Key Takeaways:

• AHIMA 2025 Conference, held from October 12 to 14, gathered the brightest leaders from the healthcare industry to discuss various challenges in healthcare information management.
• Autonomous coding implementation needs frameworks that balance automation with human oversight. Organizations should focus on solutions that maintain 95% accuracy.
• CMS has introduced SDoH/HRSN screening requirements in specific programs (e.g., Hospital IQR) and encourages standardized SDoH capture across quality and innovation models, but it is not universally required for all reimbursements.
• CMS’s July 2025 Interoperability Framework is voluntary. Early adopters of CMS‑Aligned Networks aim to provide FHIR‑based access by July 4, 2026; these are participation criteria, not a universal mandate.
• AI governance prevents black box algorithms. Explainable AI systems with transparent decision-making processes protect organizations from audit exposure while maintaining HIPAA compliance.

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The AHIMA 2025 Conference, held in Minneapolis, Minnesota, from October 12 to 14, brought together thousands of coding professionals, RCM experts, compliance officers, and technology vendors to discuss several pressing issues in Healthcare Information Management (HIM). From autonomous coding to social determinants of health (SDoH) to Artificial Intelligence, the conference highlighted how technology and data governance are reshaping the modern revenue cycle operations.

For healthcare providers, CDI stakeholders, and IT professionals, the AHIMA 2025 conference offered clarity on priorities that directly influence ethics, reimbursement accuracy, and interoperability.

This article highlights the key perspectives shared at the event and how HOM’s services and programs are aligned with AHIMA’s forward-looking vision.

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Autonomous Coding Moves from Theory to Practice

Medical coding automation dominated this year’s AHIMA discussions as healthcare organizations face a nationwide shortage in coders. Austin Ward, Head of Growth at Fathom, shared insights on how the conversation shifted from “whether to adopt autonomous coding” to “how to implement it successfully”

AI-based coding tools can help extract key elements from physician notes, pathology reports, and discharge summaries to assign ICD-10 and CPT codes autonomously. But the healthcare industry still remains cautious around it. Their hesitation has nothing to do with technological capabilities. Organizations want autonomous coding that matches the industry standards of around 95% accuracy. They need systems that can handle complicated cases across multiple specialties. But most importantly, they need technology that supports coding teams, rather than replacing them.

The reality is that autonomous coding changes how coders work – automation handles easy and straightforward cases while coders use their expertise where it matters more.

Experts at AHIMA, however, emphasized that autonomous coding must not sacrifice accuracy or compliance. AI tools should function within a framework to ensure continuous auditability, clinical validation, and monitoring from certified Healthcare Information professionals.

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Social Determinants of Health (SDoH) Documentation Gains Priority

Another major focal point of AHIMA 2025 Conference was SDoH, which affects 80% of health outcomes. Lauren Montwill, Vice President of Community Health & Social Impact at UnitedHealth Group, shared perspectives on the five key domains - food insecurity, transportation access, housing instability, economic stability, and interpersonal safety. The conference emphasized that SDoH data collection has evolved from optional screening to a program-specific requirement, with CMS integrating SDoH/HRSN screening into initiatives like Hospital IQR and various quality and innovation models.

Montwill and other speakers stressed that social factors impact patient outcomes more than clinical interventions alone. Therefore, they highlighted the need to integrate SDoH data into electronic health records (EHR) and analytics frameworks to support risk adjustment, population health management, and clinical workflows.

However, Mary Grady, VP of CDI Acquity, pointed out that the major challenge is capturing these factors in structured, codable formats and understanding which screening tools meet CMS requirements precisely. It requires training clinical staff on documentation standards and workflows that don’t burden already busy providers.

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Interoperability Framework Creates New Expectations

The Trump Administration announced a new Interoperability Framework in July 2025. This voluntary framework establishes participation criteria for early adopters of CMS-Aligned Networks, with a goal to eliminate redundant data entry and improve patient access to health information through standardized, FHIR-based data exchange.

