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The media has extensively covered the healthcare workforce shortage and its impact on patient care. It's a chronic, dangerous problem that seems to worsen, despite the industry's efforts to staff up. A recent Experian Health survey found severe and long-term implications for revenue cycle management and its impact on provider and patient care. 100% of revenue cycle leaders surveyed agree the pervasive healthcare workforce shortage impacts their facility's ability to get paid. The problem isn't going away; most survey participants (69%) expect recruiting challenges to continue. Furthermore, nine of 10 survey participants admit to a double-digit turnover rate. However, the shortage of qualified labor is impacting healthcare in other areas beyond patient outcomes. The report shows the bottom line is clear: The healthcare workforce shortage impedes the industry's ability to get paid. How can providers solve this? Experian Health's survey, “Short Staffed for the Long-Term,” polled 200 revenue cycle executives to understand the impact of the hiring deficit's impact on provider cash flow. Survey Finding #1: Staffing shortages impede payer reimbursements and patient collections. 32% of survey participants said patient collections is the revenue cycle channel most impacted by healthcare workforce shortage. 22% said payer reimbursements are most affected by staff shortages. 43% said both channels were equally impactful to the healthcare revenue cycle. There was little disagreement in the survey around whether provider revenue cycle suffers from a lack of qualified staff. The debate centered on which reimbursement channel took the biggest hit. Experian Health's staffing survey revealed revenue cycle executives agree that collecting late patient payments is much more complicated now. The worker shortage impedes the ability to manage this process. In an era when many patients put off care due to high out-of-pocket costs, maximizing collections is more important than ever. Short-staffed, overworked healthcare collections teams require the time and tools to optimize the collections process by identifying the accounts more likely to pay. Patient collections teams could also benefit from software that finds financial assistance that could ease self-pay burdens. Collections Optimization Manager saves staff time by automatically determining the most suitable patient collections approach. The University of San Diego California Health (UCSDH) uses this software to segment patients by propensity to pay. It allows collections agents a more efficient, personalized approach to improve the revenue cycle and the patient relationship. From 2019 to 2021, UCSDH increased collections from $6 million to more than $21 million with this solution. Patient Financial Clearance automates screening prior to service or at the point of-service to determine if patients qualify for financial assistance, Medicaid, or other assistance programs. Kootenai Health leverages the software, which increased the accuracy of determining patient financial assistance by 88%, and saved 60 hours of staff time through automation. Together, these tools can ease the healthcare workforce shortage by optimizing and streamlining collections. Survey Finding #2: The healthcare workforce shortage contributes to increasing denial rates. 70% say escalating staff shortages increase claims denials. 92% report new staff member errors are a significant factor in delayed or declined reimbursement. Today, healthcare providers are seeing claim denials increase by 10 to 15% year over year. A lack of qualified revenue cycle staff costs billions annually in preventable revenue cycle errors. 35% of healthcare leaders admit losing more than $50 million yearly on denied claims. The complexities of the revenue cycle particularly challenge new staff; 92% of survey respondents say errors are common. Denied claims ripple across the revenue cycle, tying up staff time and provider cash flow. Ultimately, it is patients and staff who suffer. When hospitals experience restricted cash flow, it can hamper their ability to effectively deliver the highest quality care. When staff stretch to their limit due to the healthcare workforce shortage, they may make more errors, burnout, or quit. Automating the claims process is a necessity in this challenging environment. Tools like ClaimSource® and Claim Scrubber can catch errors before submission, reducing undercharges and denials. Franklin Healthcare Associates, a 100-provider, four-location practice, used Claim Scrubber to reduce accounts receivable (A/R) by 13%. As claims volume grew, the practice decreases its full-time employee (FTE) requirements by leveraging this automated tool. It's one clear example of how technology can stretch staff farther to improve the bottom line. Survey Finding #3 Staffing deficits aren't going away. Close to 70% of respondents believe revenue cycle staffing levels will continue as a problem into the future. Staff turnover is a contributing factor; 80% said their organization's turnover revenue of cycle management staff is between 11-40%. Experian Health's survey confirms that healthcare teams struggle to find qualified staff. Staff turnover is a significant contributor to a revolving hiring door. One survey showed the average hospital turnover rate is 100% every five years. Traditional solutions to the problem include throwing more money into salaries, bonuses, or other perks. Overtime is a go-to remedy for the chronic healthcare worker shortage. But these approaches strain the provider bottom line. A recent Kauffman Hall survey shows: 98% of healthcare providers have raised minimum wage or starting salaries. 