First Pst after migration to Cloud in Health care Blog

Prospects for US hospitals that closed out 2022 at a financial loss looked brighter by the end of 2023, prompting cautious optimism heading into 2024. An industry analysis published in October 2023 found that most hospitals were back in the black from March 2023 onward, while the economy more generally ended the year with a strong finish. That said, healthcare margins remain slim, and expenses continue to grow. Finding efficiency savings across all operations remains a top priority. That's where revenue cycle automation comes in. With revenue cycle automation, providers can eliminate many of the persistent pain points in traditional revenue cycle management (RCM). Staff no longer lose time to tedious manual tasks, patients get their queries answered faster, and managers get the meaningful data they need to drive improvements. And the biggest win? It's easier for providers to get reimbursed for the services they provide – faster and in full. What is revenue cycle automation and how does it work? Healthcare revenue cycle management knits together the financial and clinical components of care to ensure providers are properly reimbursed. As staff and patients know all too well, this can be a complex and time-consuming process, involving repetitive tasks and lengthy forms to ensure the right parties get the right information at the right time. This requires data pulled from multiple databases and systems for accurate claims and billing, and is a perfect use case for automation. Revenue cycle automation refers to the application of robotic process automation (RPA) to these repetitive, rules-based processes. In practice, this might include: Automatically generating and issuing invoices, bills and financial statements Streamlining patient data management and exchanging information quickly and reliably Processing digital payments Collating and analyzing performance data to draw out useful insights. Common RCM challenges Automation is already making headway in tackling some of the most pervasive challenges, such as: Stemming the rise in claim denials: Experian Health's State of Claims 2022 survey found that a third of providers had around 10-15% of their claims denied. These often result from errors made earlier in the revenue cycle such as incorrect patient information or overlooked pre-authorizations. RCM automation reduces the propensity for errors significantly. Streamlining patient access: Without a welcoming digital front door, the revenue cycle gets off on the wrong foot. Automation can be deployed in patient scheduling and registration to ensure patient information is collected and stored quickly and accurately. Improving collections rates: Self-pay patients (who are increasing in number) want clear, upfront information about what their care is likely to cost. Providers can find themselves playing catch-up if patients are unsure about what they owe. Automated tools that generate accurate estimates and support pre-service payment can build a more resilient cash flow. Expanding access to data insights: One of the biggest ironies in revenue cycle management is that more data is collected than ever, but managers are struggling to digest it and uncover actionable insights. RCM automation helps identify patterns in claims and collections. Six ways revenue cycle automation accelerates reimbursements Let's break down these opportunities into six specific actions providers can take to improve their organization's financial health: 1. Capture accurate information quickly during patient access Victoria Dames, Vice President of Product Management at Experian Health, says, “Patient access is the first step in simplifying healthcare and revenue cycle processes. Replacing manual processes and disjointed systems with integrated software solutions can reduce errors, improve efficiency, offer convenience and transparency to patients, and accelerate the healthcare revenue cycle.” Patient Estimates automatically compiles an accurate breakdown of what a patient is likely to owe before or at the point of service. It builds in prompt-pay discounts, financial assistance advice and instant payment links, so patients are more likely to pay sooner. 2. Simplify collections and focus on the right accounts Healthcare collections are a drag on resources. Automating the repetitive elements in the collections process helps reduce the burden on staff. Collections Optimization Manager leverages automation to analyze patients' payment histories and other financial information to route their accounts to the right collections pathway. Scoring and segmenting accounts means no time is wasted chasing the wrong accounts. Patients that can pay promptly are able do so without unnecessary friction. As a result, providers get paid faster. 3. Reduce manual work and staff burnout Chronic staffing shortages continue to plague healthcare providers. In Experian Health's recent staffing survey, 96% of respondents said this was affecting payer reimbursements and patient collections. While automation cannot replace much-needed expert staff, it can ease pressure on busy teams by relieving them of repetitive tasks, reducing error rates and speeding up workflows. Hear Jonathan Menard, VP of Analytics at Experian Health talk to Andrew Brosnan of Omdia about how AI and automation are addressing staff burnout and improving revenue cycle efficiency. 