AHIMA 2025 sessions explored what this voluntary framework means practically for health information professionals. Susan Houck Clark, VP of Interoperability Strategy at Converge Health, discussed FHIR (Fast Healthcare Interoperability Resources) standards, implementation of compliant APIs that support data exchanges, and the importance of semantic alignment for organizations choosing to participate in CMS-Aligned Networks.

The HHS Office for Civil Rights has cracked down on HIPAA right of access violations. The Office of the National Coordinator for Health IT announced new efforts to enforce prohibitions on information blocking. While the CMS Interoperability Framework is voluntary, these existing HIPAA and information blocking regulations remain mandatory, ensuring organizations review data-sharing practices and fulfill patient access requests promptly.

For revenue cycle management, better interoperability means faster prior authorizations and fewer claim denials. When clinical data move seamlessly between systems, coding accuracy improves, and payers get complete information upfront, which reduces back-and-forth delays and missing documentation requests.

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AI Requires Governance and Human Oversight

Artificial Intelligence in healthcare was part of many of AHIMA 2025 discussions, particularly ambient documentation tools and coding assistance. The message from conference speakers was clear and consistent – AI should complement human expertise. Not replace it.

Experts warned against adopting AI models that function as “black boxes” where the decision-making process remains opaque and unauditable. Instead, they recommended ‘explainable AI (XAI)’, tools that make the decision-making process transparent and auditable. AHIMA also emphasized that AI in healthcare must be used under stringent data governance and compliance regulations, particularly those of HIPAA standards and Protected Health Information.

Health Information professionals play an oversight role in AI implementation. They validate that AI suggestions align with clinical reality and coding guidelines. They monitor for bias that might influence specific patient segments unreasonably. For CDI programs, AI improves efficiency when properly governed - automated chart reviews help identify improvement opportunities across entire patient populations, while predictive models prioritize which charts need specialist attention.

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The Future of HIM and How HOM Aligns with AHIMA 2025

The one consistent message throughout AHIMA 2025 was that the HIM profession is undergoing an enormous change. No longer chained to managing records, HIM leaders are becoming strategic data stewards today, guiding how healthcare information kindles payments, policies, and patient outcomes.

The excellent convergence of artificial Intelligence, analytics, and interoperability means that the next generation of HIM professionals must be skilled and certified in data interpretation, governance, and automation oversight.

HOM empowers healthcare organizations, clinicians, and payers to strive beyond traditional RCM and documentation management toward data-driven operational Intelligence.

Our workflows are structured around AHIMA’s Information Governance and Documentation Integrity principles. And our RCM ecosystem mirrors AHIMA’s emphasis on precision, ease of accessibility, and highly secure and encrypted health information. We measure information quality using AHIMA-aligned metrics, i.e., timeliness, completeness, and accuracy. In addition, all data handling practices follow AHIMA’s Privacy and Security Principles alongside U.S. HIPAA requirements.

With eight years of experience across 15+ medical specialties, HOM has reviewed millions of charts with 99% coding accuracy. Our 48-72 hour coding turnaround time helps organizations meet coding deadlines without sacrificing quality.

To know more about how we can help, book a free audit of your operations.

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FAQs

1. What is AHIMA, and why does it matter for healthcare providers?

AHIMA is the American Health Information Management Association’s annual conference that gathers industry leaders to discuss innovations in Healthcare Information Management (HIM). For providers, it’s a guide to where healthcare operations and compliance are heading.

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2. What is explainable AI and why does it matter?

Explainable AI (XAI) are AI-tools that clearly show how and why they made a particular decision or prediction. In healthcare, this transparency is absolutely critical because AI often influences financial, treatment, and operational decisions. XAI prevents ‘black box’ situations and makes detecting errors more efficient.

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3. Why is SDoH documentation important for reimbursement? 

Centers for Medicare & Medicaid Services (CMS) has introduced SDoH screening requirements for specific programs including Hospital IQR and Annual Wellness Visits, and encourages health-related social needs (HRSN) capture across various quality reporting and innovation models. While not universally required across all reimbursements, these screenings are increasingly integrated into value-based care programs.