Tag: AGS Health

ICD-10’s Subtle Updates May Create Big Coding Risks

Leigh Poland

By Leigh Poland, RHIA, CCS, CDIP, CIC, is Vice President – Coding Services, Clinical Quality, and Education, AGS Health

The latest ICD-10 update may look insignificant to many healthcare organizations. There are no sweeping diagnosis code additions, no major guideline rewrites, and no dramatic restructuring of the classification system at first glance.

That perception could become a costly mistake.

The April 2026 ICD-10 changes introduced by the Centers for Medicare & Medicaid Services (CMS) and the National Center for Health Statistics (NCHS) are deceptively quiet. While the diagnosis code set itself remains largely untouched, the update alters something far more consequential: the decision-making framework coders use to determine sequencing, coexistence, and classification relationships. In practical terms, the update shifts more responsibility onto coder judgment, documentation precision, and organizational oversight.

For health systems already navigating staffing shortages, denials pressure, increasing payer scrutiny, and growing dependence on encoder technology, even modest classification logic changes can create operational instability.

The Real Change Is Not the Codes

The 2026 ICD-10-CM release includes no additions, deletions, or revisions to diagnosis codes. The Official Coding Guidelines also remain unchanged. But focusing only on code counts overlooks where the actual disruption is occurring.

The most meaningful changes involve instructional notes, exclusions, and indexing logic embedded within the classification system itself. These structural revisions alter how diagnoses relate to one another and how coders determine sequencing priorities.

Historically, ICD-10 relied heavily on embedded hierarchy through directives such as “code first” and “use additional code.” Those instructions created relatively rigid sequencing expectations. The April update softens several of those relationships by replacing them with “code also.”

That wording change appears minor. Operationally, it is not.

“Code also” removes automatic sequencing hierarchy and places greater emphasis on the clinical circumstances of the encounter. As a result, two experienced coders reviewing similar documentation may now reasonably arrive at different sequencing conclusions.

That variability introduces downstream risk for MS-DRG assignment, reimbursement consistency, quality reporting, and audit exposure.

Hypertensive Emergency Becomes a Judgment Call

One of the clearest examples appears in category I16.1 for hypertensive emergency.

Previous instructional language reinforced sequencing expectations around the hypertensive crisis itself. Under the revised structure, coders must now determine whether the hypertensive emergency or the associated complication represents the principal reason for admission.

In real-world inpatient settings, that distinction can materially alter reimbursement outcomes.

If the case emphasis shifts toward complications such as acute kidney injury, myocardial infarction, encephalopathy, heart failure, or cerebral infarction, the resulting DRG assignment may change significantly.

What was previously more standardized now becomes more interpretive.

For revenue integrity teams, this creates a new challenge: ensuring consistent organizational logic across coding staff, CDI specialists, and auditing functions.

Expanded Coding Combinations Increase Complexity

Another major change involves the conversion of multiple Excludes1 notes to Excludes2 notes. Within ICD-10 methodology, this distinction matters enormously.

Excludes1 notes prohibit reporting two conditions together because they are considered mutually exclusive. Excludes2 notes acknowledge that conditions may coexist when clinically appropriate.

The April revisions expand the number of valid diagnosis combinations across several clinical areas, including hematologic disorders, respiratory failure, and substance-related conditions.

That expansion creates both opportunity and risk.

On one hand, organizations may now capture clinical complexity more accurately. On the other, newly permissible combinations may attract increased payer attention if documentation does not clearly establish coexistence and medical necessity.

Respiratory failure coding illustrates the issue well.

The revision affecting postprocedural respiratory failure now allows certain respiratory failure conditions to be reported concurrently when documentation supports both diagnoses. Depending on sequencing and present-on-admission indicators, these changes can influence CC/MCC assignment and case severity calculations.

Increased flexibility sounds beneficial until organizations realize it also increases variation.

Technology Alone Will Not Solve This

Many organizations assume encoder systems will absorb these changes automatically. That assumption deserves caution. Encoder logic can support compliance, but it cannot fully resolve interpretive ambiguity introduced by structural classification changes. When sequencing hierarchy is loosened, technology becomes more dependent on human documentation quality and coder judgment.

This is particularly important as hospitals continue expanding the use of AI-assisted coding workflows.

Automation performs best in environments with stable and predictable rules. The more classification systems rely on nuance, contextual interpretation, and clinical prioritization, the more critical human oversight becomes.

The April ICD-10 update quietly reinforces that reality.

