Tag: ClaimSource

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.

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.

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.

AI and automation could cut US healthcare spending by up to 10% – a promising figure for hospitals operating on razor-thin margins. Despite the potential for cost savings and revenue growth, investing in AI can seem risky while the technology feels relatively new. But as denial rates increase, staff shortages persist, and payers race ahead with their own AI-led efficiencies, investing in AI and automation could help healthcare providers increase efficiency and reduce manual workloads, while improving the patient experience. In a recent podcast interview, Johnathan Menard, VP of Analytics at Experian Health, talked to Andrew Brosnan of Omdia about how providers can use AI and automation in healthcare to reduce admin costs and tackle staff burnout, while maximizing the ROI on new technology. This article sums up the key takeaways. “AI and automation are gaining momentum in the healthcare revenue cycle, but there remains untapped potential” For healthcare leaders, maintaining the financial health of their organization is critical to serving their communities. Menard sees untapped potential to use AI to improve financial prospects by automating and eliminating administrative tasks within the revenue cycle: “There are many repetitive, tedious tasks involving large amounts of data that's already collected, and mostly structured and standardized. That can be organized and analyzed with AI to help improve efficiency and accuracy.” Automation is a well-established route to lowering manual workloads, increasing efficiencies and generating data for better decision-making. AI takes this a step further. For example, Experian Health's flagship AI platform, AI Advantage™, can parse an organization's data to identify and predict patterns in payer behavior. It translates this data into insights that help providers boost profitability and improve the staff and patient experience. Menard explains why claims management is a prime use case for AI: “Last year, the average denial rate was already above 11%. That's 1 in 10 patients potentially having to deal with uncertainty about who will pay the bill, when they should be focusing wellness. That's where we see Experian Health being able to lean in and drive value and change in the healthcare industry with AI.” “Cost is the biggest barrier to AI and automation adoption in healthcare – but can be offset with the right data” Despite the potential upside, healthcare still lags other industries when it comes to implementing AI. Menard says that workforce costs are the biggest barrier to adoption: “In healthcare, it's not just a matter of implementing the technology or solution, but also maintaining it on a yearly basis with talent. Organizations are going to have to recruit an AI-competent workforce.” He says that providers may struggle to offer competitive salaries to attract staff with this skillset, but there are other ways to offset cost concerns. One example is working with a trusted third-party vendor to choose the best-fit AI solution for their organization. These vendors can leverage economy of scale, data and lessons learned in other markets to help providers deliver new models of care: “At Experian Health, we have health data spanning eligibility and benefits, address, identity, claims remittance payments. We have insights on 300+ million consumers and 126 million households. We're able to offer providers one of the most holistic views of today's health care consumer. It gets really exciting when you think about partnering with providers to augment their capacity to deliver a different style of care.” “Providers need to make sure staff see the benefits of AI and automation” Menard notes that successful implementation of AI needs staff buy-in: “Providers need to make sure staff see the benefits of what this technology can bring. They must also make sure they give them the proper training on how to embrace these capabilities. They do not replace your job; they augment you to do more, or they allow you to focus on doing the right thing, not the right thing that needs their specific level of expertise.” AI Advantage is a prime example, reducing the admin burden for staff, who can then focus on higher priority tasks. The solution takes a two-pronged approach to help staff reduce claim denials and maximize reimbursement: AI Advantage – Predictive Denials synthesizes historical and real-time claims data and payer decisions to flag claims that are likely to be denied. This allows staff to intervene and make necessary amendments prior to submission. AI Advantage – Denial Triage performs a similar function for claims that do end up being denied. It helps staff eliminate time spent on low-value denials by guiding them resubmissions that are most likely to be reimbursed. Schneck Medical Center and Community Regional Medical Center (Fresno) are seeing the benefits of AI Advantage. Watch the on-demand webinar to hear about their results. Moving beyond proof of concept Menard acknowledges that providers need to feel confident in a tool's ability to deliver before they make an investment, especially if they are operating on single-digit margins: “You can't do that without the proof of concept. There are too many competing priorities, especially in the revenue cycle, and healthcare leaders need to be laser-focused and very confident in their decision-making.” In part, this is what Experian Health is looking to do with AI Advantage. By demonstrating the power of AI to reduce costs and alleviate staff pressures within claims management, it can act as a springboard for smarter automation across other revenue cycle operations. Menard believes that as AI adoption expands, it will become faster, easier and cheaper to develop solutions at scale: “That's why we built the AI Advantage platform – to launch other products in the future and solve other issues throughout the healthcare journey. We talked about automation, adoption and healthcare. To me, the best way to automate a process is to eliminate the need for it in the first place.” Find out more about how AI and automation in healthcare can reduce costs, prevent staff burnout and help providers prepare for future challenges.

