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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.

For many Americans, access to healthcare is increasingly a question of affordability. There's no room for error when it comes to determining a patient's medical bill. Helping patients understand and plan for medical bills starts with calculating patient responsibility quickly and accurately. Incorrect charges, unexpected costs and confusing payment processes create poor financial experiences for patients. According to research by Experian Health and PYMNTS, patients are increasingly worried about their healthcare costs. 46% of those surveyed had canceled care after receiving a high-cost estimate, while 60% of those with out-of-pocket expenses said inaccurate estimates or an unexpected bill would prompt them to consider switching providers. As the stakes get higher, providers must reexamine how to calculate patient responsibility in medical billing so all parties are clear about who will pay for what. Providing that clarity will improve the patient experience, streamline patient collections and protect the organization from bad debt. What is patient responsibility? Responsibility for paying medical bills is apportioned between the patient who receives care, their insurance provider (if they have one), and government payers like Medicare and Medicaid (if the patient is eligible). “Patient responsibility” refers to the portion of the bill that should be paid by the patient themselves. Getting these calculations right is critical to the provider's revenue cycle. Determining patient responsibility starts during patient registration. Here, providers have their first opportunity to check that insurance details are up to date and ensure that the patient has not overlooked any active coverage. If the patient does not have coverage, they'll be liable for the whole bill (or will have to find charity assistance). If they do have insurance, the provider will liaise with their payer to check that the proposed care is covered under the patient's plan and establish any prior authorization requirements. Then, the provider can estimate how much of the cost of care should be reimbursed by the payer, and how much will fall to the patient. The amount paid by patients includes the following categories: Co-payment – this is a fixed, flat fee the patient pays toward their medical care at the time of service. If providers do not have accurate co-pay information available at the time of the visit, they may need to bill or refund the difference later. Not all health plans include co-payments, and those that do often specify exceptions. Deductible – this the total amount the patient must pay toward medical care each year before the payer contributes. For example, if a patient has a $1000 deductible, they must pay the first $1000 of medical bills that year, and any eligible costs on top of that will be covered by their payer or shared between the patient and payer. High-deductible health plans are attractive to patients who don't think they're likely to need care, as these plans often come with lower monthly premiums. However, if the patient does need care, they'll be left footing a greater portion of the bill. Coinsurance – this is the patient's share of remaining medical costs after paying their deductible. Out-of-pocket maximum – some health plans set an annual limit to the amount a patient needs to pay toward care, including co-payments, deductibles and coinsurance. Once that limit is reached, the payer will cover the remaining eligible expenses for the remainder of the period. Clearly, this is a complicated formula. To bill correctly, providers need to know whether the proposed treatment is covered by the patient's plan, how much the payer has agreed to pay for specific services, and whether individual service providers involved in the patient's care are in-network or not. Claims will only be reimbursed if all necessary coding and payer policy requirements have been met. Revenue cycle management tools to calculate patient responsibility Traditionally, providers have relied on teams of hard-working coders and billers to manually compile and review each claim. But with so many moving parts – not to mention frequent payer policy changes and staffing shortages – manual processes are no longer viable. When determining how to calculate patient responsibility in medical billing, providers should turn to automation and digital tools. This can help them augment their staff's capacity to calculate patient responsibility more efficiently and accurately and optimize patient collections. Here are a few examples of how they might do that: Automate insurance eligibility verification - Without understanding exactly what the patient's active coverage includes, providers will remain one step behind in the medical billing and claims management process. Payers are already using automation and artificial intelligence to fulfil their side of the equation, and providers cannot risk being left behind. Automating the verification process allows providers to capture up-to-date eligibility and benefits data, including the patient's co-pay and deductible amounts, to calculate the patient's responsibility pre-services. Find missing and forgotten coverage - As more patients switch health plans, more payers join the Affordable Care Act marketplace, and employer-based insurance changes, it's increasingly likely that the patient may not be 100% sure of their active coverage. With Coverage Discovery, providers can run quick, automated and repeated checks to see if any active coverage has been overlooked. This could drastically reduce the patient's responsibility, leaving them with a more affordable