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Contracts govern the revenue cycle, but negotiating contracts and ensuring compliance can feel increasingly unmanageable as mergers and acquisitions, ongoing staffing challenges, and the sheer volume of contracts, plans, and provisions make contract management a massive project for healthcare providers. Tricia Ibrahim, Director of Product Management at Experian Health, shares her insights on a challenging environment heading into 2024. Providers are grappling with mounting complexity, an explosion of data, and continuing pressure to maximize efficiency and revenue. But, according to Ibrahim, healthcare contract management software is evolving to meet these challenges—and helping providers find clarity amid the complication. Q1: What are the major challenges with healthcare contract management as we move into 2024? “I think what clients are most concerned with, especially leading into 2024, is the complexity of payer contracts,” says Ibrahim. A typical provider may manage hundreds or thousands of contracts, each one with a range of plans and provisions that affect the bottom line. “Being able to negotiate better contracts is a key concern,” says Ibrahim, “but clients increasingly feel outgunned and overwhelmed by the amount of information involved.” Accessing and analyzing data effectively is more critical than ever. “When providers come together with payers to negotiate contracts, it can be difficult for them to evaluate the contract that the payer is putting in front of them,” in part because it's hard to know how their current contract is performing or how contract provisions will play out in dollars and cents, Ibrahim explains. “Underpayments and denials are a constant struggle. Also, providers need to understand how volume and patient mix will factor in.” Contract management has a direct effect on revenue and the bottom line. Negotiated terms may or may not cover actual costs. A small change in terms might have an outsized effect due to high volume. Denied claims, underpayments, downcoding and late payments can slow the revenue cycle and reduce the amount of revenue providers receive. “At the same time, we're also starting to see a greater interest in collaboration between providers and payers,” says Ibrahim. “Having additional visibility allows both parties to have more meaningful discussions and move toward solutions that work for everyone.” Q2: What are providers doing to take on these challenges? “Many providers are investing in technology,” says Ibrahim. “A 2023 analysis by Bain & Company found that 80% of healthcare executives had accelerated software and IT investment over the past year in response to mergers and acquisitions, staffing shortfalls, and an increasing need for efficiency.” As contract management becomes more complex, providers are also reaching for more powerful healthcare contract management software tools to manage data—and leverage it to negotiate contracts effectively and monitor contract compliance over time. Q3: How can healthcare contract management software like Experian Health's Contract Manager and Contract Analysis help providers negotiate better contracts? “Having meaningful information backed by data changes the dynamic,” Ibrahim says. “It allows you to have a more strategic conversation. You can say, 'You're supposed to pay us 45 days from the receipt of the claim, but it's been taking 140 days.'” Data provides objective information and can point the way toward measurable improvements going forward. “Our Contract Analysis module allows for the provider to audit payer contract performance,” says Ibrahim. That's not only helpful for tracking what's happened to date; it's also useful for projecting how a new contract might work going forward. “We're able to use historical claims to create scenarios that show how a new contract would affect payment. Sometimes, payers will keep reimbursement rates the same where you have a lot of volume and give you an increase where you don't. When you use our solution to run these types of analyses, you get a more effective understanding of proposed terms.” Q4: Once contracts are in place, how can healthcare contract management software help providers improve compliance? “Detailed analysis is key, and small discrepancies can have a significant impact,” says Ibrahim. “One of our clients, a large academic provider on the medical group side, spotted a trend where they were being underpaid by 10 cents to 50 cents on their EKGs. These kinds of variances typically go unnoticed, but they found 20 or 30 claims to submit.” The payer acknowledged the underpayment and issued the few dollars' difference. “Then the provider decided to look at their contract to see how far back they could appeal. It turned out they were able to go back a significant amount of time. When they added up the underpayments, it equated to $850,000. They ended up settling for $750,000,” Ibrahim says. OrthoTennessee, a Knoxville-based orthopedic practice with multiple locations and more than 50 physicians, uses Experian Health's Contract Management software for healthcare to find inaccuracies, make appeals, and audit contracts at scale. Using Experian Health's Contract Management platform, OrthoTennessee had an 86% success rate for appeals in 2022. “That's the power of the solution: You can really identify trends,” says Ibrahim. Monitoring compliance is a continuous effort: “We’ve done a lot of work with our clients to understand what their evolving needs are. We’ve been named Best in KLAS [by healthcare IT research firm KLAS] multiple years in a row. That recognition has centered around engagement—being engaged with our clients, so we understand what the trends are, what challenges they’re facing, and how we can help solve problems in the most efficient manner.” Q5: What role do regulations play in shaping contract management solutions? “Regulation drives different reimbursement methodologies, [such as] bundled payments or value-based care,” says Ibrahim. “Part of our challenge is making sure we are always evaluating new regulations and ensuring that our system is agile enough to support these new methodologies. “Because regulation never stops, it actually drives a lot of the innovation we do. The No Surprises Act, which came into effect in 2021, requires providers to provide patients with a good faith estimate of costs. We've been able to help clients establish an estimated median rate, which can be useful for estimates that involve non-contracted payers.” As an additional benefit, healthcare contract management software also helps providers spot opportunities. “One of our clients identified 26 plans with enough volume to support additional contracts,” says Ibrahim. “Providers can even use these solutions to evaluate whether a market exists for a new piece of technology to deliver state-of-the-art care. Understanding performance is a powerful tool.” Q6: Early in our conversation, you said there was a growing interest in collaboration among providers and payers. What does it mean to take a collaborative approach in this context? “I think it's really important for providers and payers to have collaborative communication, to engage in productive conversations where they can work together instead of against each other,” says Ibrahim. “That's how we're going to deliver more integrative care and reduce costs. It’s how we’re going to arrive at coverage options that work for all parties, by developing good relationships between providers and payers. “For our part, Experian Health is continuing to expand Contract Manager to provide data analytics that clearly show the cost of care and the expected reimbursement for various types of services, so providers can evaluate contract performance, identify potential areas of improvement, and have meaningful conversations with payers. “At the end of the day, we all have a common goal: delivering appropriate care at the right time for patients,” Ibrahim concludes. “To progress toward that goal, payers, providers and partners like Experian Health are going need to work together.” These conversations start with a common set of data, so that everyone at the table understands where the opportunities to collaborate and improve may lie—and where the path forward may begin. Learn more about Experian Health's Healthcare Contract Management software and how it can help your organization negotiate and manage contracts effectively and efficiently, even in an increasingly complex environment.
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.
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.
Getting a claim right the first time is much less expensive than reworking it. Experian Health's 2022 State of Claims survey illustrates most claims denials result from simple human errors. Automation and claim scrubbing software help lower the burden of denied claims. But payer contract management software offers one of the most critical strategies for optimizing revenue cycle. These tools help providers maximize reimbursements throughout the lifecycle of their payer contracts. Experian Health client OrthoTennessee, which has an 86% successful appeals rate, recovers hundreds of thousands of dollars annually by conducting contract audits and recovering underpayments with these tools. This result could extrapolate across healthcare if providers consider implementing payer contract management software. Understanding the financial impact of denial rates Denial rates can significantly affect a healthcare provider's revenue. One study showed these administrative complexities cause $265 billion in healthcare misspending annually. Preventing claims denials should be a high-priority issue for healthcare providers. It's an untenable situation for