Tag: patient access curator

Artificial intelligence (AI) and computer automation are finally beginning to impact healthcare. Payers are implementing generative AI to improve the customer experience. Researchers at Stanford use AI to review X-rays and detect pathologies in seconds. Today, AI and automation can remind patients about appointments and even provide a portion of their treatment via robotic surgery devices. While groundbreaking AI and automation technologies are in the news, adoption by the majority of healthcare providers has been slow despite research showing these tools could eliminate up to $360 billion in spending. It's a startling statistic that illustrates the reality of AI and automation applied to the revenue cycle: These tools quite literally can pay for themselves. The case for applying artificial intelligence and automation in healthcare Successful revenue cycles depend on thousands of daily tasks, which means efficiency lies at the heart of these endeavors. However, there are a lot of improvement to be made. Experian Health's State of Claims Survey 2022 shows the current state of the average healthcare revenue cycle: Reimbursement cycles are running longer. Claim errors are on the rise. Denials are increasing. More than one-half of U.S. hospitals reported financial losses in 2022. A 2023 America Hospital Report (AHA) report showed: 84% of hospitals admit the cost of complying with payer reimbursement requirements is increasing. 95% report spending more time on pursuing prior authorization approval. Over 50% of hospitals and health systems have more than $100 million tied up in A/R for claims six months old. These challenges stem from the increasing complexities of working with third-party payers, but also the by-hand human workflows embedded within provider revenue cycles. The State of Claims Survey 2022 showed that 61% of providers say they rely too heavily on manual processes and lack the automation they need to streamline reimbursement. As costs rise and revenue cycles tighten, there is increasing pressure to do more with less—faster. However, chronic healthcare staffing shortages have only exacerbated how hard it is for providers to get paid. Technology solves many of the problems plaguing healthcare's revenue cycle. AI and automation offer better revenue cycle management tools with fewer errors, less manual work, and more streamlined processes. How AI and automation improves revenue cycles Increasingly complicated reimbursement processes are the perfect testing ground for new technologies. These tools can improve the revenue cycle from the first point of patient contact to collections long after the procedure is over. For example, AI and automation software can greatly reduce errors and increase the accuracy of claims information before submission. When billing becomes more accurate, it lessens the volume of rejected claims, which take up an inordinate amount of staff resources and lengthen the time from service delivery to reimbursement. But AI and automation also impact the backend of the patient encounter by helping collections teams prioritize accounts most likely to pay. Four applications for AI and automation in the revenue cycle include: 1. Applying automation to patient registration The revenue cycle begins at patient registration, and that's also where providers can begin to apply technology to increase cash flow downstream. Patient registration is often cumbersome, an in-person process tied to a clipboard, paper, and open office hours. Yet Experian Health's State of Patient Access 2023 report shows that 73% of patients want to handle these processes online. Self-scheduling offers patients more flexibility for scheduling appointments when they want and on their preferred digital device. It can remove the friction from a frustratingly manual paperwork process while decreasing no-shows with automated messaging by text and email. Experian Health's automated patient scheduling software reduces time spent on traditionally manual scheduling tasks by 50%. Providers that select these tools increase their patient show rate to nearly 90%. From a revenue cycle perspective, providers that implement online self-service scheduling can see up to 32% more patients each month—which is money in the bank. 2. Finding hidden financial resources to reduce bad debt Experian Health's Coverage Discovery® automates the insurance verification process to match patients' responsibility with the best financial resources possible given their policy limits. Coverage Discovery scans proprietary databases and historical information for primary, secondary, and tertiary coverage. The platform seeks to find all available financial resources to lower the volume of accounts that end up as write-offs or in collections. In 2022, Coverage Discovery found $64.6 billion in patient coverage. In 2023, this software discovered previously unknown financial options for 32.1% of patient accounts, giving these customers more options for reducing debt. 3. Preventing denials by improving data quality Many claims are rejected by payers each day simply due to human error. Some of the most common reasons for claims errors include missing or inaccurate information caused by manual processes. From eligibility verification errors to incorrect insurance details, when paperwork is still by hand and this complex, it's far more likely to make an error than not. Experian Health's Patient Access Curator software automatically verifies eligibility and coverage while scanning patient documentation for obsolete or inaccurate data. The software leverages artificial intelligence and robotic process automation (RPA) to apply computer rigor to previously manual workflows to reduce manual errors. Significantly, this new technology performs these tasks in seconds, freeing up staff time and improving the patient experience. 4. Using artificial intelligence to prevent and mitigate denials How much does the endless pursuit of denials management tie up potential revenue? One survey showed half of hospitals report more than $100 million in delayed or unpaid claims at least six months old. The good news is that 85% of the errors that lead to denied claims are preventable with the help of existing technology. Experian Health's AI Advantage™ solution works in two critical areas to prevent denials before they happen—and correct any denied claims quickly: At the front end of the claim, by correcting errors before submission. AI Advantage - Predictive Denials spots the submissions most likely to kick back from the payer. This early warning system reduces the volume of denials by flagging claims with errors stemming from human mistakes or payer requirements changes. At the back end of the claim, for those rejected by the payer. AI Advantage - Denial Triage takes the volume of claims rejections and prioritizes them by those with the highest ROI for the provider organization. Not all denials offer the same volume or potential for revenue collection. This solution helps prioritize the highest returns quickly to increase revenue collection. Benefits of applying AI and automation to healthcare's revenue cycle There is little argument across the healthcare industry that the strategies that once worked to create a healthy revenue cycle still apply. Fortunately, today's AI and automation software allow these organizations to modernize their approach to these complexities—and win the revenue cycle game. The benefits of applying modern AI and automation tools at every point of the revenue cycle are substantial: Faster and more accurate patient scheduling and registration. No more manual data searches that tie up staff time. Fewer data entry tasks that lead to errors. Fewer claim denials. Less time spent chasing claims. Fewer days in A/R. More cash on hand. A high-performing revenue cycle is possible with the latest technology tools. Experian Health offers a suite of technology solutions that utilize artificial intelligence and automation designed to get providers paid faster, free up staff time, and improve the patient experience. Improving the revenue cycle is a necessity, and Experian Health helps healthcare organizations achieve this goal.