Healthcare organizations increasingly pursuing autonomous coding strategies may find that classification logic changes expose gaps in governance, validation, and audit readiness.

Procedure Coding Continues Tracking Clinical Innovation

While the diagnosis side of the update focuses on logic restructuring, ICD-10-PCS continues expanding to capture emerging procedural complexity. New codes support advancements in cardiac pacing technologies, including conduction system pacing techniques involving ventricular septal lead placement.

Additional updates improve specificity for hepatobiliary and pancreatic drainage procedures by distinguishing transpapillary and transmural approaches commonly used in advanced endoscopy.

The update also expands reporting capabilities for reconstructive urologic procedures, rehabilitation therapies, electrotherapeutic modalities, and new technology interventions involving biologics, vascular scaffolds, gene therapies, and immunotherapies.

These additions reflect a continuing challenge for healthcare organizations: clinical innovation is moving faster than many operational infrastructures can adapt.

Coding specificity requirements continue increasing, increasing provider documentation burden..

Why This Matters Beyond Coding Departments

The significance of this update extends beyond HIM and coding operations. Sequencing variability influences reimbursement predictability. Documentation inconsistency affects denial vulnerability. Coding interpretation impacts publicly reported quality measures and risk adjustment performance.

In other words, structural coding logic changes eventually become enterprise financial and operational issues.

Organizations that dismiss this release because it lacks major code volume changes may underestimate its cumulative effect over time.

The healthcare industry often focuses attention on large regulatory overhauls while overlooking smaller classification refinements that quietly reshape operational behavior. This update falls squarely into that category.

The Organizations Most Likely to Struggle

The greatest risk may not come from the coding changes themselves but from uneven organizational response.

Health systems with mature auditing programs, strong CDI integration, and consistent coding governance will likely adapt relatively quickly.

Organizations with fragmented workflows, inconsistent education practices, or overreliance on automated coding recommendations may experience wider variability in coding outcomes.

The most immediate priorities should include:

The danger is not a dramatic overnight disruption. It is the gradual accumulation of inconsistencies across thousands of encounters.

A Quiet Update With Long-Term Consequences

The April 2026 ICD-10 revision is a reminder that healthcare reimbursement systems do not need sweeping reform to create operational consequences.

Sometimes the most impactful changes are the least visible.

By loosening embedded sequencing hierarchy, expanding allowable diagnosis relationships, and increasing procedural specificity, the update subtly changes how coding decisions are made across the enterprise.

That shift places greater pressure on judgment, governance, and the integrity of documentation at a time when healthcare organizations are already balancing financial strain and operational complexity. The organizations that recognize the significance early will be better positioned to maintain coding consistency, compliance stability, and reimbursement accuracy.

Those who treat this as a routine update may discover the real impact only after denials, audits, and DRG variation begin to surface.

AGS Health Introduces Agentic Digital Workforce Solutions to Tackle Rising Claim Denials and Margin Pressures

Healthcare providers are under unprecedented strain from rising claim denials, staffing shortages, and mounting margin pressures. To help meet these challenges, AGS Health, a leading provider of tech-enabled RCM solutions and a strategic growth partner to healthcare providers across the U.S., has introduced a new suite of agentic digital workforce solutions powered by AI agents and intelligent automation.

“Labor-intensive processes, fragmented RCM ecosystems, and continuously shifting payer rules have put healthcare finance leaders at a disadvantage,” said Patrice Wolfe, CEO of AGS Health. “CFOs are now dealing with alarming denial trends and significant financial threats that demand new strategies led by a collaborative digital RCM workforce built for scalability and engineered for impact. Through agentic AI, AGS Health empowers healthcare leaders with digital agents that work alongside their teams, taking on autonomous tasks and recommending data-driven next steps to improve decision-making.”

Market Pressures Driving Urgent Change

Lower reimbursements and denials are cited by 84% of health system leaders as the top drivers of declining margins. With global healthcare RCM software and services spending projected to grow from $42.6 billion in 2024 to $65.7 billion by 2031, investment in automation is accelerating. According to a recent Black Book Research survey, within the first six months of adopting AI-powered RCM solutions:

A New Class of Digital RCM Workforce

“AGS Health is answering the call for change with AI agents that level the playing field for overburdened RCM teams,” said Thomas Thatapudi, CIO of AGS Health. “Our next-generation, AI-infused workforce solutions bring speed, agility, accuracy, and human-like decision-making to critical RCM functions such as eligibility verification, prior authorizations, denials management, and appeals.”