84% offer signing bonuses, and 73% offer retention bonuses. 67% experienced wage increases of more than 10% for clinical staff. The American Hospital Association (AHA) states, “Hospitals also have incurred significant costs in recruiting and retaining staff, which have included overtime pay, bonus pay and other incentives.” But what if recruiting isn't the answer to the healthcare workforce shortage at all? Artificial intelligence (AI) and automation software can help cut costs and lessen the workload of existing staff. The latest data suggest providers could save close to $25 billion annually (one-half of what they spend on administrative tasks) if they leveraged these tools. Experian Health's  AI Advantage™ uses powerful algorithms to automate manual claims processes to reduce denial and lessen the volume of tasks for revenue cycle staff. The software works in two critical areas: Predictive Denials proactively cleans claims before they are submitted. The software flags claims at risk of denial, allowing manual intervention for a clean submission—with no denials. Denial Triage manages denied claims by identifying the highest value reimbursements to maximize cash flow. Instead of chasing low-value claims or those least likely to pay, the software prioritizes where revenue cycle staff should spend their time for the greatest return. Schneck Medical Center saw significant ROI from this software in just six months. AI Advantage helped the facility reduce denials by an average of 4.6% per month. Claims corrections that took up to 15 minutes in the past now take under five minutes. Better software can do more than help hospitals get paid faster. Automating revenue cycle management processes frees up staff time. More time and less pressure mean fewer mistakes. Automation can ease the impact of the healthcare workforce shortage Two of the most pressing problems hospitals face today are the healthcare workforce shortage and revenue cycle impediments that keep them from getting paid. These challenges interconnect, and providers can solve them both with better technology to automate time-wasting manual functions. AI and automation in healthcare can cut costs and reduce staff burnout. Deploying revenue cycle software to automate billing, claims management, and collections could save $200 billion to $360 billion in spending in this country. These numbers are real. But so are the numbers showing increasing claims denials, staff burnout, turnover, and difficulties recruiting in the healthcare field. Today, the answer for hospitals to get paid faster is to leverage modern technology to improve the revenue cycle. Learn more about how Experian Health's revenue cycle management solutions can help automate common processes, and download the new survey to see the latest healthcare staffing shortage stats.

Could common revenue cycle management (RCM) myths be preventing healthcare organizations from getting paid in full? Does what constituted best practice a few years back still apply to revenue cycle operations today? Many providers are embracing new technology to strengthen their RCM processes, using automations and software to create more accurate and efficient billing and claims management workflows. But if these processes are built on shaky assumptions, the results will be sub-optimal. As year-end financial reviews get under way, there is a prime opportunity to re-evaluate some long-standing beliefs about billing, collections and payments that, if not set straight, could limit financial performance in the year ahead. This article examines four of the most common revenue cycle myths and considers what providers can do to make financial growth a reality in 2024. Revenue Cycle Myth 1: All patients are equally likely to pay Reality: No two patients are alike – whether in their medical needs or financial circumstances. Providers know this, yet many rely on revenue cycle management solutions that lean toward a one-size-fits-all approach to patient payments. Instead, providers should consider RCM tools that use data and analytics to segment patients according to their individual financial situation, to create a more personalized and proactive approach to collections. This should take account of both the patient's ability to pay (i.e., whether they can afford their bills), and their likelihood to pay promptly, which may be enhanced by offering payment options that are convenient and aligned to their personal preferences. Collections Optimization Manager analyzes patients' individual payment history and demographic information so their accounts can be routed to the most appropriate collections pathway from the start. Patients that are likely to pay quickly can be sent billing information automatically and presented with self-service payment options. Alongside this, Patient Financial Clearance pulls together credit and non-credit data to help providers identify patients who may need a little more guidance and connect them to suitable payment plans. It catches any individuals who may be eligible for Medicaid or charity support. Staff get accurate, at-a-glance data to help them have sensitive financial conversations with patients, and can avoid losing time chasing collections from patients who would never have been able to pay. Case study: See how Stanford Health Care improved collections with a tailored, patient-focused approach to healthcare collections. Myth 2: It's hard to have meaningful pre-service financial conversations with patients Reality: Contrary to popular