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Beyond the Margin Squeeze: How Specialty Providers Use RCM Automation to Combat Rising Costs

by Teri Schmidt, VP of Consulting and Business Development at SYNERGEN Health 12/12/2025 Leave a Comment

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Teri Schmidt, VP of Consulting and Business Development at SYNERGEN Health

Despite a recent uptick in margins, providers continue to face significant pressure on their revenue cycles as a result of potential reimbursement cuts, workforce recruitment challenges, and higher costs. 

Providers in 2024 reported operating margins of 1.2%, up from -0.5% the prior year, according to a report from Fitch. Nonetheless, margins remain “well below” pre-pandemic levels, and looming federal cuts to Medicaid funding could be devastating for some providers.

Federal reductions in Medicaid reimbursement and a rise in uncompensated care are straining financial stability, particularly those serving a high proportion of Medicaid patients. These fiscal pressures may compel providers to downsize services, close facilities, or lay off staff, according to Fitch.

Separately, providers continue to get crushed by soaring labor costs, as total compensation and related expenses now account for 56% of total hospital costs, according to the American Hospital Association (AHA). To cite just one staggering data point: advertised salaries for registered nurses have grown 26.6% faster than the rate of inflation over the past four years, the AHA reported.

While much of the broader media attention is focused on hospitals’ financial challenges, specialty care providers – such as radiology, behavioral health, and surgical specialties – are not immune from this pressure. To overcome the unique operational and billing issues they face, many specialty providers are adopting intelligent revenue cycle management (RCM) automation tools that are tailored to their specialties to streamline staff workflows and improve patient financial experience. 

Why specialty providers are different
Specialty healthcare providers face distinct RCM challenges that differ significantly from those encountered by hospitals and primary care providers. While hospitals often operate with centralized billing systems and standardized workflows, specialty providers must navigate complex payor/reimbursement challenges with minimal resources.  

Radiology practices, for instance, contend with intricate billing requirements due to the diversity of imaging modalities and the necessity for precise coding. The use of specific CPT and ICD-10 codes, along with appropriate modifiers, is essential to preventing denials and underpayments. Additionally, many radiology services require prior authorization, especially for advanced imaging procedures, making this step crucial to avoid delays in treatment and disruptions to patient care. 

Behavioral health providers face their own set of RCM complexities. The billing process must accommodate various services, including individual therapy sessions, group treatments, and crisis interventions, each with distinct coding and documentation requirements. Further, navigating intricate payer requirements and prior authorizations adds another layer of potential complication and can lead to significant delays in reimbursement and collections.

Orthopedic practices, deal with the manual nature of pre-authorizations, correct coding and use of modifiers, and the need for accurate documentation of unique specialized procedures. These factors can result in denials and delays in collections, significantly reducing a practice’s financial health. 

Overall, tailored RCM solutions that streamline these unique processes are crucial for optimizing revenue across specialty practices.

How automation benefits RCM
Automation technologies such as robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) are revolutionizing RCM by streamlining tasks, reducing errors, and enhancing financial performance. In the initial stages of the revenue cycle, RPA automates eligibility checks and insurance verifications, minimizing manual data entry and expediting patient intake processes. 

AI and ML algorithms analyze patient data to predict coverage issues and flag potential discrepancies before claims are submitted, thereby reducing the likelihood of denials. NLP extracts pertinent information from unstructured data sources, such as clinical notes and insurance documents, ensuring accurate and efficient data capture. 

In the claims management phase, automation tools are employed to monitor claim statuses and facilitate timely follow-ups. RPA can navigate payer portals and retrieve claim information, reducing the need for manual intervention. AI-driven systems prioritize claims based on factors like reimbursement potential and aging, enabling staff to focus on high-impact tasks. ML models learn from historical data to predict claim outcomes and suggest optimal follow-up strategies, enhancing the efficiency of the claims process. 

Denial management also benefits significantly from the integration of AI and ML technologies. These tools analyze denial patterns, identify root causes, and recommend corrective actions to prevent future occurrences. Automated systems can generate appeal letters using NLP, extracting relevant information to support the appeal process. By automating these tasks, organizations can reduce the time and resources spent on managing denials, leading to improved cash flow and reduced accounts receivable days. 

Finally, in the payment reconciliation stage, automation ensures accurate and timely posting of payments. RPA handles repetitive tasks such as matching payments to corresponding claims and updating financial records. AI algorithms detect anomalies in payment patterns, flagging potential issues for further investigation. This level of automation not only enhances accuracy but also frees staff to focus on more strategic financial tasks.

A need for customized solutions
Specialty providers need RCM tools that conform to their workflows and are customized to their specific operational and clinical needs. Across different types of specialty providers, the diversity in billing structures, prior authorization demands, clinical documentation dependencies, and payer-specific nuances require unique and specialized RCM strategies. By adopting advanced technologies such as AI, ML, and RPA, in addition to specialty-tailored solutions, specialty providers can leverage automation not just as an efficiency tool — but as a strategic enabler of growth, agility, and better patient financial experiences.


About Teri Schmidt

Teri Schmidt, MBA, CPC, is the vice president of consulting & business development at SYNERGEN Health. She brings more than 30 years of experience in the healthcare industry as a practice administrator, operational leader, and revenue cycle optimization consultant to large laboratories, health systems, and physician organizations. Her extensive hands-on knowledge of end-to-end revenue cycle processes gives her the ability to identify workflow redesign and overall performance improvement opportunities with an eye toward financial improvement and increased efficiency.

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