AGS Health, a leading provider of tech-enabled revenue cycle management (RCM) solutions and a strategic growth partner to healthcare providers across the U.S., has received a UiPath AI25 Award for the company’s innovative use of automation and AI to support greater accuracy and efficiency in the intake and management of faxed documents.
Despite efforts to eliminate faxing, use of this cumbersome, inefficient, and costly technology by healthcare organizations remains prolific. Over 9 billion fax pages are exchanged annually at a cost of $125 billion, significantly straining already limited resources.
AGS Health’s IntelligentFax Processor automates this process, accelerating indexing, enhancing accuracy, reducing costs, and improving efficiency by leveraging a hybrid workflow model combining GenAI and robotic process automation (RPA) with manual indexers to handle exceptions. The system can handle a wide array of document formats and types, including consultation notes, test results, and medical records. Powered by advanced AI, it learns and adapts to the unique fax templates of each organization, ensuring accurate data extraction and categorization.
The annual UiPath AI25 Awards recognize the 25 most innovative UiPath customers using a combination of AI and automation as a strategic change enabler to accelerate bigger and bolder outcomes. AI and automation are redefining what’s possible—not just in business, but in the ways we work and live. This powerful combination creates fast, comprehensive, and actionable insights to inform decisions—uncovering never-before-seen opportunities for productivity and innovation.
Various forms of automation have long been present within healthcare revenue cycle management (RCM). However, advances in artificial intelligence (AI) have brought the industry to a significant inflection point, where the use cases for AI tools are expanding as rapidly as their capabilities.
We sat down with Thomas Thatapudi, chief information officer of AGS Health, to discuss the current and future state of AI in RCM and what healthcare organizations need to know about effectively integrating it into workflows.
EHR: How are automation and AI reshaping healthcare’s approach to revenue cycle management?
Thatapudi: Healthcare finance leaders have long recognized the power of simple automation, like simple rules-based workflows or analytics dashboards, to improve billing processes and error rates. Now, advanced AI tools like ChatGPT, large language models, and generative AI – or GenAI – have brought RCM to an inflection point with a variety of viable new AI-driven RCM use cases that could have significant financial impacts. AI and automation can reduce manual labor costs and increase net revenue through a seamless process that follows the entire patient journey, from preventing authorization denials upfront and reducing coding errors to implementing more proactive and efficient accounts receivable follow-up processes.
With front-end revenue cycle tasks such as insurance verification and prior authorization, we have an opportunity to create a completely seamless and interactive process for patients while ensuring the presence of appropriate controls to mitigate revenue leakage. For mid-cycle coding, certain specialties lend themselves to autonomous coding that eliminates the need for human intervention, freeing staff to focus on more complex work. On the back end, the focus can shift to denial management and collection rates, particularly for claims that, due to capacity constraints, were left unworked in the past. This can be particularly beneficial in cases where payer requirements have become more stringent.
These examples are just the tip of the iceberg in terms of potential RCM use cases over the next two years.
EHR: What are some examples of areas where AI tools are being used to improve RCM?
Thatapudi: AI is being used in clinical documentation, patient communication and payments, scheduling, prior authorization, and medical coding. In fact, coding has been utilizing true AI and machine learning in the form of NLP-based computer-assisted coding (CAC) for about a decade. With existing CAC applications reaching a plateau in coding accuracies of approximately 70-75 percent, new autonomous solutions are entering the market that leverage deep learning models and Gen AI to truly increase fully automated coding rates. I expect that coding will be one of the RCM areas that will be most heavily impacted by true AI, machine learning, and deep learning.
EHR: How can finance leaders make use of advanced data analytics and business intelligence (BI) tools to inform RCM decisions and measure their impact?
Thatapudi: BI tools can measure a wide range of metrics, from the number of system users to interactions and accounts, all of which can inform the key performance indicators (KPIs) that are crucial for monitoring financial performance. The problem is that the sheer volume of metrics can easily be overwhelming, which can lead to analysis paralysis. To prevent this, it’s important to take a step back and home in on KPIs such as financial indicators like collection rates per day or per month and the time it takes to collect payments—performance indicators that tell how much in time and money is being spent to recover a dollar so it can be reduced or better managed.