Artificial intelligence (AI) is cropping up everywhere. But it's about to make an even bigger splash by revolutionizing how providers handle HCM (healthcare claims management). In healthcare, the claims process is a real source of frustration. Thirty-five percent of healthcare providers say they lose more than $50 million annually in denied claims. That's a lot of money lost for healthcare providers after care is delivered to their patients. As industry costs rise, healthcare claims management becomes an unsustainable financial drain for providers, who have no choice but to push these costs back to the patients they're trying to serve. Using AI for claims management has numerous benefits - and with denied claims on the rise, healthcare providers will need to incorporate this technology or risk leaving millions on the table. AI Advantage™, Experian Health's innovative predictive analytics software, uses AI in claims processing to help providers expedite reimbursement and improve cash flow. This software takes the unsolvable Gordian Knot that is U.S. claims reimbursement and untangles it for faster reimbursement, better cash flow, and less wasted time. Understanding AI in Healthcare Claims Management The odds are stacked against providers before the patient ever visits their practice. One patient claim can go through 20 or more checkpoints before the payer approves reimbursement. Denied claims are much less likely to be paid, and 89% of hospitals say denial rates are rising. An Experian Health survey said the three most common reasons for medical claim denials include: Missing or incomplete prior authorizations Failure to verify provider eligibility Inaccurate medical coding Without question, healthcare claims denial management must include better training for staff to file claims without error. Providers need accurate patient data upfront, with standardized verification processes at each step in the process.However, healthcare providers can reduce or completely avoid many common reasons for medical claim denials by using AI in claims processing. AI claims management software provides “teachable moments” for staff by sharing claims management errors at the front-end of processing before submission and possible rejection by the payer. Tom Bonner, Principal Product Manager at Experian Health, says, “Healthcare providers everywhere ask themselves: How can we reduce claims denials? But we have the technology to go even further. By using AI in claims processing, providers can avoid claims denials altogether by proactively spotting and correcting the human errors that slow down reimbursement before the claim is submitted to the payer.” Top Benefit of Using AI in Claims Processing - Providers Avoid Claims Denials AI and automation are the one-two punch providers need to improve healthcare claims processing. Using AI healthcare claims management software helps organizations avoid claim denials far upstream — before it occurs. AI Advantage - Predictive Denials is a preventative tool that proactively stops bad claims before they turn into costly denials. This AI-driven healthcare claims management software works in two key ways: By proactively identifying undocumented payer adjudication rules potentially resulting in denials. By identifying claims with a high likelihood of denial based on an organization's historical payment data. Schneck Medical Center improved their claims management processing by using AI Advantage - Predictive Denials to first identify error-prone claims. When the automated system spots the probability of a denial, it triggers an alert that routes the claim to an investigative biller. The AI carefully scrubs the claim, checking coding errors, authorization status, insurance eligibility, and more. Once the agent resolves these errors, they can successfully submit the claim to the payer. Using AI in claims processing leads to improved accuracy and fewer rejections for better revenue cycle management. After leveraging these tools for six months, Schneck Medical Center reduced denials by 4.6% on average per month. Benefit #2 - Healthcare Claims Management Software Speeds Denials Mitigation But what if a claim makes it through to the payer and they deny it? Denial management is a tedious, time-consuming process that impedes cash flow. AI Advantage - Denial Triage uses advanced algorithms to segment denials based on their potential value, allowing billers to focus first on high-value claims to maximize the revenue cycle and quickly reduce the denials queue. AI in reimbursement processing increases the speed of healthcare claims management to help staff identify and target the claims that need attention as quickly as possible without wasting time on low-value denials. By using automation and AI, healthcare providers gain better insights into their claims and denial data, resulting in improved financial performance and greater efficiency. Benefit #3 - AI Software Automates Reimbursement for Faster Payment Experian Health offers a streamlined series of standardized, automated tools to help with claims management. From registration, quality assurance, and eligibility on the front-end to claims processing and denials management on the back-end, Experian Health has full lifecycle solutions to prevent and mitigate reimbursement denials. The Experian Health intelligent ecosystem is a comprehensive solution to the untenable healthcare claims denials management