cash-strapped healthcare providers, and by most accounts, the problem is getting worse. Payer contract management software reduces denial rates. A well-managed contract ensures providers are reimbursed accurately and promptly, reducing denials due to billing errors or non-compliance. Individual payer contracts stipulate how and how much a healthcare provider gets paid. In addition to critical payment terms, payer contracts contain: How many days a provider has to submit a claim How many days the payer will take to reimburse a correctly submitted claim The services and scope of coverage by payer Reimbursement rates for every covered service How to dispute a claim denial The term of the payer contract When to renegotiate or the notice period for a contract termination Most of these reimbursement contracts allow payer amendments. Tricia Ibrahim, Director of Product Management, Contract Manager Suite, says, “Depending on how the contract is written, providers may receive very little notice of these changes. Without a way to systematically and efficiently monitor these agreements throughout the contract term, there is simply no way for a provider to ensure they're paid properly.” Better payer contract management can reduce denials and improve revenue collection by reducing the most common reasons for medical claim denials. Proactive strategies for denial reduction Proactive denial reduction correlates with a better bottom line. This effort entails a multi-faceted approach with two key elements at its core: Analyzing payer contracts for pitfalls To mitigate denials effectively, healthcare providers must scrutinize payer contracts meticulously. By delving into the fine print, organizations can identify potential pitfalls and the sources of denials. Whether complex reimbursement terms, ambiguous language, or stringent coding requirements, a comprehensive contract analysis can unveil these challenges. Crafting contract strategies for denial mitigation With a deep understanding of contract nuances, providers can develop tailored strategies for denial mitigation. These strategies encompass streamlined claims submission and staff training. Additionally, organizations can engage in informed negotiations with payers to amend unfavorable reimbursement terms. Through this fusion of contract analysis and proactive strategy development, providers can navigate the complex landscape of healthcare payer contracting with precision, ultimately reducing denials and bolstering financial stability. Crafting comprehensive contract management strategies for denial mitigation Developing proactive strategies within payer contract management is a critical component of denial reduction. For example, when creating payer contracts in healthcare, providers must proactively negotiate advantageous terms for their organization. These negotiations should focus on fair reimbursement rates, reasonable timeframes for claims submission, and other favorable conditions that minimize the potential for denials. Strategies should also encompass addressing ambiguities in healthcare payer contracting. These misunderstandings lead to disputes and denials. Clarifying any vague or unclear language within the agreement ensures all parties have a shared understanding of the terms and expectations. Finally, to mitigate denials effectively, healthcare payer contracts should align seamlessly with billing and coding practices. These contracts must reflect current industry standards and guidelines to prevent discrepancies resulting in claim rejections. Harnessing the power of payer contract management software in healthcare Payer contract management software offers healthcare providers a powerful way to automate payer document analysis. A single provider can have 20 or more payer contracts to manage. From HMOs to PPOs, fee-for-service federal programs, third-party administrators, to ACOs and CINs—the payer list can be long. While a thorough analysis of healthcare payer contracting is essential to identify potential areas of improvement, it can be challenging to scrutinize all of these contract terms and conditions to mitigate future denial risks. But with the right software, this revenue cycle function can be a game-changer. Payer contract management software can handle contract renewal and regulatory updates automatically, ensuring healthcare providers remain compliant. The software eliminates the hours spent manually reviewing data. Some of the benefits include: Centralizing contracts in one location Alerting significant milestones, such as contract renewals or changes Automating processes and workflows Linking contracts with provider procedures and complianc OrthoTennessee Manager of Payer Strategy, Frances Thomas, uses Experian Health's payer contract management software. She states, “The system gives us the information we need to be successful. They can't really argue with you on