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.
As the saying goes, “what gets measured gets managed.” For healthcare providers, this is a reminder that optimizing the revenue cycle relies on monitoring and reporting on the right metrics. Claims, billing and collections teams will struggle to know which of their activities lead to improvements if they don't track key performance indicators (KPIs). The question, then, is how to choose the right KPIs. How can providers gain more visibility into their financial performance? Where are the pitfalls that limit the usefulness of the data? This article looks at how revenue cycle managers may find more opportunities to prevent revenue leakage by building a healthcare revenue cycle KPI dashboard populated with the right medical billing metrics. What is a revenue cycle KPI dashboard? A revenue cycle or medical billing KPI dashboard is part of a revenue cycle management (RCM) platform. It enables real-time visibility into metrics regarding billing and revenue and is customizable based on the KPIs that matter to each healthcare organization. It centralizes critical information related to patient access, healthcare collections, claims management and payer contract management. Challenges and pain points in revenue cycle management The first step in selecting the most relevant KPIs for a revenue cycle dashboard is to identify and understand the thorniest RCM challenges that could be causing dollars to slip through the net. Here is a run-down of some of the biggest obstacles to effective RCM and possible performance measures that may help track improvements: 1. Inefficient patient access for scheduling and registration Revenue cycle management begins in patient access. Unfortunately, so do many of the errors and inefficiencies that lead to claim denials and missed payment opportunities. Confusing and disjointed scheduling systems can lead to underutilization of services and no-shows, as well as falling short of consumer expectations for online booking methods.Online self-scheduling tools make it easier for patients to book appointments so they can start their healthcare journey quickly and conveniently. Cancelled appointment slots can be offered to other patients, to maximize clinician time. Here, it would be useful to track the percentage of unfilled appointments: an increase over time would suggest that patients are finding it easier to book appointments, and confirm better use of doctors' hours.Similarly, digital registration options can quell the frustrations that many patients feel when trying to fill out forms ahead of treatment. No-show rates, percentage of patients using online tools, registration error rates and patient satisfaction scores would all be relevant KPIs. 2. Claims and denial management processes that rely too heavily on manual work From checking payer updates to poring over billing codes, claims management workflows often involve manual tasks that put unwelcome pressure on already-overwhelmed staff. There are many opportunities for errors, which drive up denials and put the brakes on the organization's cash flow. An increase in clean claim rate and a reduction in the rate of denials would be KPIs to look for on the revenue cycle dashboard. An end-to-end claims management solution that uses automation and artificial intelligence (AI) to improve accuracy and lift the load on staff can alleviate these challenges. For example, AI Advantage™, leverages AI to predict and prevent denials using the organization's own historical claims data. 3. Patient collections practices are often inconsistent Patient responsibility for healthcare costs is higher than ever, so the consequences of poor billing practices are severe. Experian Health's State of Patient Access 2023 report found that 63% of providers believe patients frequently postpone care because they're worried about costs. If patients are unsure about what they owe, unable to find financial assistance, or unclear about how and when to pay, the provider is likely to see their accounts receivable metrics and collection rates heading in the wrong direction. Clear bills and convenient ways to pay are key to optimizing patient collections. Collections Optimization Manager supports better financial decision-making for both patients and providers by screening, segmenting and routing accounts based on payment probability. Users get tailored support from an experienced optimization consultant to select the right KPIs and turn insights into effective action. 