process. These tools include: ClaimSource: Voted Best in KLAS Claims Management Clearinghouse 2023, this healthcare claims management software gives providers reimbursement visibility in real-time from one intelligent hub. This software helps providers handle the entire reimbursement cycle. The tool allows end-users to create custom work queues to manage claims more efficiently. It also automates claims, allowing the software to clean submissions before they send. Flagging features let billers know exactly what's wrong with a claim, so staff can repair the error. Ensuring clean claims lessens denials and improves cash flow. Claim Scrubber spots claim errors within 3 seconds, flagging the claim with an explanation of why it needs reworking. Intelligent algorithms identify undercharging to maximize payer-allowed amounts. For medical billers and coders, this tool quickly spots the root causes of claims denial, faster and more accurately than doing it by hand. Enhanced Claim Status connects billers quickly to denied, pending, returned-to-provider, or zero-pay transactions well before the EOB or Electronic Remittance Advice forms process. Instead of waiting 30- or 45 days to review a denied claim, this software lets teams see the problems online in real time. It's an immediacy that's been missing from both front- and back-end claims management processes, allowing real teaching moments for revenue cycle teams. Denials Workflow Manager: Eliminates manual processes and allows providers to optimize the claims process. Providers no longer review claims manually, instead using computer automation to optimize follow-up activities. Claims management teams can quickly identify and target the claims needing attention quickly. Powerful features leverage root cause analysis to identify trends leading to claims denials. These platforms easily integrate with existing practice management and electronic health record software. They work well together or ala carte to increase the accuracy of claims documentation to eliminate denials. A successful strategy for reducing claims denials starts with AI and automation software. Healthcare organizations can reduce the time spent processing rejections and improve A/R by flagging at-risk claims. Ultimately, healthcare claims management software solves the complexities inherent in these processes. Higher patient satisfaction and greater provider revenues are possible. Talk to Experian Health today to see AI in claims processing at work.

Nearly three out of four healthcare leaders said reducing claims denials was their highest priority in  Experian Health's State of Claims Report. But knowing how to reduce claim denials is difficult. According to the survey, 62% of providers said they had insufficient access to data and analytics, and 61% lacked automation to meet the challenges of healthcare claims management. New and emerging artificial intelligence (AI) tools aim to help providers overcome these hurdles. Makenzie Smith, Product Manager at Experian Health, shares her thoughts on how providers can harness AI tools to predict, prevent, and prioritize claim denials for better results—and why preventing claim denials is so critical now. Q1: What is the challenge for revenue cycle teams, specifically when it comes to managing claims denials? “Revenue cycle teams that want to optimize claims processing have to respond to shifting payer behaviors, including major changes in the volume of denials,” says Smith. “Payers have been able to outpace providers in adopting new technologies, including AI. Payers are able process claims in a matter of seconds. For revenue cycle teams, that means receiving a large volume of denials all at once, which can be overwhelming.” At the same time, keeping up with policy changes is more than a full-time job. “You may have 20 different payers, each with multiple plans and policies that each have their own reimbursement or clinical guidelines,” says Smith. None of these policies are static: “They're constantly changing, which creates a huge challenge for providers.” Finally, maintaining enough staff to manage increased volume is an uphill battle. “The number of team members handling denials has not grown in a proportional way. Quite the opposite: They're being asked to do more with less. As providers continue to struggle with staffing imbalances, the challenge is not only having somebody to actually sit in these seats, but also managing the constant training and retraining that goes along with it.” Q2: Why is effective denial management so critical for providers' success?  “By one estimate, half of our country's hospitals are operating in the red,” says Smith. “Healthcare finance professionals are under incredible pressure to maintain or increase their operating margins. Meanwhile, Experian Health data shows that most organizations operate with an initial denial rate of 10% to 15%, and that rate is increasing year over year. “Effective denials prevention and management allow providers to get paid appropriately for services they've already provided,” Smith continues. “Optimizing revenue, improving cash flow, and maintaining expenses all stack up to provide meaningful financial resources providers can use on essential investments in staffing, physician recruitment and retention; capital equipment; and the expansion of services or service areas.” Providers that can't maintain healthy margins may be at risk for