4. Maintain regulatory compliance with minimal effort While regulatory compliance may not directly influence how quickly providers get paid, it does play a crucial role in preventing the delays, denials and financial penalties that impede the overall revenue cycle. Constant changes in regulations and payer reimbursement policies can be difficult to track. Automation helps teams continuously monitor and adapt to these changes for a smoother revenue cycle – often with parallel benefits such as improving the patient experience. One example is Experian Health's price transparency solutions, which help providers demonstrate compliance with surprise billing legislation while boosting patient loyalty via a more compassionate financial experience. 5. Improve the end-to-end claims process Perhaps the most obvious way RCM automation leads to faster reimbursement is in ensuring faster and more accurate claims submissions. Automated claim scrubbing, real-time eligibility verification, more reliable coding, and easier status tracking all improve the chances of a provider being reimbursed promptly and fully. And as artificial intelligence (AI) gains traction, providers are discovering new ways to use technology to improve claims management. AI AdvantageTM uses machine learning to find patterns in payer behavior and identify undocumented rules that could lead to a claim being denied, alerting staff so they can act quickly and avert issues. Then, it uses algorithmic logic to help staff segment and rework denials in the most efficient way. Providers get paid sooner while minimizing downstream revenue loss. 6. Get better visibility into improvement opportunities Finally, automation helps providers analyze and act on revenue cycle data by identifying bottlenecks, trends and improvement opportunities. Automated analyses bring together relevant data from multiple sources in an instant to validate decisions. Machine learning draws on historical information to make predictions about future outcomes, so providers can understand the root cause of delays and take steps to resolve issues. A healthcare revenue cycle dashboard is not just a presentation tool; it facilitates real-time monitoring of the organization's financial health, so staff can optimize workflows and speed up reimbursement. Revenue cycle automation is the solution Just like any business, healthcare organizations must maintain a positive cash flow to remain viable and continue serving their communities. Together, these six revenue cycle automation strategies can cut through many of the common obstacles that get in the way of financial stability and growth. Learn more about Experian Health's revenue cycle management technology and see where automation could have the biggest impact on your organization's financial health.

Racing against the clock to troubleshoot billing issues, claims bottlenecks and staffing shortfalls are just part of an average day for healthcare revenue cycle managers. It's hard enough to maintain the status quo, never mind driving improvements in denial rates and net revenue. With integrated artificial intelligence (AI) and automation, many of these challenges in revenue cycle management (RCM) can be alleviated – and with just a single click. Real-time coverage discovery and coordination of benefits software reduces errors and accelerates accurate claim submissions. This eases pressure on busy RCM leaders, so they have the time to focus on improving the numbers that matter most. Top challenges in revenue cycle management Efficiency is the currency of revenue cycle management. Maximizing resources is not just about keeping dollars coming in the door but about making the best use of each team member's time and expertise. The ever-present call to “do more with less” is probably the biggest challenge. Breaking that down, some specific concerns that consume more time and resources than RCM managers would like, are: Complex billing procedures: With hundreds of health payers operating in the US, each offering different plans with different requirements, providers have their work cut out to ensure claims are coded and billed correctly. Any errors in verifying a patient's coverage, eligibility, benefits, and prior authorization requirements can lead to delays and lost revenue. More claim denials: Inaccurate patient information and billing codes guarantee a denial. Beyond the rework and revenue loss, denied claims leave patients with bills that should not be their responsibility to pay, causing confusion, frustration, and higher levels of bad debt. Garbage in, garbage out. Patient payment delays: A few years back, patients with health insurance represented about a tenth of bills marked as bad debt. Now, this group holds the majority of patient debt, according to analysts. The rise in high-deductible health plans combined with squeezed household budgets means patients are more likely to delay or default on payments. Providers must be on the lookout for ways to help patients find active coverage and plan for their bills to minimize the impact of these changes. How can AI-powered revenue cycle management solutions help? The Council for Affordable Quality Healthcare (CAQH) annual index report demonstrates how much time can be saved using software-based RCM technology. Case in point: switching from manual to automated eligibility and benefits verification could save 14 minutes per transaction. This adds up quickly when daily, monthly, and yearly transactions are factored in. Predictive analytics can be used to pre-emptively identify and resolve issues and support better decision-making, giving providers a head start on those elusive efficiency gains. Three specific examples of how automation, AI and machine learning can streamline the front-end and solve