment and collections downstream.” A better financial experience in 2024 should include self-service and digital tools that guide patients through each step of their financial journey. For example, PatientSimple® gives patients a user-friendly, comprehensive way to generate price estimates, apply for charity care, set up payments plans and even make payments, all through a single web-based portal. Patient Payment Estimates deliver accurate pre-service cost estimates through the patient's preferred channels and point them toward any appropriate financial assistance. And of course, offering a wide range of convenient and flexible payment options will promote timely payments and maximize collections. Learn more about our revenue cycle management solutions or contact Experian Health today to discuss how we can support your strategies, based on our healthcare predictions for 2024.

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

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

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