acquisition. “[Providers' viability is] put at risk daily because they must fight for every dollar from payers,” says Smith. Q3: How is Experian Health helping providers leverage AI tools and technology to start leveling up their denial management strategies? “Healthcare claims management technology solutions should be helping to bring providers up to speed,” Smith says. “Experian Health has released two products powered by a machine learning technical enablement layer to the market this year. Providers that use ClaimSource® to manage their claims can add AI Advantage™ tools to improve the way they manage claim denials. “AI Advantage - Predictive Denials uses AI and the provider's historical claim and remit data on the most probable reasons for medical claim denials to predict when claims will deny, in real-time, prior to claim submission. Billing teams can review denial predictions within their existing claim review workflows,” says Smith. “The design is incredible, allowing teams a seamless workflow integration with almost zero additional training.” “When denials do occur,” Smith continues, “AI Advantage - Denial Triage provides a predictive score based on the likelihood of recovery. Many denial follow-up teams prioritize working denials based on the highest charge amount. While that seems like a logical approach, there's a better way: segmenting by likelihood of recovery to drive priority and accelerate cash flow and recovery rates.” Q4: How is AI Advantage different from using human intelligence to predict and triage claim denials? “In some ways, it's quite similar,” Smith explains. “I was a director of billing for several years before I came to Experian Health. Often, one of the more senior billers would come to me and say, 'Hey, we're starting to see a trend with this payer, or with this denial reason code. We probably need to talk to our payer representative about this.' AI Advantage uses machine learning to identify these trends with greater speed and effectiveness, system-wide and in real-time. “Without this tool, one biller could see a denial happening twice and think nothing of it, while the biller sitting next to them is experiencing the same thing. This technology compiles all of this information together and identifies the holistic picture, so everyone benefits and trends don't go undetected.” Using AI in claims processing can make human teams more productive; it may help them feel empowered as well. Schneck Medical Center saw an average 4.6% monthly reduction in denials after six months of using AI Advantage. “Our people spend hours and hours on the phone with insurance companies fighting for dollars on claims we believe [are payable],” says Skylar Earley, Director of Patient Financial Services at Schneck. “Any leg up we can give our team members is a big, big deal.” Watch the webinar to hear from Eric Eckhart of Community Regional Medical (Fresno) and Skylar Earley of Schneck Medical Center as they discuss how their organizations use AI tools for claims management. Q5: What types of denials can providers expect to prevent, versus those that will continue to be denied? “Overall, the answer depends on a few things: an organization's healthcare claims denial management processes and ability to change on the one hand, and payer requirements on the other,” Smith says. “Too often, providers say they're just playing the game that payers put forward, simply so they can get paid what they are contractually owed.  As an industry, we cannot continue to accept this as the status quo. We'll find ourselves and our communities in a worse position to access healthcare.” Organizations that are willing to adopt new technology and be agile with their denial strategies can reduce their denial rates, even in a constantly changing environment. “I've seen the most success in denial prevention with eligibility, authorization, and technical billing categories,” says Smith. “But AI and machine learning are opening the door for new potential strategies that are more effective, more efficient, and more productive.” Q6: Clearly, claim denials affect providers, but patients also have a stake here. How do denied claims interfere with a positive patient experience? “There's definitely a patient impact,” says Smith. “Medical billing is already confusing, and a lot of people just don't understand their insurance to begin with. Add in potential denials and bills that seem to keep coming for months and months before getting resolved, and patients are bound to feel frustrated. Getting claims right on the first submission solves many of these issues up front. It reduces anxiety and makes for a much better patient experience overall.” Adding AI to the claims management toolkit Understanding how to avoid claim denials is a priority with good reason: Minimizing denials can improve revenue, lighten the burden on staff, and even help maintain a positive patient experience. Marginal changes make a difference: Smith notes that an increase in denied claims from 10% to 12% at an organization with $500 million in gross patient revenue represents a $2 million impact. Adding AI tools doesn't eliminate all the challenges of managing healthcare claims, but it does help equip providers for the current environment—and the future. Learn more about how AI Advantage can help providers prevent denials, improve the likelihood of reimbursements, and prioritize denied claims for reworking more efficiently and effectively.

