THANK YOU FOR SUBSCRIBING
Weekly Brief
Be first to read the latest tech news, Industry Leader's Insights, and CIO interviews of medium and large enterprises exclusively from Healthcare Tech Outlook
Julien Dubuis, Chief Commercial Officer, NymRevenue cycle management, historically viewed as an administrative task, is quickly becoming a key strategic function for health systems. Medical coding departments are playing a key role in this shift, as they sit at the center of what gets billed, how quickly, and whether it holds up to payer or regulatory audits. However, workforce shortages, increasing regulatory complexity, razor-thin operating margins, and rising patient volumes have made medical coding more challenging than ever. As coding becomes increasingly strategic, organizations are seeking solutions that scale with their teams while reinforcing transparency, trust, and operational confidence.
How does autonomous medical coding address workforce shortages and operational pressure in health systems
Nym, a leader in autonomous medical coding, has developed a solution that positions within this shift by applying medical codes to patient encounters and routing them directly to billing with speed, accuracy, and no human intervention. Built with configurability in mind and powered by Clinical Language Understanding (CLU) technology, its autonomous medical coding engine addresses real operational pressures while empowering coding teams to focus on higher-value, strategic work within modern revenue cycle environments.
"The purpose of our solution is to reduce the administrative burden faced by medical coders and set those same teams up for growth and stability," says Julien Dubuis, Nym’s Chief Commercial Officer.
Building Trust through Configurability and Transparency
Redefining Coding Teams
Why are configurability and transparency critical when deploying automation in revenue cycle operations
Nym’s autonomous coding engine is designed to meet the compliance, clinical nuance, and financial performance standards that define modern revenue cycle operations. Recognizing that automation must align closely with existing workflows, the company prioritizes configurability during implementation, ensuring each deployment reflects customer-specific coding guidelines, operational processes, and compliance requirements. By mirroring established practices while introducing automation, Nym enables health systems to unlock increased efficiency and accuracy without sacrificing visibility or control, reinforcing confidence as encounters move directly from documentation to billing.
Explainability is equally central. Each encounter coded by Nym’s engine includes a detailed audit trail that outlines the logic behind assigned codes, supporting compliance discussions with payers and regulators. By eliminating the perception of a black box, health systems gain clarity into how clinical narratives are interpreted and translated into billable outcomes. For revenue cycle leaders, this level of transparency strengthens trust while maintaining accountability.
-
The purpose of our solution is to reduce the administrative burden faced by medical coders and set those same teams up for growth and stability.
Redefining Coding Teams
How does clinical language understanding enable fully autonomous coding across diverse medical specialties
Nym’s approach centers on building a comprehensive clinical narrative for each encounter, enabling accurate coding decisions without requiring manual validation. Achieving this level of automation requires deep clinical language understanding that builds a complete narrative for each encounter, capturing who performed specific actions, when they occurred, and how clinical context informs coding decisions. This foundation has enabled the platform to expand across specialties, including emergency medicine, radiology, outpatient visits, and outpatient surgery, while maintaining high accuracy.
The company’s solution reshapes workforce dynamics by automatically processing a large share of encounters, allowing coding professionals to focus on more nuanced cases, higher-acuity specialties, and coding-adjacent functions (e.g., auditing, revenue integrity). By aligning automation with real-world workflows, Nym’s autonomous coding engine supports a shift toward more strategic roles within coding teams while helping reduce operational strain and persistent backlogs.
At Inova, a top U.S. health system, Nym’s engine helped reduce weekly DNFB backlog by 50%, generated significant annual cost savings, and increased charges per encounter after implementation in the health system’s emergency departments. Similar operational improvements were seen at Genesis Healthcare System, where workflows became more streamlined and coders no longer needed to shift between specialties after Nym’s engine was implemented constantly.
As revenue cycle operations continue to evolve into strategic drivers of organizational performance, autonomous coding becomes a foundational capability for modern healthcare systems. By combining true automation with configurability and explainability, Nym aligns technology with the operational realities of compliance, workforce transformation, and financial precision.
Building Trust in Autonomous Medical Coding Systems
Revenue cycle leaders face mounting strain. Patient volumes continue to rise while experienced coders retire faster than they can be replaced. Departments rely on contract labor to manage backlogs, often at escalating cost. Regulatory updates and payer scrutiny add layers of complexity that demand precision, documentation, and defensible decisions. Beneath these structural pressures is a human one: coders working extended hours, handling routine encounters that underutilize their expertise, and absorbing the stress of delayed claims and compliance risk.
Automation has long promised relief, yet skepticism persists. Coding errors carry financial and regulatory consequences, and few executives are willing to route encounters directly to billing without confidence in how decisions are made. Any credible autonomous medical coding solution must address two realities at once: it must demonstrate accuracy at scale and it must earn trust from compliance teams, coding managers and finance leadership.
Trust begins with alignment to existing coding practices. Health systems operate under specific guidelines, payer rules, and internal policies that shape how encounters are coded. A solution that cannot be configured to reflect those standards will struggle to gain adoption. Leaders should expect technology that adapts to their workflows rather than forcing wholesale process change. Implementation should involve a detailed review of coding guidelines, documentation patterns, and specialty nuances so that the system reflects current practice while improving coding throughput.
Transparency is equally central. Black box outputs may accelerate code assignment, yet they undermine confidence during audits. Executives should look for systems that generate a clear audit trail for each coded encounter, documenting the clinical reasoning and guideline citations behind every assigned code. Explainability shifts compliance conversations from defensive to informed. When payers question claims, organizations need immediate access to traceable logic rather than retrospective reconstruction.
True autonomy also distinguishes mature platforms from assistive tools. Many vendors describe automation as AI while still requiring human validation before billing. That model may reduce keystrokes but does not resolve staffing shortages or persistent backlogs. An advanced solution should move encounters from documentation directly to billing for a defined portion of cases without human intervention. Achieving that level of autonomy depends on constructing a complete clinical narrative for each case, capturing what was done, by whom and under what conditions, then mapping it accurately across code sets.
Executives evaluating the market should probe coverage across specialties and work types, confirm the percentage of encounters that can be routed to billing without human review and examine documented results across multiple health systems. They should also assess the implementation lift. Platforms that demand years of historical data or extended validation periods can delay value and perpetuate workload pressure.
NYM describes its platform as a fully autonomous coding engine designed to move from documentation to billing without routine human validation. It emphasizes configurable deployment tailored to each health system’s guidelines and produces a detailed audit trail for every coded encounter, supporting transparency and compliance. Its clinical language understanding technology constructs comprehensive encounter narratives that support code assignment. This enables direct billing at scale while maintaining high reported accuracy. Case examples such as a large emergency department reporting reduced backlogs and measurable financial impact illustrate how automation can shift coders toward complex cases, auditing and revenue integrity rather than repetitive encounters. For organizations aiming to modernize revenue cycle performance while maintaining compliance integrity, NYM stands out as a disciplined, autonomous solution grounded in configurability, explainability and demonstrable results.
...Read more
Company
Nym
Management
Julien Dubuis, Chief Commercial Officer, Nym
Description
Nym develops autonomous medical coding technology that converts clinical documentation directly into medical codes without human intervention. Built on configurable workflows and explainable clinical language understanding, it helps health systems improve revenue cycle performance, enhance compliance transparency, reduce operational burden, and enable coding teams to focus on complexity and strategic responsibilities.