AGS Health was recently recognized with a UiPath AI25 Award for its pioneering use of agentic AI to help healthcare organizations reduce the financial impact of denials. Its digital workforce features AI agents that understand natural language, adapt to changing rules and workflows, and make autonomous decisions to drive measurable business outcomes, including fewer denials and higher clean claim rates.

Key benefits include:

The Hybrid Intelligence Advantage

While AI systems can act autonomously, RCM professionals remain central to a successful digital workforce model. Skilled specialists help train and refine the AI, driving strategy while maintaining oversight and accountability.

“Our hybrid intelligence model combines AI’s speed, accuracy, and scalability with human expertise and empathy,” added Thatapudi. “AI agents manage high-volume tasks while professionals handle exceptions and guide continuous improvement. This can be achieved in-house domestically or through our globally distributed workforce model to reduce operating costs and allow for 24/7 production schedules.”

By preparing work, surfacing insights, and managing exceptions, AGS Health’s AI agents empower RCM teams to make smarter, faster decisions without compromising quality.

For more information on AI agents and digital workforce solutions from AGS Health, visit https://www.agshealth.com/ai-platform/ai-agents-and-intelligent-automation/.

Agentic AI: A Smarter Path Forward for Healthcare Revenue Cycle Leaders

Emily Bonham

By Emily Bonham, senior vice president of product management, AGS Health.

In healthcare revenue cycle management (RCM), we’ve long relied on automation systems that process rules-based workflows with limited or no need for complex logic and nuanced judgement. Robotic Process Automation (RPA) has been highly effective at automating repetitive, high-volume tasks such as claim status checks and data entry.

However, its limitations are increasingly apparent. Today’s revenue cycle challenges demand more than just speed and efficiency; they require adaptability, context, and intelligent decision-making.

That’s where agentic AI comes in.

Agentic AI represents a next-generation approach to automation—one that mimics how humans think, make decisions, and interact with systems and people. Unlike RPA, which follows strict, predefined scripts, agentic AI models operate as autonomous agents. They’re context-aware, goal-oriented, and capable of reasoning across complex workflows. For revenue cycle teams under pressure from rising denials, staffing shortages, and shrinking margins, this kind of intelligence isn’t just nice to have—it’s becoming essential.

What Makes Agentic AI Different?

The simplest way to explain agentic AI is to compare it to a seasoned team member—one who not only knows how to complete a task but also when to escalate, adapt, or reprioritize based on changing circumstances. Agentic systems can:

In practical terms, this means AI can now triage claims, initiate and complete payer calls, route work dynamically, or even autonomously document and code encounters—all with logic and consistency.

Why This Matters for RCM

Healthcare RCM is a perfect candidate for agentic automation because it sits at the intersection of structure and unpredictability. Processes are highly regulated, but real-world conditions vary constantly. Consider these examples:

These aren’t distant possibilities—they’re already being piloted and implemented in real-world environments.

The Human + Agentic AI Model

It’s important to note that agentic AI is not about replacing people—it’s about augmenting them. The most effective models combine human oversight with AI execution:

This hybrid approach doesn’t just improve throughput; it also enhances job satisfaction for teams that no longer spend their days on tedious follow-ups or simple reconciliations.

Getting Started with Agentic AI

For organizations beginning to explore this space, here are a few guiding steps:

  1. Consolidate and clean your data: Fragmented data across EHRs, billing systems, and vendor platforms limits AI effectiveness. Start by creating interoperable, governed data environments.
  2. Identify high-ROI use cases: Look for repeatable processes with moderate complexity and clear financial upside, like denial prediction, prior authorization automation, or A/R follow-ups.
  3. Experiment with short feedback loops: Choose pilots where you can quickly assess ROI and adjust based on results. Don’t aim for perfection—aim for momentum.
  4. Build trust through transparency: Ensure your AI systems are auditable and explainable, especially when financial decisions are being made autonomously.

A Path to Sustainable Margins

Every healthcare leader is being asked to do more with less: deliver care, navigate compliance, and protect financial performance. Those who lead with tech-forward cultures by embracing intelligent automation and prioritizing data cleanliness in their revenue cycle operations are well-positioned to rise to the occasion. In contrast, those who resist innovation due to skepticism or overly protective and risk-averse policies risk falling behind—exposing their financial performance to volatility and long-term disruption.

