By Ritesh Ramesh, CEO, MDaudit
LinkedIn:Â Ritesh R.
LinkedIn: MDaudit
Healthcare finance executives face an intensifying storm of audits, denials, and clawbacks that threaten their organization’s financial stability. Couple that with an environment of heightened regulatory and payer scrutiny, and it becomes clear that proactive risk monitoring and AI-driven compliance strategies are no longer optional—they are imperative.
Aggressive Action
An internal analysis of over $8 billion in audited professional and hospital claims and over $150 billion in denials collected from over 650,000 providers and more than 2,200 facilities identified surging audit volumes and claim denials in the past year. Our annual benchmark report documented that audit volumes more than doubled over 2023 rates while total at-risk dollars increased fivefold to $11.2 million, straining provider organization cash flows.
Payer scrutiny, particularly in Medicare Advantage (MA) plans, is also at an all-time high, with HCC and RADV audits increasing by 72% and total MA denials climbing by 51%. Coding-related denials increased by 126%, representing one of the most significant increases in the last three years. Denials surged across care settings; hospital inpatient-related denials were up nearly 220% to $10,000 per claim, hospital outpatient by 32.5% to $825, and professional by 24% to $140.
While the data makes it clear that coding integrity is one of the biggest revenue optimization opportunities, medical necessity also urgently needs improvement. The MDaudit analysis revealed a 140% increase in total denial amounts for inpatients and a 75% increase in outpatient amounts related to the “Medical Necessity and Information Needed” category. Overall, more claims dollars were denied in 2024 by Medicare and commercial payers due to a lack of information submitted for the service and medical necessity, driving an increase in final denial dollars across professional (34%), hospital outpatient (84%), and hospital inpatient (148%),
The driving factor behind these increases was a doubling of external audit volumes, including higher pre-payment audit volumes, which exacerbated provider cash flow issues and increased overall denial rates.
Fraud prevention also raises pressure. According to the US Department of Health and Human Services (HHS) Office of the Inspector General (OIG) Health Care Fraud and Abuse Control Program Report for Fiscal Year (FY) 2023, released in December 2024, federal recovery efforts targeted $4.7 billion in projected overpayments within MA alone, a figure expected to rise as the Centers for Medicare and Medicaid Services (CMS) ramps up fraud prevention.
In FY 2023, civil healthcare fraud settlements and judgments under the False Claims Act exceeded $1.8 billion, bringing the total amount returned to the federal government or paid to private individuals to more than $3.4 billion. That figure includes $974 million that was returned to the Medicare Trust Funds and $257.2 million in federal Medicaid money transferred separately to the CMS.
Reshaping Today’s Strategy
These data trends tell the story of a shift toward more aggressive pre-payment audits, an intensified focus on fraud, and lengthening reimbursement delays. They highlight the need for an equally aggressive revenue strategy that prioritizes revenue optimization and risk mitigation.
AI, automation, and other technology tools that enable continuous monitoring of real-time financial risk based on payer trends and denial management are foundational elements of a transformative revenue cycle strategy. These solutions offer a significant return on investment (ROI) and introduce automated workflows that drive operating margins.
Focusing on audit response is also essential for enhancing revenue capture, particularly when provider organizations struggle with RCM staffing shortages and payer organizations increasingly rely on pre-payment audits to lengthen the reimbursement window and increase denial rates. Investing in AI, machine learning (ML), and automation tools that deliver intelligent functionality to automate and accelerate the management of external payer audits ensures the timely processing of additional documentation requests (ADRs), improving audit defense outcomes and revenue retention.
Generative AI and natural language processing (NLP) solutions further optimize audit outcomes. They allow finance leaders to unlock insights and patterns from their historical data by increasing accessibility and democratizing that information across the revenue cycle. Specifically, generative AI tools that take natural language questions and instantly compute complex formulas to return clear, concise, and actionable responses boost human productivity and deliver speed-to-value. They eliminate information silos between revenue integrity and executive teams and transform how they interact with data to make more innovative and strategic decisions.
Transforming Revenue and RCM
Strong internal compliance programs and a cross-functional operating model that connect the dots between billing, coding, CDI, and revenue integrity will advance a unified revenue retention and growth agenda. Leveraging data and insights as a storytelling mechanism enhances program value by removing bias and injecting objectivity into discussions and decision-making while establishing success metrics introduces accountability for tangible outcomes.
With the core strategy in place, finance executives can look to other targets for RCM transformation to enable healthy operating margins, such as high-value outpatient services like elective surgeries and some inpatient services. Along with scrutinizing complex services, other opportunities to
improve revenue retention include implementing clinical documentation improvement (CDI) programs that drive outcomes tied to RCM and denial management metrics.
CDI, billing, coding, and RCM programs can also be tightly coupled to implement a closed feedback loop from the backend to the mid-cycle to drive efficiencies. Finally, automate coding operations and increase utilization of AI-powered systems that amplify errors at scale while keeping “humans in the loop.”
Deploying technologies that bridge mid-cycle and back-end functions will drive more substantial margins and cash flow while mitigating risks tied to payer-driven policies and denials. An aggressive AI-enabled, data-driven, and people-led approach to the revenue cycle allows forward-looking finance leaders to position their organizations for financial survival in today’s high-risk landscape.