challenges in revenue cycle management are as follows: 1. Upfront insurance discovery to find and fill coverage gaps Confirming active coverage across multiple payers gives patients and providers clarity about how care will be financed. But this can be a resource-heavy process when undertaken manually. Coverage Discovery uses automation to find missing and forgotten coverage with minimal resource requirements. By unearthing previously unidentified coverage earlier in the revenue cycle, claims can be submitted more quickly for faster reimbursement and fewer write-offs.With Experian Health's recent acquisition of Wave HDC, clients now have access to faster, more comprehensive insurance verification software solution. The technology works autonomously to identify existing insurance records for patients with self-pay, unbillable, or unspecified payer status and correct any gaps in the patient's coverage information. The patient's details are updated automatically so that a claim can be submitted to the correct payer. 2. Real-time eligibility verification and coordination of benefits As it gets harder to figure out each patient's specific coverage details, it also makes sense to prioritize automated eligibility verification. Eligibility Verification uses real-time eligibility and benefits data to confirm the patient's insurance status on the spot.Similarly, Wave's Coordination of Benefits solution, now available to Experian Health clients through Patient Access Curator, integrates directly into registration and scheduling workflows to boost clean claim rates. It automatically analyzes payer responses and triggers inquiries to verify active coverage and curate a comprehensive insurance profile. This means no insurance is missed, and the benefits under each plan can be coordinated seamlessly for more accurate billing. 3. Predictive denials management to prevent back-end revenue loss Adding AI and machine learning-based solutions to the claims and denials management workflow means providers can resolve more issues pre-claim to minimize the risk of back-end denials. Use cases for AI in claims management might include: Automating claims processing to alleviate staffing shortages Reviewing documentation to reduce coding errors Using predictive analytics to increase operational efficiency Improving patient and payer communications with AI-driven bots All of these contribute to a front-loaded denials management strategy. While prevention is often better than a cure, AI can be equally effective later in the process: AI AdvantageTM arms staff with the information they need to prevent denials before they occur and work them more efficiently when they do.Whatever new challenges may pop up on the RCM horizon, AI and automation are already proving their effectiveness in helping providers save time and money. But more than that, they're giving busy RCM leaders the necessary tools to start future-proofing their systems for persistent and emerging RCM challenges. Learn more or contact us to find out how healthcare organizations can use AI and automation to manage current revenue cycle management challenges with a single click.

Healthcare is a challenging profession. Providers understand that their mission of care delivery is fueled by the revenues they capture; after all, it is the business of healthcare. However, capturing revenues through the claims management process is burdensome and complex. Denials are all too common, hampered by inefficient workflows and manual tasks. As a result, it slows down reimbursement and impacts revenue. Moving toward reliable claim acceptance requires the strategic use of automation and technology to reduce denials. These initiatives accelerate the cycle of payments, improve cash flow, and ease strains on existing staff. This article takes a deep dive into the challenges of healthcare claims processing and strategies to help providers transform the claims management process. Challenges of healthcare claims processing The healthcare claims management process desperately needs modernization and optimization. Last year, an Experian Health survey showed that three out of four providers say reducing claims denials is their top priority. What's making it so difficult for providers to get paid? The healthcare reimbursement journey Let's start with the typical claims management process. Step 1: Prior authorization The first issue is that most generally accepted standard practices in healthcare claims processing create a long journey for provider reimbursements. This journey starts even before patient care, at eligibility and preauthorization. The American Medical Association (AMA) states, “Prior authorization is a huge administrative burden for physician practices that often delays patient care.” While prior authorization may help insurance companies reduce the cost of “unnecessary” treatments, the data shows it's having the opposite effect on the providers themselves. An AMA physician survey shows that 86% of prior authorizations lead to higher overall utilization of services. The practice doesn't appear to help patients, either; the AMA says 94% of doctors report care delays related to prior authorization, and 82% say patients abandon their treatment plans due to prior authorization struggles. Step 2: Data capture The second part of healthcare claims processing begins after the patient encounter. It involves many manual tasks, often leading to errors and claim denials. Intake and billing specialists must gather data from multiple sources for coding claims, including electronic health records (EHRs), physician notes, diagnosis