that.” The role of automation in error reduction Healthcare runs on revenue. Automation is pivotal for reducing healthcare claims errors that tie up revenue in the denials process. Automation software streamlines workflows, reducing manual intervention and the likelihood of human errors. These tools can apply across the revenue cycle, including during the payer contract management process. For example, Experian Health's payer contract management software includes Contract Manager and Contract Analysis features that can automatically: Compare the expected payment with the actual reimbursement from payors Maintain and manage contract terms Pinpoint underpayments Audit claims Analyze claims data and the financial impact of potential changes to provider fee schedules Highlight bulk claims for appeal en masse OrthoTennessee highlights the importance of the ability to handle claims in bulk. Thomas says, “We had over 600 claims for one day in the wrong network. I was able to take that bulk of claims and handle those—otherwise, I was going to have to sit there and go claim by claim. It's a huge time saver to work smarter, not harder.” Real-time verification and validation with automation Automated systems revolutionize healthcare operations by offering real-time verification and validation capabilities. Automation technology streamlines the billing process and minimizes errors that can lead to claim denials. It enhances efficiency and precision, allowing healthcare staff to allocate more time to patient care. As providers embrace automation, they can expect increased accuracy and financial stability. RevCycleIntelligence estimates the healthcare industry could save nearly 41%, or nearly $25 billion, of the $60 billion they spend annually by fully automating administrative transactions. But payers also stand to benefit; McKinsey says administrative automation could shave 30% off insurance claims processing costs. Seamless integration of automation with payer contracts Integrating automation tools with payer contracts in healthcare enhances efficiency. Integration ensures contract terms are consistently applied throughout the claims lifecycle, reducing denials. Interoperability between these platforms also improves the payer-provider relationship by increasing communication and streamlining processes. Cross-platform integration creates two-way accountability that's a win/win for both provider and payer. It's a transformative step in healthcare revenue cycle management that could: Streamline claims submission, verification, and adjudication Continuously monitor claims for contract adherence and correct problems before they lead to denials Reduce human errors Apply advanced analytics to identify trends and patterns Improve contract negotiations with data-driven decision-making Lower administrative costs Navigating challenges and embracing payer contract management software Healthcare providers face numerous challenges in revenue cycle management, especially when handling intricate payer contracts and the need for standardized handling of these documents. These challenges create scenarios where providers underbill or are underpaid for services, in addition to tying up revenue in denials management. Becker's Hospital Review reports providers lose up to 3% of their revenue from underpayments. Plus, the insurance industry isn't immune to making mistakes; the AMA says the claims processing error rate of public and private payers is more than 19%. By harnessing the power of technology, healthcare providers can streamline complex payer contracts and standardize how providers handle these agreements. For example: To expedite negotiations, modeling tools within payer contract management software offer claim scenarios that help providers negotiate better rates from payers. These systems provide real-time feedback through smart log messages, enhancing staff training and refining registration best practices. Most healthcare organizations lack the time and resources to closely monitor payer contracts. When these agreements are on auto-renewal, it's easy to forget their importance. Payer contract management software helps these organizations wring the maximum amount out of these revenue streams. Embracing Experian Health's payer Contract Management software Experian Health's healthcare payer contract management software offers a comprehensive contract management solution that can substantially lower denial rates. By adopting this software, providers can maximize revenue potential and streamline their revenue cycle. Importantly, healthcare providers can implement payer contract management tools without adding staff or conducting major process improvements. This software is the one tool organizations need to ensure they don't leave revenue on the table. Learn more or contact us to speak to our experts.
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.