Payers are using automation to adjudicate healthcare claims at scale, leaving providers struggling to keep up. One major insurer was found to have denied over 300,000 claims in two months, with each one taking an average of just 1.2 seconds. Providers that continue to rely on manual claims management methods will see their margins squeezed as the denials challenge grows. The future of healthcare claims management is here - and the answer lies in artificial intelligence (AI). Providers can level the playing field by turning to AI and automation , using tools like AI Advantage™ to streamline healthcare claims management. This article summarizes a recent webinar with two early adopters, Eric Eckhart of Community Regional Medical Center (Fresno) and Skylar Earley of Schneck Medical Center, who are using the technology to prevent denials and increase collections. Small increases in claim denials can lead to major revenue loss Makenzie Smith, Product Manager for AI Advantage at Experian Health, set the stage with observations on the current state of claims management. She notes that one of the biggest challenges when it comes to denials is constantly shifting payer behavior: “So many payer decisions are now being driven by artificial intelligence. Insurers are reviewing and denying at scale using intelligent logic, leaving providers fighting harder for every dollar.” Two hypothetical scenarios illustrate the potential impact of just a 2% increase in denials, assuming other variables remained constant: In an organization with a gross patient revenue (GPR) of $500m, an increase in denials from 10% to 12% could squeeze operational margins from 3% to 2.6%, resulting in a drop in net income from $15m to $13m. In an organization with a GPR of $2000m, an increase in denials from 18% to 20% could wipe out a 0.35% margin completely, causing net income to fall from $7m to 0. Some providers are choosing to stick with their existing processes; changing course seems too risky within thin margins. But as Eric Eckhart points out, “the just-work-harder approach doesn't work anymore.” Providers need a more efficient way to sustain operating margins. How AI Advantage helps reduce denial volume and improve net collections AI technology is emerging as a better alternative to the status quo. By using automation and AI, providers can gain insights into their claims and denial data, resulting in improved financial performance, greater efficiency and improve the future of healthcare claims management. AI Advantage™ – Predictive Denials uses AI to identify claims with a high likelihood of denial based on an organization's historical payment data. This allows staff to intervene prior to claim submission. It identifies undocumented payer adjudication rules that result in new denials. It works within Experian Health's ClaimSource® solution to proactively flag at-risk claims, allowing teams to review them within their existing claims workflow. Key takeaways from 2 real-world examples of AI in healthcare claims management Eckhart and Earley share how they are approaching denial prevention in today's fast-changing claims environment. Below are the key takeaways from their conversation about how AI is helping to optimize reimbursement and support their teams: Providers need to move beyond the “just work harder” approach to claims management Eckhart says that staffing challenges were a major driver of his organization's early adoption of AI Advantage, as it became harder to manage the increasing rate of denials with existing resources: “I think we've all tried the “let's work very hard approach” and worked overtime for months on end, but that's just not a long-term solution. We were looking for something technology-based to help us bring down denials and stay ahead of staff expenses. We're very happy with [AI Advantage] and the results we're seeing now.” Skylar Earley agrees, saying that despite their efforts, the rate of denials stayed the same. “It's so important for us to reduce denials because costs are increasing, reimbursements are decreasing, payments are shrinking. In our smaller community, there are only so many ways to grow revenue. We've got to maximize reimbursement, however we can.” Discover how Schneck Medical Center used AI to prevent claim denials.   Seamless integration with ClaimSource® was key to staff adoption While senior leadership teams may have been on board with testing the new technology, staff members were more hesitant about the potential pitfalls of introducing a new tool. Eckhart says, “Experian were already processing our claims through Claim Scrubber, so the workflow was essentially the same. I got some pushback when I said it was AI. I think the biggest fear for my billers was that they were going to get 5000 alerts that they would have to override and ignore. But we phased it in slowly and that was a good approach.” Earley agrees: “This is probably one of the most seamless products I've seen: it's entirely in ClaimSource®. If you didn't know about it, you wouldn't know it was there. The people using the product don't toggle back and forth between screens, they don't run reports to view alerts. The product shows them what claims they need to look at.” The predictive model gives staff their time back – so savings snowball For both organizations, a big win from AI Advantage was being able to reduce denials so staff could focus on other tasks. Making better use of staff time is increasingly urgent as the growth in denied claims outpaces recruitment. Eckhart says that over the last six months, his team have saved 30 hours a month in collector time. “Now I have almost a whole week a month of staff time back, and I can put that on other things. I can pull that back from outsourcing to other follow-up vendors and bring that in house