Agentic AI offers a path forward, not as a magic bullet, but as a powerful tool for reclaiming time, improving accuracy, and aligning resources where they have the most impact.

It’s still early days for agentic AI in healthcare RCM, but the direction is clear. With the right balance of vision and pragmatism, revenue cycle leaders can unlock a new level of operational intelligence and move closer to sustainable, value-driven performance.

 

An Automated Solution to Healthcare’s $125 Billion Fax Problem

By Thomas Thatapudi, CIO, AGS Health

In 2018, the head of the Centers for Medicare and Medicaid Services issued a challenge to health IT developers and providers alike to “help make every doctor’s office in America a fax-free zone by 2020.”

The challenge was issued out of frustration with a vital workflow that remains reliant on outdated fax technology. Each year, healthcare providers exchange over 9 billion fax pages, driving an estimated $125 billion in costs across the healthcare system.

The continued reliance on fax technology is a persistent challenge for healthcare, undermining data integrity and operational efficiency. Studies by DirectTrust reveal alarming statistics: 30% of tests must be re-ordered due to lost faxes, and 25% fail to arrive on time for patient visits. Additionally, integrating faxes into health systems often demands manual indexing—an expensive and time-intensive task many organizations can ill afford.

Fortunately, automation offers a solution. Machine Learning and Generative AI are particularly adept at handling repetitive tasks such as fax indexing. While achieving perfect accuracy from the outset is unlikely, pairing AI-driven Digital Workers with human oversight ensures exceptions are managed effectively. Over time, as AI systems learn and adapt, they can assume more complex responsibilities.

To succeed, this model requires a carefully designed workflow that balances human expertise with AI capabilities to meet quality, timeliness, and accuracy standards.

Building the Digital Workforce

A successful hybrid fax indexing strategy relies on a carefully designed digital workflow model that effectively coordinates efforts between human staff and Digital Workers. The process begins with identifying the necessary technologies, which is best accomplished by observing human indexers to gain a comprehensive understanding of their workflows and unique requirements. This insight informs both implementation planning and feasibility testing.

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RCM In Transition: Key Trends to Watch in 2025

By Ryan Chapin, executive director of strategic solutions, and Vijaya Krishna Veeravalli, senior vice president of cloud engineering, AGS Health.

Ryan chapin

As we head into 2025, several key trends are expected to significantly shape the future of healthcare revenue cycle management (RCM). From managing surging denial rates and evolving workforce dynamics to mitigating rising cybersecurity risks and integrating cutting-edge technologies, healthcare organizations are entering the new year while navigating a complex—often contentious—environment to enhance patient care and operational efficiency.

Navigating an Adverse RCM Environment

Denials, evolving payer relationships, and greater administrative burdens have come together to create what may best be described as an adverse RCM environment for healthcare organizations.

Climbing denial rates, prior authorization requirements, and the costs associated with managing both are among the most significant challenges confronting healthcare organizations going into 2025. According to an American Medical Association (AMA) survey, physicians reported spending nearly two business days per week completing an average of 43 prior authorizations—many of which end in denial.

Vijaya Krishna Veeravalli

In terms of denials, the surge is driven in large part by the growth in commercial and government third-party audits, including an increase in the volume of prepayment audits. According to MDaudit, external audit volume more than doubled between 2023 and 2024 and total at-risk dollars increased fivefold. The result was a sharp uptick in final denial dollars across professional (34%), hospital outpatient (84%), and hospital inpatient (148%) settings.

Healthcare providers participating in increasingly popular Medicare Advantage (MA) plans have been especially hard-hit. MDaudit reports that MA-related denials increased by 59% on average across professional and hospital settings in 2024, and the total denials amount for MA plans rose by 51%—a trend that has a growing number of providers reconsidering or dropping participation based on high denial rates and poor payments.

The impact of these trends goes deeper than financial. They add to already high administrative demands that in turn increase the strain on an overburdened—and increasingly costly—workforce that RCM leaders struggle to shore up in a tough recruitment and retention environment. To avoid staff burnout, healthcare leaders are continuing to adapt strategically, including exploring onshore, nearshore, and offshore outsourcing models.

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AGS Health’s Fax Automation Solution Honored by UiPath with AI25 Award

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 Intelligent Fax 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.

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AI Advances Bring RCM To an Inflection Point

Thomas Thatapudi

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.

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Alleviating the Prior Authorization Headache  

Matt Bridge

By Matt Bridge and Ryan Chapin of AGS Health 

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. 

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