belief, most patients are receptive, and even eager, to have financial discussions with their provider as soon as possible. Doing so need not be challenging. In the past, providers may have worried that broaching the money question could deter patients from seeking necessary care, or simply not prioritized such discussions. Billing and insurance can also be highly complex, which may lead staff to assume that patients would find conversations about these issues to be confusing or overwhelming. But it is for these exact reasons that providers should have financial discussions with patients as early as possible. Experian Health's 2023 State of Patient Access survey found that almost 90% of patients wanted upfront pricing estimates so they could plan ahead for their financial obligations – yet less than a third received one. Tools like Patient Payment Estimates and Patient Financial Advisor can calculate cost estimates, taking account of the patient's claim history, deductibles and other insurance information, and automatically send these to patients before treatment so they know what to expect. These can also be combined with quick payment links so bills can be cleared before care. Giving patients consistent information through whichever digital channel they prefer means they will be better positioned to make informed decisions and discuss their situation with patient access staff if necessary. When patients are better informed and supported, they're also less likely to end up postponing care due to cost concerns. And with the same accurate data at their fingertips, patient access staff can serve as financial concierges, helping patients to understand coverage and copayments and check eligibility for relevant financial assistance programs. In addition to user-friendly data tools, providers should consider whether staff would benefit from additional training to bolster their confidence in leading compassionate financial conversations. Myth 3: It's impossible to know what patients owe across a system with a single look-up Reality: Thanks to data analytics and digital payment technology, it is now pretty straightforward to consolidate a patient's outstanding balance information from across an entire health system, and debunks common revenue cycle myths. Patient access staff can view a comprehensive summary of a patient's insurance status, estimated liability and open balances from multiple providers, enabling them to have meaningful financial conversations with patients. Even if these discussions do not lead to immediate payment, they can still act as a reminder to nudge the patient to act soon, thus accelerating the payment process. Selecting RCM tools from a single vendor makes it easier to integrate data from multiple workflows and generate a unified view of what a patient owes. When systems talk to each other, it's possible for a single tool to leverage the data and create a better experience for patients and staff. For example, PaymentSafe® automatically brings together data gathered throughout the revenue cycle to streamline what was previously a disjointed and time-consuming process. With point-to-point encryption, it accepts secure payments at any point in the patient's journey, using cash, check, card payments and recurring billing, through a single web-based application. Myth 4: Revenue cycle management is “set-and-forget” Reality: Revenue cycle managers may dream of setting up a system once and then forgetting about it, but the reality is that managing billing, claims and collections is an ongoing and evolving process that needs constant attention. Healthcare organizations must regularly review and adjust their RCM strategies to prevent missed revenue opportunities, manage compliance risks and promote operational efficiencies. That said, data analytics and automated revenue cycle management tools do make it far easier for providers to stay on top of RCM demands. These tools help providers with everything from monitoring payer policy changes and identifying billing errors to personalizing patient communications and generating monitoring reports. Artificial intelligence takes it a step further, for example, by preventing and predicting claim denials. In this way, these tools reduce the need for extensive staff input, so staff can spend more time focusing on the issues that need more human attention. With up-to-the-minute reports covering multiple RCM processes, staff also have the information they need to optimize performance and find opportunities to boost reimbursement that may have been previously overlooked. So, while RCM is not quite a “set-and-forget” process, automations and analytics can simplify it significantly, so it's less labor-intensive for staff and more efficient overall. Debunk revenue cycle myths and proactively challenge assumptions to increase profitability Debunking these revenue cycle myths is simple and achievable with tools that integrate a patient's clinical and financial data for a fuller picture of what that patient needs. This is crucial as changing consumer expectations, economic drivers, and new technology reshape how patients, providers and payers interact with one another. Checking underlying assumptions in any RCM process is essential to root out potential misunderstandings and outdated thinking. Not doing so leaves providers vulnerable to inaccurate financial projections, mismatched strategies and poor patient experiences. See how Experian Health's industry-leading Revenue Cycle Management Solutions make streamlined billing and collections a reality.

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.