4. Actionable insights are often out of reach RCM analysts may have a wealth of information to interrogate, but they are often tripped up by disparate systems and legacy processes. Critical information in patient access, collections, claims management and payer contract management may be held in different systems and formats, which makes it much harder to see connections. With revenue cycle analytics tools, providers can make sense of the information they hold, rather than drowning in data. A revenue cycle or medical billing dashboard can enable real-time visibility into the KPIs that matter most while tracking changes over time. What are KPIs for RCM? Revenue cycle KPIs are quantifiable measures that illustrate the financial viability of an organization's revenue cycle. These metrics indicate if healthcare organizations are achieving their financial goals and are effectively managing revenue inflows and outflows. Specific KPIs will be tailored to the organization's particular goals, challenges and processes. The quality and availability of relevant data will also play into the selection process, to maximize visibility and insights into the revenue cycle. In addition to the suggested metrics discussed above, other common KPIs to feature in a revenue cycle dashboard include: Days in account receivable Aged accounts receivable rate Adjusted collection rate Clean claim rate Claim denial rate Claim appeal rate Bad debt rate Gross collection rate Net collection rate Importance of healthcare revenue cycle KPI dashboards A revenue cycle KPI dashboard is more than just a handy way to present data. Monitoring an organization's financial health is critical to its ability to serve patients and attract and retain high-performing employees. A healthcare revenue cycle dashboard can enable providers to: Identify if revenue levels are sufficient to keep the organization afloat and know in advance if new strategies are needed to maintain cash flow Locate glaring operational efficiencies in RCM that are costing the organization time and money Forecast future revenue projections to determine the organization's ability to expand and invest Improve all financial decision-making through better use of data that is already being collected Boost patient satisfaction by highlighting opportunities to create a more convenient and transparent financial experience. Driving efficiency and success through RCM solutions Once the revenue cycle KPI dashboard is built, RCM teams can get to work on implementing the specific actions needed to tackle those thorny issues discussed above. With Experian Health's integrated RCM solutions, providers can bring together metrics such as financial performance, billing efficiency and collections rates into one place, to allocate resources more strategically, drive targeted improvements, and accelerate reimbursement. And with these insights, providers are not just managing revenue – they are optimizing for future financial stability. See how Experian Health's revenue cycle management solutions, dashboards and drill-down reports can uncover opportunities to prevent revenue loss and boost profitability.
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.
Experian Health ranked #1 in Best In KLAS for our ClaimSource® claims management system and Contract Manager and Analysis product – for the second consecutive year. The rankings were revealed in the annual 2024 Best in KLAS Awards – Software and Services, published on February 7, 2024. The Awards recognize the top software and services vendors that are helping American healthcare professionals deliver the best possible patient care, based on feedback from thousands of providers. Experian Health topped the list in two categories: ClaimSource ranked #1 in Claims Management and Clearinghouse. This automated and scalable solution reduces denials and increases revenue through a single application. The addition of an artificial intelligence component this year (AI AdvantageTM) is helping providers cut denial rates to just 4%, compared to an industry average of more than 10%. Contract Manager and Analysis ranked #1 in Revenue Cycle: Contract Management. This product levels the playing field with payers by monitoring compliance with contract terms and recovering underpayments. It also arms providers with financial models of proposed contracts, so they can negotiate more favorable terms. Case study: See how Hattiesburg Clinic in Mississippi uses ClaimSource to automate claims management and reduce denials. The awards come as the industry grapples with ongoing staffing challenges and rising claim denials. In Experian Health's 2023 report on the healthcare staffing crisis, 100% of respondents saw staffing shortages affect revenue cycle management and patient engagement. As the pressure continues, revenue cycle technology offers a way to increase efficiency and improve financial performance. “Healthcare professionals face immense pressures, ranging from financial strains to staffing shortages and the very real issue of clinician burnout,” says Adam Gale, CEO and Founder of KLAS Research. “We want to provide actionable insights that will ultimately alleviate burdens and enhance clinician success.” For Tom Cox, President of Experian Health, the awards reflect a continuing commitment to help providers optimize operations and patient engagement using data-driven insights and technology. “This recognition from KLAS recognizes our dedication to deliver innovative solutions that not only improve the financial health of providers but also the patient experience. Receiving this award two years in a row is an honor as we remain steadfast in our commitment to simplifying healthcare through technology.” Find out more about how ClaimSource and Contract Manager and Contract Analysis helps healthcare organizations increase efficiency and boost financial performance.