It’s important that senior leadership avoid being overly impressed by the wealth of intelligence that can be collected and displayed on a dashboard. The focus should instead be on determining the KPIs that drive day-to-day operational decisions. For example, predictive analytics services help healthcare organizations better predict denials, anticipate underpayments, forecast payments, and more. This allows for proactive claim correction prior to submission, which improves clean claim rates and cash flow. Creating simulations and projections for customized “what-if” scenarios provide an understanding of the impacts associated with interdependent metrics.
The prior authorization process has evolved in complexity as the healthcare industry transitions from fee-for-service to value-based care. At the same time, payers are expanding the number of services subject to prior authorization to establish medical necessity and appropriateness. It’s a one-two punch that leaves providers and provider organizations struggling under the weight of a prior authorization burden that, left unaddressed, can have long-term revenue cycle impacts.
Today’s prior authorization process involves time-consuming steps, including gathering and submitting medical documents to insurance companies and waiting for approval. It also often involves dealing with denials and appeals – all while guidance around required documentation becomes stricter.
The number of procedures subject to authorization is also expanding, creating new challenges for staff who must understand the clinical documentation and office notes necessary to support the authorization. This also means the addition of new administrative requirements with far-reaching impacts on finances, operations, and patients. Additionally, when establishing a centralized prior authorization team is infeasible, expanded prior authorization needs exacerbate the problem of competing priorities for staff tasked with obtaining authorizations amidst other core responsibilities, including patient care.
Prior Authorization Challenges
The impact of today’s challenging prior authorization environment is felt in three key areas: financial, operational, and the patient experience.
On the financial front, the administrative burden of prior authorization has increased steadily over the years, leading to additional costs and workload. Among the most significant financial impacts are higher administrative costs and reduced or lost revenues due to denials, which can be difficult to overturn. The prior authorization process can also delay cash flow.
By Matt Bridge, senior vice president – Strategy and Solutions, AGS Health.
Optimizing financial clearance and other patient access operations is an important aspect of any strategy to offset revenue cycle issues that are behind more than half of all claim denials. Healthcare organizations struggle to do so, however, thanks to staffing and technology limitations that impede efficient operational processes and increase front-end authorization errors.
Those barriers are starting to crumble as artificial intelligence (AI) and automation become more deeply embedded in healthcare revenue cycle management (RCM). Of particular note is the emerging subset of tools designed to streamline and expedite aspects of financial clearance operations, including eligibility and benefits determination and prior authorization processes. Early adopters of these intelligent authorization tools are reporting rapid return on investment (ROI), including 70% to 85% faster eligibility and benefit determination and 85%-90% improvement in authorization determination time.
Also being reported are 65% to 80% less time on authorization initiation and authorization follow-up times that are up to 85% shorter, as well as 80% faster price estimating. The result of these improvements is not only higher revenue growth and employee retention, but an improved overall patient financial experience.
Challenges to Financial Clearance
Operational inefficiencies, outdated technology, and staffing limitations are among the main contributors to rising denial rates, which were up to nearly 12% in the first half of 2022. More than 41% of those denials are the result of front-end RCM issues, including eligibility, authorization, and other financial clearance activities, which also contribute to higher net revenue leakage via avoidable write-offs.
Breakdowns in the financial clearance process can also drive down patient experience scores, with one survey reporting that 93% of patient respondents indicated provider loyalties hinge on their financial experience and more than half said it also impacts their decision to refer a friend or family member. Forty-one percent said they’re unhappy with their overall medical billing experience, with many pointing to a lack of pricing transparency or certainty despite the No Surprises Act mandate to provide them with both.
One cause is the critical shortage of RCM professionals. More than 60% of providers face RCM staff shortages, and nearly half of CFOs and revenue cycle vice presidents from large health systems and physician groups say their labor shortages are severe, with four in 10 reporting vacancy rates between 51%-75%.
The opportunity to resolve these challenges while also eliminating error-prone manual processes from financial clearance is why nearly 80% of healthcare organizations surveyed are turning to AI and automation. Financial clearance and its redundant and time-consuming tasks is a prime candidate for AI and automation, with 42% of respondents to one survey saying their organization would benefit most if eligibility checks and prior authorizations were automated.
By Eric McGuire, senior vice president, Medical Coding and CDI Service Lines and Corporate Strategy, AGS Health.