Staffing shortages are the new normal in healthcare. Most news headlines focus on gaps between the supply of providers and the growing demand for care. However, a recent survey by Experian Health, released in November 2023. shows the massive impact staffing shortages have on back office revenue cycle where these functions intersect with front-of-house patient engagement. Strikingly, the healthcare staffing shortage statistics in the survey show revenue cycle executives are 100% in agreement—staffing shortages significantly affect reimbursement workflows to the detriment of patients and healthcare employees. Experian Health's report, Short-staffed for the long term, surveyed 200 healthcare executives responsible for revenue cycle functions. The goal was to gauge the impact of worker shortages on revenue cycle management and patient engagement. While the pandemic brought these shortages into the public purview, this new data shows most providers believe healthcare staffing gaps are chronic and here to stay. These results reinforce The State of Patient Access 2023 survey, where 87% of providers blamed staffing shortages for declining access to care. As the healthcare industry continues to struggle with an ever-increasing staffing shortage, it has become increasingly evident that if left unresolved, this situation can wreak havoc on revenue cycle management (RCM). The latest survey illustrates the need for new strategies to alleviate healthcare worker shortfalls. This article explores the most recent healthcare staffing shortage statistics and some key findings from the study to help determine how healthcare providers can turn these challenges into opportunities. Experian Health surveyed 200 revenue cycle executives to determine the impact of staffing shortages on reimbursement and patient engagement. Download the report to get the full results. Finding 1: Most revenue cycle leaders believe staffing shortfalls negatively affect payer reimbursements and collections. 96% of survey respondents indicated a lack of qualified workers has a detrimental impact on organizational revenue channels. 80% say turnover in their department ranges from 11 to 40%, much higher than the national average of 3.8%. When healthcare organizations lack revenue cycle talent, they risk missing performance goals. High turnover and the departure of experienced staff create information deserts within healthcare organizations. It forces new team members to train faster, handle bigger caseloads before they're ready, and potentially burnout from stress. The pressure to do more faster creates a higher volume of preventable claims errors that lead to denials. The survey showed all these factors at play, and their negative impact on reimbursement, collections, and the patient experience. While the traditional way to alleviate staffing shortages is to increase recruiting and retention efforts, these approaches no longer work when there simply isn't enough available staff to hire and train. Healthcare organizations must consider new partnerships with technology providers who offer automation tools to streamline human workflows. Revenue cycle management software eliminates repetitive tasks and lessens errors that lead to rejected claims. Digital technology can help solve labor shortages by reducing staff workloads and improving operational performance. Automation can streamline collections by prioritizing the accounts most likely to pay. These tools help existing revenue cycle teams work more efficiently while enhancing patient encounters. Finding 2: Healthcare staffing shortages roadblock a positive patient experience. 8 of 10 survey respondents say patient experience suffers due to gaps in staffing coverage. 55% report the patient experience is most heavily affected at intake, and 50% say at appointment scheduling. Staffing shortages and turnover cause an undue burden on the healthcare workers left behind. The survey asked respondents to indicate the top pain points experienced by revenue cycle professionals, and one of the major challenges was staff burnout. Stress has a detrimental effect on patient interactions throughout the revenue cycle. The survey shows staffing shortages impede patient satisfaction in critical areas within revenue cycle functions, including: Scheduling appointments Patient registration Prior authorization Insurance coverage confirmation Patient estimates Revenue cycle interactions can be delicate, requiring extreme patience and clear communication. Healthcare organizations must provide the support their revenue cycle teams need to handle these crucial conversations appropriately. To improve the patient experience, organizations must first improve the workflows and workloads of these critical back-office teams. When healthcare organizations have the right tools to eliminate manual tasks that bog down revenue cycle staff, these professionals can spend more time on the compassionate handling of patients and their accounts. Providers have the opportunity to solve these challenges with digital patient engagement solutions that improve workflow efficiencies at every level of the revenue cycle. Patient scheduling software creates a self-service environment that 73% of healthcare customers prefer. Patient intake improves with online software that automates the tedious paperwork that tie up staff. Better technology can create price transparency without manual effort, ensuring patients understand their responsibilities up front instead of facing surprises during or after care delivery. Finally, a frictionless online payment platform allows patients to handle their obligations seamlessly without staff intervention. Finding 3: Errors arise when healthcare providers are short staffed, leading to claims denials. 