and save money. The savings have snowballed. That's really been the biggest financial impact.” Reducing denials with accurate predictions Eckhart and Earley report that the success of the tool comes down to the accuracy of predictions, and the fact that it uses their own data. This applies to claims submitted to commercial and government payers, including prior authorizations. For example, Schneck Medical Center is seeing an ongoing reduction in AR days, while the number of authorized outpatient visits has increased by around 2.5% since implementing the technology. In addition to improving claims management processes, AI Advantage also helps root out persistent payer errors. Eckhart says that while denials teams tend to focus on high value claims, smaller payers can sometimes make erroneous denials that add up over time. The tool brings this to light so providers can raise it with the payer and fix it going forward. The future of healthcare claims management is here Ultimately, every prevented denial means more dollars coming back to the provider, increasing their capacity to deliver high quality services. Revenue growth makes it possible to recruit more staff, reduce outsourcing, increase capital purchases, introduce new service lines, and even explore merger and acquisition strategies. Payers are already making strides in their use of AI technology and automation, but with AI Advantage, providers can process accurate claims and reduce denials at a scale and pace to match. Find out more about how AI Advantage™ is changing the future of healthcare claims management and watch the webinar to hear the full conversation on 'The Future of Claims Management. Today.'  

With the ability to be applied across many different areas – from disease prediction to claims management and administrative tasks – data and analytics in healthcare is booming. In fact, according to a Grand View Research report, the global market for data analytics was valued in 2022 at $35 billion and is expected to increase at a compound annual growth rate of 21.4% until 2027. So, why the rapid growth? How can healthcare data analytics be used across the healthcare revenue cycle? The role of data and analytics in healthcare Historically, there has been a large amount of healthcare data being generated, but the industry has struggled to properly leverage this data into useful insights that improve patient outcomes, operations, or revenue. Today, with increasingly advanced data analytics, healthcare providers are using real-time data-driven forecasts to stay nimble and pivot quickly in rapidly changing healthcare and economic environments. And there is more data collaboration between healthcare organizations to convert analytics-ready data into business-ready information, thanks to the ability to automate low-impact data management tasks. Data-derived intelligence is also now easier to share with colleagues, third parties and the public. Types of healthcare data analytics methodologies and tools Healthcare data analytics involves several different types of methodologies and tools – all of which can be applied to various aspects of revenue cycle management. For example, descriptive analytics allows organizations to review data from the past to gain insights about previous trends or benchmarks. Predictive analytics, on the other hand, uses modeling and forecasting to help predict future results. When a strategic course of action is needed based on certain data inputs, prescriptive analytics is used. If a provider wants to take a deep dive into raw data to uncover patterns, outliers, and interconnection, they may employ discovery analytics. There are also generally three categories of technology-driven tools that can help collect and convert raw data into usable insights during the revenue cycle, including: Solutions that gather data from a wide variety of sources, such as patient case files, machine-to-machine data transfers, and patient surveys Programs designed to scrub, validate, and analyze data in response to a specific question being researched Software created to leverage the results produced by the analysis into actionable suggestions that be applied to meet specific goals Applying data analytics to maximize revenue “There are many things driving near-constant change in the healthcare revenue cycle, including shifting reimbursement, evolving value-based payment models, growing regulatory pressures, and increasing provider risk and patient responsibility,” says John Menard, VP of Product, Analytics, at Experian Health. “Healthcare organizations are also adapting to value versus volume reimbursement models, requiring revenue cycle leaders to lean into leveraging data analytics to improve not just operational efficiency, but patient financial experience and quality outcomes as well." Here's a closer look at how data analytics can help with revenue cycle management: Assessing patient finances From registration to collections, data analytics can play a key role at every step of the patient journey – and revenue cycle. Not only can the right data analytics tools help healthcare organizations better assess a patient's individual financial circumstances, but they can also help providers create accurate estimates and payment plan recommendations. Data-driven technology can help providers reduce surprise billing through more transparent pricing, helping patients navigate the cost of care and providing more timely patient communication. Digital solutions can help improve the patient financial journey by: Providing a self-service patient portal – With a solution like PatientSimple, patients get convenient 24/7 access to self-service account management tools. They can use the online portal to log into their healthcare account to securely process payments, request or