The relationship between hospitals and payers has often carried an undercurrent of tension. Stacks of paperwork, complex claims rules and manual adjustments are a recipe for disrupted cash flow and time-consuming rework. With profit margins hanging in the balance, providers need the reimbursement process to move forward without a hitch. To the relief of revenue cycle managers, recent developments in digital technology are paving the way for more effective claims management. Case in point: Experian Health's recent acquisition of Wave HDC, which brings together a suite of advanced patient registration solutions for faster and more accurate claims management at the front end of the process. Shifting sands in the hospital-payer relationship could increase denials For healthcare organizations, getting paid in full- and on-time hinges on seamless communications with payers. Any missteps can lead to revenue losses, with denied claims and delayed payments being the outcomes providers most want to avoid. Payers will automatically deny claims that have errors or missing information, while disputes and slow processing times can seriously hamper a hospital's cash flow. The sources of potential conflict have been pretty steady over time, stemming from complex billing processes, frequent changes to payers' requirements, and a lack of standardization between payers.  Tension created by the cost of services and the need to control healthcare costs is a constant in the revenue cycle. Recently, a major shift in dynamics has occurred with the widespread adoption of artificial intelligence by payers. This enables them to process – and deny – claims with unprecedented speed and scale, leaving providers struggling to catch up. On a recent webinar, Makenzie Smith, Experian Health Product Manager for AI AdvantageTM, explained how this change was reshaping the relationship between payers and providers: “So many payer decisions are now being driven by artificial intelligence. Insurers are reviewing and denying at scale using intelligent logic, leaving providers fighting harder for every dollar… Many revenue cycle managers will stick in their comfort zone because operating margins are tight and changing course seems risky. But given this change in payer behavior, the cost of staying the course could put organizations at risk.” How AI-powered revenue cycle management solutions help close the gap between payers and providers Providers are increasingly leveraging digital technology to level the playing field with payers. Integrated software and automation give revenue cycle management teams the right data in the right format and at the right time to respond to queries promptly and accurately. These solutions enable teams to work more efficiently, so they can process more claims in less time. Experian Health's flagship AI-based claims management solution, AI AdvantageTM, is a prime example. This tool predicts and prevents denials by identifying patterns in payer behavior and flagging claims with a high probability of denial so specialists can intervene before the claim is sent to the payer. This works alongside ClaimSource®, which automates clean claim submissions at scale. Using a single application, all claims are prepared and submitted with all necessary documentation, reducing the risk of denial due to missing or inaccurate information. Integrating Wave HDC's data capture technology for comprehensive claims management In November 2023, Experian Health acquired Wave HDC, which specializes in using AI-guided solutions to capture and process patient insurance data at registration with unrivalled speed and accuracy. This gives Experian Health clients access to a single denial management solution, known as Patient Access Curator. This new technology is a single click solution that spans eligibility verification, coordination of benefits, coverage and financial status checks with near-100% accuracy in less than 30 seconds. Crucial registration data can be captured in real time as soon as the patient checks in for an appointment, with no need to chase and update data post-registration. A single inquiry can search for all the essential insurance and patient demographics instantly, enabling better use of staff resources and smoother communications with payers. Tom Cox, President of Experian Health, says the move “allows us to quickly scale our portfolio with advanced logic and AI-powered technology to help solve one of the biggest administrative problems providers face today, which is claim denials.” Accurate patient data from the outset is key to preventing downstream denials, many of which originate in patient access. By reducing errors and enabling faster processing times, this comprehensive approach to denial management will help strengthen the relationship between providers and payers, ensuring timely payments and clean claims. Contact Experian Health today to find out how AI and automation can help build a successful relationship between providers and payers – and drive down denials.

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.