70% of survey respondents say staff shortages exacerbate denial rates. 92% of survey respondents said new staff members make errors that negatively impact claims processing. Some of the most common reasons for healthcare claim denials include: Incomplete collection of claims data Coding errors Billing errors Eligibility verification errors Missed insurance verification Healthcare operations and revenue cycles are full of manual processes. RevCycleIntelligence reports one-third of prior authorizations are completed manually, and two-thirds of hospitals haven't automated any part of their denials management processes. Yet technology has made significant strides toward reducing these error-prone manual tasks. Leveraging artificial intelligence (AI), with solutions like AI Advantage™, within the complexities of claims processing could cut provider spending by up to 10% annually. Eliminating repetitive tasks with automated claims management solutions improves the lives of staff, cuts manual errors that tie up cash flow in reimbursement wrangling, and creates a better, less stressful environment for customers. Reducing the impact of healthcare staffing shortages with revenue cycle automation and technology Sometimes, 100% agreement isn't the desired outcome. In this case, the healthcare staffing shortage statistics found in the survey shows healthcare providers agree unanimously that chronic staffing shortages create a problematic environment for employees that costs revenue and patient engagement. While technology exists that can maximize revenue staff workflows to extend the reach of overburdened employees; survey participants suggest that healthcare organizations continue to approach solving these issues by adding staff.  But healthcare's staffing challenges are not new. While organizations have historically invested revenue in higher salaries and sign-on bonuses to attract staff, technology offers a new opportunity for history to avoid repeating itself. It's time for healthcare organizations to support their teams with automation. These tools alleviate mundane, error-prone tasks that tie up staff. Experian Health offers these organizations a way to improve the lives of everyone within the revenue cycle by allowing back and front-office teams to focus on patient care, rather than filling in forms. It's a more humane way to handle a very human staffing crisis. Download the survey or connect with an Experian Health expert today to learn how we can help your healthcare organization combat staffing shortages.

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.'  

Compared to other industries, healthcare tends to be more resilient to economic turbulence. But the weight of the pandemic, labor shortages, rising costs and increasingly complex reimbursement structures are squeezing hospital margins. A Kaufman Hall National Hospital Flash Report in July 2023 found that many hospitals underperformed, and the gap between high-performing hospitals and those struggling continues to widen. Providers must find new and effective ways to improve revenue cycle management, should any new uncertainties emerge. With pressure mounting to increase efficiency and reduce expenses, more providers are turning to automation and artificial intelligence (AI) to eliminate unnecessary manual work and optimize revenue cycle management processes. For example, Stanford Health Care leveraged automation to reduce their cost to collect. Banner Health improved patient collections with transparent price estimates. Schneck Medical Center zeroed in on claims management and incorporated AI to reduce denials. In the face of a cashflow crunch, healthcare providers increasingly turn to data-driven revenue cycle management (RCM) strategies that span the entire patient journey. This article lists six of the most effective income-generating digital RCM strategies that providers are using to maximize profits. Building blocks of a healthy revenue cycle At its core, revenue cycle management is about ensuring providers are fully reimbursed for the care they provide. The true ROI is much broader – efficient financial and administrative processes for patient billing, claims management and collections contribute to better care, satisfied patients, high-performing staff and good financial health. Realizing these benefits calls for revenue cycle processes built on three principles: Efficiency – streamlining processes to reduce resource utilization across the entire billing cycle Accuracy – ensuring all patient and claims data is correct and complete to avoid denials and delays Transparency – giving patients, providers and payers relevant and timely information, so they can act with confidence in each financial transaction. To achieve this, providers are moving away from slow, costly manual systems. Digital RCM tools are becoming non-negotiable. 6 data-driven strategies for effective revenue cycle management 1. Increase efficiency in patient access Revenue cycle management starts when the patient books their appointment and ends when the final bills are settled. Claim denials and delayed payments often arise from data errors and miscommunications in the early stages of the patient journey, which means patient scheduling and registration processes are critical to streamline RCM. With automated, data-driven patient access tools, providers can simplify tasks across the patient journey, so patients can move from one stage to the next with as little friction as possible. Fewer errors mean delays and disappointment are more easily avoided. Automated registration and online self-scheduling can also lead to savings through more efficient use of staff time and reducing the number of appointment no-shows. Experian Health clients find that online tools allow them to make relatively minor adjustments to their workflows, with a major impact on productivity. 