bill. Automate prior authorization - Many health plans require specific services to be authorized by the payer before being administered. Providers must check these requirements pre-service, or face a denied claim which could affect the patient's bill. Obtaining authorization from health plans before administering services can be slow and expensive, and often delays care. The Council for Affordable Quality Healthcare (CAQH) states that automating prior authorizations could save the medical industry $449 million per year (or 11 minutes per transaction). Automated prior authorization software gives providers real-time insights into payer requirements, so they can speed up reimbursement and give patients clarity over what they'll owe. Why use a patient cost estimator? With the necessary insurance information at their digital fingertips, providers can then use a patient responsibility pricer to calculate the patient's co-pays, deductibles and other out-of-pocket expenses. For example, Patient Payment Estimates is a web-based price transparency tool that generates personalized estimates for patients before and at the point of service. Patients get a comprehensive breakdown of what they'll owe, so they can plan for upcoming bills or even pay upfront. Patient liability estimator tools give patients more financial clarity, saving staff time and encouraging prompter payments. They're also an important compliance tool, and are specifically recommended in CMS advice on compliance with the Hospital Price Transparency Final Rule. Accelerate and streamline patient collections Early financial clarity encourages patients to pay sooner. This means it's more likely that those bills are paid in full, instead of lingering on the aged receivables list. In addition to upfront estimates, providers should make the payment process itself as easy as possible. This might include directing patients to payment plans or charity assistance, and connecting patients to convenient payment tools at any point in their healthcare journey. Inevitably, there will be some patients who simply cannot pay their bills. Collections Optimization Manager shows staff which accounts, so they don't waste time chasing the wrong accounts. By scoring and segmenting patient accounts based on the likelihood of payment, and adjusting as the patient's situation changes, Collections Optimization Manager helps providers manage resources more efficiently, while supporting a more compassionate patient financial experience. It also enables more effective use of collections agencies to minimize the cost to collect, and incorporates reporting and benchmarking tools to identify improvement opportunities. Find out how Experian Health's revenue cycle management tools can help providers calculate patient responsibility in medical billing, for a more compassionate patient experience and streamlined collections process.

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 released 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 traced 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 keep 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.

Could common revenue cycle management (RCM) myths be preventing healthcare organizations from getting paid in full? Does what constituted best practice a few years back still apply to revenue cycle operations today? Many providers are embracing new technology to strengthen their RCM processes, using automations and software to create more accurate and efficient billing and claims management workflows. But if these processes are built on shaky assumptions, the results will be sub-optimal. As year-end financial reviews get under way, there is a prime opportunity to re-evaluate some long-standing beliefs about billing, collections and payments that, if not set straight, could limit financial performance in the year ahead. This article examines four of the most common revenue cycle myths and considers what providers can do to make financial growth a reality in 2024. Revenue Cycle Myth 1: All patients are equally likely to pay Reality: No two patients are alike – whether in their medical needs or financial circumstances. Providers know this, yet many rely on revenue cycle management solutions that lean toward a one-size-fits-all approach to patient payments. Instead, providers should consider RCM tools that use data and analytics to segment patients according to their individual financial situation, to create a more personalized and proactive approach to collections. This should take account of both the patient's ability to pay (i.e., whether they can afford their bills), and their likelihood to pay promptly, which may be enhanced by offering payment options that are convenient and aligned to their personal preferences. Collections Optimization Manager analyzes patients' individual payment history and demographic information so their accounts can be routed to the most appropriate collections pathway from the start. Patients that are likely to pay quickly can be sent billing information automatically and presented with self-service payment options. Alongside this, Patient Financial Clearance pulls together credit and non-credit data to help providers identify patients who may need a little more guidance and connect them to suitable payment plans. It catches any individuals who may be eligible for Medicaid or charity support. Staff get accurate, at-a-glance data to help them have sensitive financial conversations with patients, and can avoid losing time chasing collections from patients who would never have been able to pay. Case study: See how Stanford Health Care improved collections with a tailored, patient-focused approach to healthcare collections. Myth 2: It's