Traditional fee-for-service reimbursements are falling by the wayside as healthcare continues its transition toward value-based reimbursement models. This is evidenced by data from the Health Care Payment & Learning Action Network (LAN), which shows more than half of healthcare payments in 2022 were made under value-based care models. Additionally, nearly 75% of health plan leaders surveyed by LAN believe value-based care model activity will continue to rise.
Integral to this transition – which requires providers to better manage patient costs based on a clear, concise, and comprehensive picture of patients’ health and medical conditions – are Hierarchical Condition Category (HCC) codes. Used by the Centers for Medicare and Medicaid Services (CMS) and commercial payers to forecast medical costs for patients with more complex healthcare needs, the HCC risk adjustment model measures relative risk due to health status to determine reimbursement levels. The more complex the patient’s medical needs, the higher the provider’s payment.
In fact, HCCs are the preferred method of risk adjustment for the Medicare population, which includes nearly 60 million people on both Part A and Part B, CMS reports. As such, accurate HCC management is critical for appropriate reimbursement of the care provided to Medicare patients and beneficiaries.
Accuracy is Key
The highly complex HCC model includes approximately 10,000 diagnosis codes that map to HCC codes and 189 different HCC categories with 87 CMS-HCCs, each of which represents diagnoses with similar clinical complexity and expected annual costs of care. Any error can significantly impact reimbursements, which under HCC is determined by mapping a patient’s diagnoses to these codes to create a Risk Adjustment Factor (RAF) score.
The RAF score represents the estimated cost of caring for that patient based on their disease burden and demographic information. It is then multiplied by a base rate to set the provider’s per-member-per-month (PMPM) reimbursement amount. The sicker the patient, the higher the RAF score and, subsequently, the provider’s reimbursement.
Each year, CMS publishes a list of diagnosis codes and corresponding HCC category. Hierarchies (or ‘Families’ of categories) are listed among related condition categories, which set values based on the severity of illnesses. Improperly documenting HCC codes, or failing to document the highest appropriate specificity, results in lower reimbursement rates. For example, HCC 19 (diabetes with no complications) might pay an $894.40 premium bonus compared to a bonus of $1,273.60 for diabetes with ESRD, which requires two HCC codes mapping to 18 and 136.
Conversely, properly documenting HCCs at the highest appropriate specificity can boost reimbursements. For example, if CMS has set a $1,000 PMPM for a patient with an RAF of 2.234 who has diabetes with complications reimbursement would be just $673 per month if the condition is not coded. However, if the case was properly coded as E11.9 Type 2 diabetes mellitus without complications under HCC19 Diabetes without complications, the RAF increases to 2.366, resulting in reimbursement of $1,062 per month. If properly coded as E11.41 Type 2 diabetes mellitus w/diabetic mononeuropathy under HCC18 Diabetes w/ chronic complications, the RAF increases to 2.513 for a reimbursement of $1,312.5.
Autonomous coding enjoys a high level of trust among healthcare finance professionals who use or plan to use the technology, with 45 percent indicating it often works well and 16 percent placing complete trust in it. Yet despite its emergence as a powerful tool for streamlining and improving error-prone manual coding processes, autonomous coding suffers from an awareness problem, with 52 percent saying they do not know what it is.
Those are the findings of a new survey from the Healthcare Financial Management Association (HFMA) on behalf of AGS Health, a leading provider of tech-enabled revenue cycle management (RCM) solutions and strategic growth partner to healthcare providers across the U.S. More than 450 healthcare finance professionals were surveyed during the 2023 HFMA Annual Conference on their knowledge of and value expectations for autonomous coding, including 60 percent that use or plan to use autonomous coding.
More than half (52%) of respondents said they don’t know what autonomous coding is and 30 percent either did not or were unsure if it could be trusted.
Thomas Thatapudi
“Despite high expectations around its potential to increase coder productivity and coding accuracy, reduction in denials, missed charges and low-risk scores, and accelerated provider decision-making, autonomous coding suffers from a knowledge gap that must be closed if we are to see broader adoption,” said Thomas Thatapudi, CIO of AGS Health. “Until we can fully educate finance leadership on the potential autonomous coding holds for improving the healthcare revenue cycle, we are unlikely to see an acceleration in use cases for AI-powered technology which includes autonomous coding.”