review payment estimates, and schedule appointments. The portal also provides patient access to pricing information, plus the ability to apply for financial assistance or set up payment plans. With easy-to-use patient online tools, patients are more likely to meet their self-pay responsibilities and providers get paid more quickly as a result. Offering payment solutions – To collect payments with confidence, healthcare providers can utilize comprehensive data collection and advanced analytics through a digital solution like Patient Financial Clearance. With this solution, providers use a patient's financial data to quickly assess a patient's propensity and likelihood to pay prior to treatment. When appropriate, providers can then offer empathetic financial counseling and connect those that potentially qualify to financial assistance programs. By applying data analytics to this payment solution, healthcare organizations can increase point-of-service collections while reducing bad debt—in real-time. Providing patients with more accurate estimates – A recent Experian Health study found that 4 in 10 patients said they spent more on healthcare than they could afford. However, when patients know the expected cost of their care up front, they feel more empowered and make better decisions. Patient Estimates lets providers create more accurate estimates, eliminate manual tasks and improve patient satisfaction. Plus, it allows providers to automate and standardize their price transparency practices, which can help healthcare organizations meet regulatory requirements, create a more positive patient experience and increase revenue at the point of service. Reduce denied claims According to Experian Health's 2022 State of Claims survey, denied claims are on the rise with 42% of providers reporting that denials increased in the past year. 47% of respondents also said improving clean claims rates was a top pain point. Digital solutions can help providers reduce denied claims and increase revenue by: Automating claims management – With a solution like ClaimSource®, providers can automate their claims management systems – helping to ensure claims are clean before they are submitted to a government or commercial payer. Using an automated solution also allows providers to streamline the claims management process from a single web application. With ClaimSource, providers can easily analyze claims, payer compliance and insurance eligibility. Plus, it allows staff to prioritize their workload and focus on high-impact accounts – resulting in claims denial rates of just 4% compared to the industry average of more than 10%+. Optimizing efficiencies through artificial intelligence – Incorporating artificial intelligence (AI) into an automated claims management solution enhances the claims process in two key moments: before claim submission and after claim denial. AI Advantage™ integrates seamlessly with ClaimSource to continuously learn and adapt to ever-changing payer rules. The solution features two AI offerings, AI Advantage – Predictive Denials and Denial Triage, which can be customized to prioritization thresholds. Verify insurance and patient information Missing patient healthcare data can be a headache for providers to hunt down but looking for active coverage is often necessary. Providers must contend with a range of factors impacting patient coverage – including forgotten coverage, inadequate coverage, patients being misclassified as self-pay and regulatory changes, particularly with Medicaid and Medicare coverage. Implementing digital solutions can help providers use data to verify and find missing patient health insurance coverage, optimize patient collections, and boost revenue by: Utilizing automated, real-time insurance verification – Verifying patient coverage prior to service using a digital solution, such as Experian Health's Insurance Eligibility Verification. This tool can help providers experience fewer payment delays and claim denials. Plus, verifying insurance with automated insurance eligibility and benefits data improves cash flow, reduces claims denials and speeds up payments, including Medicare reimbursements. Patients also feel empowered with accurate payment estimates and accelerated registration, leading to a better patient experience overall. Improving collections with better data – With Collections Optimization Manager, providers can screen out bankruptcies, deceased accounts, Medicaid and other charity eligibility ahead of time. Through targeted collection strategies, providers can leverage actionable insights to focus on high-value accounts. Plus, predictive algorithms and data-driven rules help providers route and distribute accounts to the right collectors and agencies, controlling overall collection costs. This solution also connects providers to live support from an experienced optimization consultant that will help develop a tailored collection strategy through data evaluation and industry knowledge. Finding unidentified coverage – In 2022, Coverage Discovery tracked down previously unknown billable coverage in 28.1% of self-pay accounts, finding more than $64.6 billion in corresponding charges. Providers can use Experian Health's Coverage Discovery solution at any point in the revenue cycle to look for previously unidentified coverage – maximizing insurance reimbursement revenue and reducing accounts sent to collections, charity, or bad debt. Coverage Discovery also automates self-pay scrubbing and proactively identifies billable Medicare, Medicaid, and private insurance options, using a mix of search, historical information, proprietary data sources and demographic validation. See how the right data and analytics can help providers better understand their patients, streamline operations, and improve revenue.