hard to have meaningful pre-service financial conversations with patients Reality: Contrary to popular belief, most patients are receptive, and even eager, to have financial discussions with their provider as soon as possible. Doing so need not be challenging. In the past, providers may have worried that broaching the money question could deter patients from seeking necessary care, or simply not prioritized such discussions. Billing and insurance can also be highly complex, which may lead staff to assume that patients would find conversations about these issues to be confusing or overwhelming. But it is for these exact reasons that providers should have financial discussions with patients as early as possible. Experian Health's 2023 State of Patient Access survey found that almost 90% of patients wanted upfront pricing estimates so they could plan ahead for their financial obligations – yet less than a third received one. Tools like Patient Payment Estimates and Patient Financial Advisor can calculate cost estimates, taking account of the patient's claim history, deductibles and other insurance information, and automatically send these to patients before treatment so they know what to expect. These can also be combined with quick payment links so bills can be cleared before care. Giving patients consistent information through whichever digital channel they prefer means they will be better positioned to make informed decisions and discuss their situation with patient access staff if necessary. When patients are better informed and supported, they're also less likely to end up postponing care due to cost concerns. And with the same accurate data at their fingertips, patient access staff can serve as financial concierges, helping patients to understand coverage and copayments and check eligibility for relevant financial assistance programs. In addition to user-friendly data tools, providers should consider whether staff would benefit from additional training to bolster their confidence in leading compassionate financial conversations. Myth 3: It's impossible to know what patients owe across a system with a single look-up Reality: Thanks to data analytics and digital payment technology, it is now pretty straightforward to consolidate a patient's outstanding balance information from across an entire health system, and debunks common revenue cycle myths. Patient access staff can view a comprehensive summary of a patient's insurance status, estimated liability and open balances from multiple providers, enabling them to have meaningful financial conversations with patients. Even if these discussions do not lead to immediate payment, they can still act as a reminder to nudge the patient to act soon, thus accelerating the payment process. Selecting RCM tools from a single vendor makes it easier to integrate data from multiple workflows and generate a unified view of what a patient owes. When systems talk to each other, it's possible for a single tool to leverage the data and create a better experience for patients and staff. For example, PaymentSafe® automatically brings together data gathered throughout the revenue cycle to streamline what was previously a disjointed and time-consuming process. With point-to-point encryption, it accepts secure payments at any point in the patient's journey, using cash, check, card payments and recurring billing, through a single web-based application. Myth 4: Revenue cycle management is “set-and-forget” Reality: Revenue cycle managers may dream of setting up a system once and then forgetting about it, but the reality is that managing billing, claims and collections is an ongoing and evolving process that needs constant attention. Healthcare organizations must regularly review and adjust their RCM strategies to prevent missed revenue opportunities, manage compliance risks and promote operational efficiencies. That said, data analytics and automated revenue cycle management tools do make it far easier for providers to stay on top of RCM demands. These tools help providers with everything from monitoring payer policy changes and identifying billing errors to personalizing patient communications and generating monitoring reports. Artificial intelligence takes it a step further, for example, by preventing and predicting claim denials. In this way, these tools reduce the need for extensive staff input, so staff can spend more time focusing on the issues that need more human attention. With up-to-the-minute reports covering multiple RCM processes, staff also have the information they need to optimize performance and find opportunities to boost reimbursement that may have been previously overlooked. So, while RCM is not quite a “set-and-forget” process, automations and analytics can simplify it significantly, so it's less labor-intensive for staff and more efficient overall. Debunk revenue cycle myths and proactively challenge assumptions to increase profitability Debunking these revenue cycle myths is simple and achievable with tools that integrate a patient's clinical and financial data for a fuller picture of what that patient needs. This is crucial as changing consumer expectations, economic drivers, and new technology reshape how patients, providers and payers interact with one another. Checking underlying assumptions in any RCM process is essential to root out potential misunderstandings and outdated thinking. Not doing so leaves providers vulnerable to inaccurate financial projections, mismatched strategies and poor patient experiences. See how Experian Health's industry-leading Revenue Cycle Management Solutions make streamlined billing and collections a reality.

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.