Among the key benefits of autonomous coding is its ability to eliminate the potential for human errors that result in missed reimbursement opportunities, backlogs, delays, and claims errors, and its ability to push accuracy levels to near perfect percentages. All of which can be achieved in near real time with the right integration pipelines. Autonomous coding is also faster than its human counterparts – it can complete charts in seconds – yet it also understands what it does not know, flagging it for human review.
AGS Health, a leading provider of tech-enabled revenue cycle management (RCM) solutions and strategic growth partner to healthcare providers across the U.S., announced today the release of Intelligent Authorization, a single-source solution that automates and optimizes the financial clearance process and avoids prior authorization-related denials.
Part of AGS Health’s AI Platform, Intelligent Authorization streamlines and expedites processes by up to 90% through a variety of configurable automation solutions that improve operational efficiency, reduce costs, and enhance the patient experience.
“Half of all denials can be traced back to prior authorization and other front-end revenue cycle issues, jeopardizing provider organizations’ financial health and negatively impacting the patient experience by limiting transparency and delaying access to care,” said Matt Bridge, senior vice president of RCM Services, AGS Health. “Intelligent Authorization addresses the underlying issues causing prior authorization-related denials while streamlining and accelerating financial clearance processes. Customers report doubling production volumes and tripling the number of days in advance their patient access teams can secure authorizations, which in turn expedites appointments to better support patient needs and fill open time slots – resulting in improved revenue growth and an enhanced patient financial experience.”
A platform-agnostic solution, Intelligent Authorization prevents denials, reduces aged A/R, improves net revenue reimbursements, and increases clean claim rates across a variety of specialties, including radiology, oncology, occupational and physical therapy, surgery, and infusion/diagnostics. Compared to manual processes, it enhances productivity and reduces the time required for financial clearance activities, delivering:
75%-85% faster eligibility and benefit determinations
85%-90% improvement in authorization determination time
65%-80% less time spent on authorization initiations
75%-85% shorter authorization follow-up times
Up to 80% faster price estimations
Intelligent Authorization achieves these outcomes by automating eligibility and benefits determination processes, including order entries, scheduling, rescheduling, and monthly and annual re-verification processes. It automates authorization status via robotic process automation (RPA) and generates good faith estimates based on the fee schedule and embedded payer- and client-specific rules, which are then transferred back to the EMR.
Finally, Intelligent Authorization offers insightful and actionable analytics including self-service reports, customized dashboards, and flexible data management that enables users to view insights across different dimensions, create action plans, and make decisions faster.
“Smart workflow tools feature fast, flexible data transfers to the EMR through HL7, simplified task management and automated case assignment, and enhanced document management and accessibility, all of which come together in Intelligent Authorization to eliminate financial clearance issues created by error-prone, time-consuming manual processes,” said Suhas Nair, director of product management, AGS Health. “By leveraging the latest advances in RPA and AI technologies, Intelligent Automation helps healthcare organizations implement the tools needed to strengthen their financial footing and better service their patients.”
AGS Health, a leading provider of tech-enabled revenue cycle management (RCM) solutions and strategic growth partner to healthcare providers across the U.S., has been named a Leader in Revenue Cycle Management (RCM) Operations by Everest Group for the third consecutive year.
Everest Group Revenue Cycle Management (RCM) Operations PEAK Matrix Assessment evaluated 25 RCM providers’ market impact and ability to successfully deliver services based on subdimensions, including market adoption, portfolio mix, value delivered, and strategic vision and capability. Results were then used to determine each organization’s overall market leadership position – Aspirant, Major Contender, or Leader.
More information on Everest Group RCM Operations PEAK Matrix Assessment can be found here.
AGS Health is more than a revenue cycle management company – we’re a strategic partner for growth. With expert services complemented by AI-enabled technologies and high-touch support, AGS Health is the premier revenue cycle partner for leading health systems, physician groups, and academic medical centers in the U.S.
With expert insight into modern revenue cycle practices, the company pairs cutting-edge technology with college-educated, trained RCM experts to help clients achieve a high-performance revenue cycle to optimize workflows, maintain compliance, and prevent revenue leakage. AGS Health employs nearly 12,000 team members globally and partners with more than 130 clients across a variety of care settings, specialties, and billing systems.
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