By all forecasts, the healthcare worker shortage isn't going away. More than 80% of healthcare executives admit talent acquisition is so challenging it puts their organizations at risk. The latest survey from Experian Health shows complete agreement across the industry—the inability to recruit and retain staff hampers timely reimbursements. The side effects of the healthcare worker shortage are increased errors, staff turnover, and lower patient satisfaction. With the healthcare worker shortage becoming a chronic red flag on the list of industry challenges, is throwing more revenue at hiring the best answer? Experian Health's new report, Short-staffed for the long term, polled 200 healthcare revenue cycle executives to find out the effects of the continuing healthcare worker shortage on the bottom line. Respondents unanimous agreed that healthcare's recruitment problem is limiting their ability to get paid. Could investing in better revenue cycle technology to automate manual human functions be the answer to the healthcare recruiting dilemma? Effect of the healthcare worker shortage on healthcare revenue cycle Result 1: Providers losing money and patient engagement simultaneously. 96% of respondents said the healthcare worker shortage negatively impacts revenue. 82% of survey participants said patient engagement suffers when providers are short-staffed. Experian Health's latest survey showed almost unanimous agreement that the revenue cycle suffers significantly when providers are short-staffed. The only area of disagreement among revenue cycle leaders is whether patient collections or payer reimbursements are affected the most by the industry's lack of human talent. As revenue cycle teams struggle to cover their workload, the need for speed increases manual error rates. The Experian Health survey showed that 70% of revenue cycle teams say healthcare worker shortages increase denial rates. This finding reinforces an earlier survey showing nearly three of four healthcare executives place reducing claims denials as their top priority. As errors snowball, patient engagement and satisfaction begin to decline. Data entry errors impact claims submissions, resulting in billing mistakes that confuse and frustrate patients. Data errors often start at patient registration and persist through claims submission, creating denial reimbursement snarls and tying up cash flow. With the average denial rate above 11%, that's one in every 10 patients facing uncertainty around whether their bill will be paid. What's worse is that Experian Health's State of Claims Report shows denial rates increasing. While providers are leaning into increasing recruiting efforts to find the employees they need, is staffing up even possible in an era of chronic labor shortages? Technology offers healthcare providers new ways to handle revenue cycles without hiring more staff. For example, patient access software reduces registration friction, where up to 60% of denied claims start. Patient scheduling software automates access to care and gives customers greater control over their healthcare journey. It's a digital front door that engages patients with online options for managing care. On the backend of the revenue cycle, automation also offers a way to decrease reliance on manual labor to handle claims submissions. Automating clean claims submissions alleviates the denials burden, freeing up staff time and provider revenue streams. Result 2: Staffing shortages heavily impact payer reimbursement and patient collections. 70% of those saying payer reimbursement has been affected the most by staff shortages also agree that escalating denial rates are a result. 83% of those saying patient collections have been affected most by staff shortages also agree that it’s now harder to follow up on late payments or help patients struggling to pay. Addressing healthcare staffing shortages is crucial for providing quality patient care, maintaining financial stability, and maximizing reimbursement in the complex healthcare reimbursement landscape. Staff shortages lead to reduced productivity within healthcare facilities, and existing teams may need to take on extra work to fill the gap. Overworked staff may be more prone to errors, leading to claims denials. Medical Economics says manual collections processes suffer due to the healthcare worker shortage. They state, “Mailed paper statements and staff-dependent processes are significantly more costly than electronic and paperless options, yet the majority of physicians still primarily collect from patients with paper and manual processes.” Technology exists for self-pay receivables that allow patients easy online payment options. Experian Health's Collections Optimization Manager offers powerful analytics to segment and prioritize accounts by their propensity to pay and create the best engagementstrategy for each patient segment. Advocate Aurora Healthcare took control of collections by using this tool and automated their collections processes, so that existing staff could focus on working with the patients who had the resources to handle their self-pay commitments. The software's automation and analytics features allowed the provider to experience a double-digit increase in collected revenues annually. Patients also benefit from collections optimization software. For example, Kootenai Health qualifies more patients for charity or other financial assistance with Experian Health's Patient Financial Clearance solution. In addition to automating up to 80% of pre-registration workflows, the software uses data-driven insights to carve out the best financial pathway for each patient. It's a valuable tool for overburdened revenue cycle teams that struggle to collect from patients. Kootenai Health saved 60 hours of staff time by automating these manual payment verification processes. Result 3: Recruiting alone isn't solving the healthcare worker shortage. Healthcare hiring is a revolving door, with 80% reporting turnover as high as 40%. 