codes, paper files, and the patients themselves. These workflows require significant manual data entry and review, which is impacted further when codes or insurance reimbursement requirements are out-of-date in provider systems. A recent survey shows that 42% of providers report code inaccuracies, and 33% say missing or inaccurate claims data as the top reasons for rejected claims. Step 3: Processing claims denials Post-submittal, there's more work when claims bounce back. It's part of the claims management process with the most inefficiencies and friction, costing the average provider millions annually. Healthcare providers experience Experian Health survey—but that number is rising. Responses from Experian Health's State of Claims 2022 report revealed that 30% of respondents experience denials increases of 10 to 15% annually. In June 2022, Experian Health surveyed 200 revenue cycle decision-makers to understand the current state of claims management. Watch the video to see the results: These challenges illustrate the need for modern and optimized healthcare claims processing. With this lens in place, healthcare providers can apply more effective claims management strategies to increase claims accuracy and reimbursement and reduce denials. Innovating your claims management strategy Healthcare professionals and organizations can proactively address challenges in the claims acceptance process by implementing effective strategies to optimize revenue cycle management. This effort should include the following: A cohesive and comprehensive claims management processNew approaches to outdated claims management workflows will address gaps, inefficiencies, and errors. Upgrading to a turnkey insurance claims manager can reduce denials and speed up claims processing. Address data quality and consolidationThe sheer volume of data required for healthcare claims processing increases the risk of errors. If the data isn't accurate at the front end, it's a fast track to denial. But claims go through multiple touch points in disparate systems without a single source of control and oversight. Organizations can employ standards for data intake to reduce inaccurate or incomplete patient information and duplicates and leverage technology to aggregate data from the multiple sources needed for claims processing. Implement best practices for denial workflowsClaim denial management on the backend of healthcare claims processing is even more challenging than capturing patient data at the front end of the encounter. Managing claims denials is time-consuming, and delays reimbursements, but denial workflow technology can streamline all follow-up activities. With this support, billers have less administrative work and can stretch farther, alleviating the burden of staffing shortages. Deploy tools for analysis and prioritizationA claims management platform can automatically analyze the components of each claim. With this information, the technology can prioritize denials workloads so high-impact accounts get the most attention. Upgrade claims technology automation with artificial intelligence (AI)Providers can transform claims management with a technology update. According to the State of Claims report, almost half of organizations replaced legacy healthcare claims processing technology in the past year. A vital component of this upgrade includes expanded automation capabilities that stretch the workforce further. Solutions like AI Advantage™ can help speed up the claims management process by predicting and preventing denials. Add prior authorization softwareAnalysis suggests that healthcare could automate up to 33% of manual tasks. Research on the benefits of automation showcases its potential for decreasing errors and other reimbursement obstacles. With prior authorization software, task assignment is seamless, and AI adds even more functionality with predictive capabilities. Accelerate claim follow upMonitoring claim status is another aspect of the payment ecosystem that heavily impacts provider cash flow. Technology automates much of this workflow. Organizations can adopt functionality that eliminates manual follow-up tasks to accelerate an unwieldy process. These solutions enable providers to respond quickly to issues, enhancing productivity beyond basic ANSI 277 claims status responses. Technology is the unifying thread behind a cohesive claims management strategy for any healthcare provider struggling with a high rate of denials. While 61% of providers lack automation in the claims/denials process, increasing evidence shows these tools drive revenue cycle efficiencies that transform claims denials management. Forward-thinking organizations like Summit Medical Group Oregon—Bend Memorial Clinic (BMC) leverage Enhanced Claim Status and Claim Scrubber to achieve a 92% primary clean claims rate. Schneck Medical Center uses AI Advantage to denials by an average of 4.6% each month. Implementing effective claims management strategies Strategies rooted in reliable, practical technology transform the claims management process. Healthcare organizations benefit from AI-driven automation solutions as part of an overarching claims management strategy that streamlines workflows, reduces denials, and boosts cash flow. Experian Health offers a portfolio of provider claims management tools to help organizations realize effective claims management process improvements to get paid faster. Learn more about the No. 1 Best in KLAS 2023 Claims Management and Clearinghouse tools or contact us to see how Experian Health can help improve your claims management processes.