2. Deliver accurate and timely patient billing Patients want the payment process to be as painless as possible. In multiple surveys, Experian Health has found that patients are worried about the cost of care, while 63% of providers believe patients frequently postpone care because of cost concerns. Clear, comprehensive estimates, billing and collections practices can make it easier for patients to navigate their financial journey. And with the end of continuous Medicaid enrollment, it's likely that more patients will find themselves unsure of their coverage situation, and in need of greater support to manage the financial process. For Stanford Health, the key to improving revenue cycle management centered around patient billing and collections. To achieve the dual goals of improving the patient experience and increasing collections, they used data-driven insights and automation to remove uncollectible accounts, prioritize accounts with a high propensity to pay, find missing coverage and reduce the manual workload. Collections Optimization Manager helped Stanford Health identify the best possible collections strategy, by scoring and segmenting patient accounts with the highest propensity to pay. Coverage Discovery® supplemented this strategy by checking for any unidentified primary, secondary or tertiary coverages that can potentially reduce self-pay amounts and avoidable charity designations. As a result, Stanford Health achieved a $4.1m increase in average monthly payments and efficiency gains of $109k per month. 3. Provide transparent price estimates Experian Health's State of Patient Access 2023 report suggests that fewer than three in ten patients know how much their care will cost in advance, while nine in ten consider it important. Delivering accurate pre-care estimates to help patients plan for bills could therefore be an easy win to improve the patient experience and recoup more revenue. Banner Health used Patient Estimates as part of a wider strategy to improve patient collections. This solution generates detailed estimates of the patient's financial responsibility along with recommendations for payment plans and financial assistance, if appropriate. Listen in as Becky Peters, Executive Director of Patient Access at Banner Health, talks about streamlining the patient registration process and improving patient access with pre-care estimates. 4. Effective claims management Perhaps the biggest opportunity to improve revenue cycle performance lies in claims and denial management, which accounts for a major proportion of wasted healthcare dollars. Summit Medical Group Oregon–BMC paired Enhanced Claim Status with Claim Scrubber to submit cleaner claims the first time and avoid lost revenue. These tools help providers submit accurate claims and monitor claim status to prevent denials and resolve issues quickly. For Summit Medical Group, this led to a 92% primary clean claims rate, and a reduction in accounts receivable days and volume by 15%. Experian Health also offers a new solution that leverages machine learning and artificial intelligence for predictive reimbursement. AI Advantage™ uses AI to predict and prevent claim denials based on historical claims data. In the first six months, this solution helped Schneck achieve a 4.6% average monthly decrease in denials and decreased time spent on denials by 4x. 5. Easy ways to pay (plus clear pricing and payment policies) How easy is it for patients to pay? This simple but important question points to another vital element of effective revenue cycle management. A compassionate and convenient patient payment experience that matches consumer experience in other industries can encourage earlier payments. Easy digital options are especially important for millennial and younger patients: research by Experian Health and PYMNTS found that 60% of younger patients are looking for digital services. Experian Health's patient-friendly payment tools are designed to help patients navigate their financial responsibilities with confidence and ease. For example, PaymentSafe® allows providers to securely collect payments anytime, anywhere, including mobile payments and patient portals. 6. Operational efficiency with automation, data and analytics RCM processes generate vast amounts of data, providing valuable insights into the organization's operational performance, revenue trends and areas for improvement. Being able to parse and translate this data into actionable insights is essential to determine the right strategies to pursue to optimize financial performance. But this in itself can be a major lift. Revenue Cycle Analytics is a web-based tool that breaks down data into actionable insights across billing, reimbursement and payer performance, presenting KPI data via comprehensive dashboards. Effective revenue cycle management strategies from start to end From labor shortages to rising costs, healthcare providers are finding creative ways to manage cash flow. While each healthcare organization’s needs and goals are different, understanding these six key strategies of successful revenue cycle management can help hospitals manage their revenue cycles more effectively and efficiently, while responding to new uncertainties. Find out more about how Experian Health helps healthcare organizations leverage automation and AI to streamline processes and boost revenue cycle performance.