73% said finding qualified staff is a significant issue. A significant contributor to the healthcare worker shortage is the grim reality that these organizations are losing human resources to burnout and stress. Being short-staffed drags down the entire organization, from the employed teams to the patients they serve. But it's impossible for recruiting alone to fix the problem when more than 200,000 providers and staff leave healthcare each year. A recent study suggests that if experienced workers continue to leave the industry, by 2026, more than 6.5 million healthcare professionals will exit their positions. Only 1.9 million new employees will step in to replace them. The news worsens with the realization that nearly 45% of doctors are older than 55 and nearing retirement age. Artificial intelligence (AI) and automation technology in healthcare can cut costs and alleviate some of the severe staff burnout leading to all this turnover. However, one-third of healthcare providers have never used automation in the revenue cycle. A recent report states that providers could save one-half of what they spend on administrative tasks—or close to $25 billion annually—if they leveraged these tools. For example, Experian Health's Patient Access solutions can automate registration, scheduling and other front-end processes. AI can also help increase staff capacity and output without adding work volume. Experian Health's AI Advantage™ solution works in two critical ways to help stretch staff and improve their efficiency: The Predictive Denials module reviews the provider's historical rejection data to pinpoint the claims most likely to bounce back before they are submitted. The tool allows the organization to fix costly mistakes before submission, eliminating the time spent fighting the payer over a denial. The claims go in clean, so the denial never happens. The revenue cycle improves, saving staff time and stress. Denial Triage focuses on sorting denied claims by their likelihood to pay out. The software segments denied claims by their value so internal teams focus on remits with the most positive impact on the bottom line. Instead of chasing denials needlessly, this AI software allows revenue cycle teams to do more by working smarter. Revenue cycle technology to fill healthcare worker shortage gaps There is no question that the healthcare worker shortage is causing a significant burden on patients and providers. Experian Health's Short-staffed for the Long Term report illustrated the effect of this crisis on the healthcare revenue cycle, patient engagement, and worker satisfaction. Technology can solve staffing challenges by allowing the healthcare workers we do have to spread further and work more efficiently. AI and automation technology in healthcare can cut costs, alleviate staff burnout and can even help healthcare providers retain their existing workforce. By implementing these new solutions, healthcare providers can help stop the bleeding of existing staff that contributes to the healthcare worker shortage, while improving the efficiency of the revenue cycle. These tools save time and money and improve the lives of everyone touched by the healthcare industry. Contact Experian Health to see how your healthcare organization can use technology to help eliminate the pressures of the healthcare worker shortage.
Prospects for US hospitals that closed out 2022 at a financial loss looked brighter by the end of 2023, prompting cautious optimism heading into 2024. An industry analysis published in October 2023 found that most hospitals were back in the black from March 2023 onward, while the economy more generally ended the year with a strong finish. That said, healthcare margins remain slim, and expenses continue to grow. Finding efficiency savings across all operations remains a top priority. That's where revenue cycle automation comes in. With revenue cycle automation, providers can eliminate many of the persistent pain points in traditional revenue cycle management (RCM). Staff no longer lose time to tedious manual tasks, patients get their queries answered faster, and managers get the meaningful data they need to drive improvements. And the biggest win? It's easier for providers to get reimbursed for the services they provide – faster and in full. What is revenue cycle automation and how does it work? Healthcare revenue cycle management knits together the financial and clinical components of care to ensure providers are properly reimbursed. As staff and patients know all too well, this can be a complex and time-consuming process, involving repetitive tasks and lengthy forms to ensure the right parties get the right information at the right time. This requires data pulled from multiple databases and systems for accurate claims and billing, and is a perfect use case for automation. Revenue cycle automation refers to the application of robotic process automation (RPA) to these repetitive, rules-based processes. In practice, this might include: Automatically generating and issuing invoices, bills and financial statements Streamlining patient data management and exchanging information quickly and reliably Processing digital payments Collating and analyzing performance data to draw out useful insights. Common RCM challenges Automation is already making headway in tackling some of the most pervasive challenges, such as: Stemming the rise in claim denials: Experian Health's State of Claims 2022 survey found that a third of providers had around 10-15% of their claims denied. These often result from errors made earlier in the revenue cycle such as incorrect patient information or overlooked pre-authorizations. RCM automation reduces the propensity