With artificial intelligence (AI) continuing to dominate conversations among healthcare's strategic thinkers, it's clear that recent innovations in this field could herald a step-change in healthcare delivery. AI's ability to mimic human intelligence and machine learning (ML)'s capacity to learn from vast amounts of data means these technologies are fast becoming indispensable tools for healthcare leaders who want to optimize operations. Understanding how they work – and where to apply them for maximum impact – will be crucial to stay ahead of the competition as the revenue cycle landscape evolves. This article breaks down the what, why and how of AI technology in healthcare, and includes a look at Experian Health's new AI-based claims denial solution, AI Advantage™. Understanding machine learning and AI in healthcare The terms “machine learning” and “artificial intelligence” are often used indiscriminately, but what do they mean in a healthcare context? Generally speaking, AI is a machine's ability to perform cognitive functions that would normally be associated with humans, such as interacting with an environment, perceiving information, and solving problems. It can spot patterns, learn from experience and choose the right course of action to achieve a desired outcome. This includes natural language processing, robotics and machine learning. In healthcare, AI might be used to transform diagnosis through the analysis of medical images, expedite drug discovery by monitoring side effects, improve the safety and efficiency of surgery through robotics, and support patients to take ownership of their own health through health monitoring and wearables. Machine learning is a broad term that covers the processes used to extract meaning from (usually large) datasets to create and train a predictive model. It will look for historical patterns in input and output that a human eye might miss, and generate recommendations based on outcome parameters defined by the user. For example, it can look at patients' electronic health records to identify those who may be at risk of specific medical conditions so they can be offered appropriate advice. Another useful application is in predicting service demand, for more efficient appointment scheduling and resource allocation. Further subsets of machine learning include supervised learning, where training data is labelled with the desired outcomes that the algorithm should aim to detect, and unsupervised learning, which has no predefined targets and is useful for discovering patterns, insights and anomalies. Unlocking the AI Advantage™: how AI can reduce claim denials and improve financial performance The transformative potential of ML and AI technology in healthcare isn't limited to clinical decision-making and patient engagement: optimizing revenue cycle operations is a particularly attractive place to leverage the technology. It can be used to identify and reduce billing errors, enhance coding accuracy, and predict revenue leakage. This results in faster payments, better use of staff time and fewer claim denials. However, Experian Health's State of Claims 2022 survey revealed that while 51% of providers were using automation, only 11% of providers had integrated AI technology into their claims processes. Experian Health's new AI-based claims solution is specifically designed for those looking to take the next step to leverage AI to predict and prevent denials. AI Advantage takes a two-pronged approach to reduce the risk of denials and expedite any rework that may be needed. AI Advantage – Predictive Denials examines claims before they are submitted and calculates the probability of denial, based on thresholds set by the provider. It incorporates historical payment data and undocumented payer claim processing behavior to evaluate individual claims in real-time, with a level of speed and accuracy that would be unachievable using manual processes alone. High-risk claims can be edited before submission to reduce the risk of denial. AI Advantage – Denial Triage evaluates and segments denials based the likelihood of reimbursement following resubmission and prioritizes the work queue based on financial impact. It learns from payers' past decisions to formulate recommendations with increasing accuracy. This means staff can eliminate guesswork and focus their attention on the denials that will be most likely to yield results. See how Experian Health's AI-powered solution works to reduce and prevent denials. Challenges to watch out for when implementing AI While the benefits are clear, the rise of AI in healthcare applications also brings some challenges. Here are some key questions to consider for smooth implementation: How reliable is the data underpinning AI technology? AI tools are only as good as the data they're analyzing. Without high-quality, structured data, they will be unable to make accurate predictions. Providers need to ensure that data is available in a usable format and free from errors. Partnering with a reliable third-party vendor can help ensure all the relevant boxes are ticked. Does the technology integrate easily with existing workflows and software systems? Integrating new tools with the existing RCM infrastructure can be complex. Organizations often have legacy systems that may trigger interoperability issues, limiting effective data exchange and requiring staff to log in to multiple interfaces. A single vendor solution can mitigate for this. For example, AI Advantage fits together seamlessly with the industry-leading claims processing tool, ClaimSource®. Experian Health's consultancy team are also on hand to ensure smooth implementation. Does the software protect data privacy and security? Healthcare data is subject to multiple privacy and security regulations, such as HIPAA. Any new technology that processes data must comply with regulations and industry best practice. Being able to reassure patients that their data is safe is also an important driver of patient loyalty. What does the future hold for AI technology in healthcare? Looking ahead, the role of ML and AI in both patient-facing healthcare processes and revenue cycle operations is only going to grow. Predictive analytics will give staff increasingly powerful insights and recommendations to maximize reimbursement, while minimizing the burden on the workforce. Emerging technologies such as robotic process automation and natural language processing will offer more sophisticated and comprehensive workflow solutions, while AI's ability to continually learn and improve means providers that leverage AI will be better placed to make full use of their data and adapt to evolving trends and challenges. Discover how AI Advantage™ is helping Experian Health's clients transform their healthcare operations.
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.