for errors significantly. Streamlining patient access: Without a welcoming digital front door, the revenue cycle gets off on the wrong foot. Automation can be deployed in patient scheduling and registration to ensure patient information is collected and stored quickly and accurately. Improving collections rates: Self-pay patients (who are increasing in number) want clear, upfront information about what their care is likely to cost. Providers can find themselves playing catch-up if patients are unsure about what they owe. Automated tools that generate accurate estimates and support pre-service payment can build a more resilient cash flow. Expanding access to data insights: One of the biggest ironies in revenue cycle management is that more data is collected than ever, but managers are struggling to digest it and uncover actionable insights. RCM automation helps identify patterns in claims and collections. Six ways revenue cycle automation accelerates reimbursements Let's break down these opportunities into six specific actions providers can take to improve their organization's financial health: 1. Capture accurate information quickly during patient access Victoria Dames, Vice President of Product Management at Experian Health, says, “Patient access is the first step in simplifying healthcare and revenue cycle processes. Replacing manual processes and disjointed systems with integrated software solutions can reduce errors, improve efficiency, offer convenience and transparency to patients, and accelerate the healthcare revenue cycle.” Patient Estimates automatically compiles an accurate breakdown of what a patient is likely to owe before or at the point of service. It builds in prompt-pay discounts, financial assistance advice and instant payment links, so patients are more likely to pay sooner. 2. Simplify collections and focus on the right accounts Healthcare collections are a drag on resources. Automating the repetitive elements in the collections process helps reduce the burden on staff. Collections Optimization Manager leverages automation to analyze patients' payment histories and other financial information to route their accounts to the right collections pathway. Scoring and segmenting accounts means no time is wasted chasing the wrong accounts. Patients that can pay promptly are able do so without unnecessary friction. As a result, providers get paid faster. 3. Reduce manual work and staff burnout Chronic staffing shortages continue to plague healthcare providers. In Experian Health's recent staffing survey, 96% of respondents said this was affecting payer reimbursements and patient collections. While automation cannot replace much-needed expert staff, it can ease pressure on busy teams by relieving them of repetitive tasks, reducing error rates and speeding up workflows. Hear Jonathan Menard, VP of Analytics at Experian Health talk to Andrew Brosnan of Omdia about how AI and automation are addressing staff burnout and improving revenue cycle efficiency. 4. Maintain regulatory compliance with minimal effort While regulatory compliance may not directly influence how quickly providers get paid, it does play a crucial role in preventing the delays, denials and financial penalties that impede the overall revenue cycle. Constant changes in regulations and payer reimbursement policies can be difficult to track. Automation helps teams continuously monitor and adapt to these changes for a smoother revenue cycle – often with parallel benefits such as improving the patient experience. One example is Experian Health's price transparency solutions, which help providers demonstrate compliance with surprise billing legislation while boosting patient loyalty via a more compassionate financial experience. 5. Improve the end-to-end claims process Perhaps the most obvious way RCM automation leads to faster reimbursement is in ensuring faster and more accurate claims submissions. Automated claim scrubbing, real-time eligibility verification, more reliable coding, and easier status tracking all improve the chances of a provider being reimbursed promptly and fully. And as artificial intelligence (AI) gains traction, providers are discovering new ways to use technology to improve claims management. AI AdvantageTM uses machine learning to find patterns in payer behavior and identify undocumented rules that could lead to a claim being denied, alerting staff so they can act quickly and avert issues. Then, it uses algorithmic logic to help staff segment and rework denials in the most efficient way. Providers get paid sooner while minimizing downstream revenue loss. 6. Get better visibility into improvement opportunities Finally, automation helps providers analyze and act on revenue cycle data by identifying bottlenecks, trends and improvement opportunities. Automated analyses bring together relevant data from multiple sources in an instant to validate decisions. Machine learning draws on historical information to make predictions about future outcomes, so providers can understand the root cause of delays and take steps to resolve issues. A healthcare revenue cycle dashboard is not just a presentation tool; it facilitates real-time monitoring of the organization's financial health, so staff can optimize workflows and speed up reimbursement. Revenue cycle automation is the solution Just like any business, healthcare organizations must maintain a positive cash flow to remain viable and continue serving their communities. Together, these six revenue cycle automation strategies can cut through many of the common obstacles that get in the way of financial stability and growth. Learn more about Experian Health's revenue cycle management technology and see where automation could have the biggest impact on your organization's financial health.
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.