Each year, healthcare providers leave revenue on the table – in fact, if you’re a provider, you probably did so this week. The culprit? Incomplete or inaccurate coding within clinical documentation.
The effects can be significant. The American Academy of Professional Coders (AAPC) estimates that 19% of all E/M services are undercoded – medical practices are short-changing their own efforts. Additionally, about one in four claim denials can be chalked up to coding errors.
This is more than just a billing and reimbursement issue. The downstream effects of insufficient documentation affect quality metrics and, ultimately, the consistency of care delivery. With the latest shifts toward value-based care participation, accurate coding – Hierarchical Condition Categories (HCC), specifically – is more than just an administrative necessity. It’s a strategic imperative.
The Compounded Risk of Insufficient Coding
Proper coding demands accurate clinical documentation. When a patient chart lacks specificity or depth, undercoding can often be the result.
In the fee-for-service world, this can simply mean reimbursement that’s below the appropriate level. But in risk-adjusted models, it can represent missed opportunities to capture the full breadth of HCCs that reflect a patient’s conditions, affecting both revenue and, potentially, care.
In that case, incomplete coding obscures the true illness burden of each patient – and a patient population – making it harder to implement appropriate care plans, track outcomes, and meet quality benchmarks (which determine future reimbursements).
Unfortunately, instances of inaccurate or incomplete coding are not isolated: Medicare reports that practices lost a total of $565 million in Medicare payments in 2023 due to incorrect coding and documentation gaps.
Ambient AI: Changing the Process by Capturing What Matters
Ambient AI offers a solution, right there in the conversation between clinician and patient. By listening to the patient visit and applying AI to chart the full complexity and context of the conversation, ambient technology captures a complete record of patient diagnoses and care.
Healthcare providers so often tell us they’ve had to rely on their memory – sometimes 10-12 hours after an encounter – to properly chart what was discussed with patients. Ambient AI removes that burden, producing a clinical note that “remembers” the entire visit, understanding language, context, and note structure.
With the entire scope of illness and clinical details documented, the medical record naturally supports the appropriate billing codes. The guesswork, estimation, and downstream inquiries are gone. Ambient AI turns a passive administrative task into a powerful driver of clinical and financial accuracy.
Beyond Documentation: Intelligent Coding Recommendations
Leading solutions go a step further by incorporating coding intelligence into the ambient AI platform. Documentation is at the core of the process, but these systems do more than document – they analyze.
As the conversation unfolds, AI can identify the appropriate ICD-10 codes (and organize them accordingly in the note), flag necessary HCCs, and recommend the Evaluation and Management (E/M) code that best matches the visit’s complexity.
This proactive support of all three covers all the bases for healthcare organizations, regardless of their blend of fee-for-service and risk-based reimbursement.
HCC coding is essential for organizations operating under value-based care models, ensuring accurate risk adjustment and appropriate funding. Real-time E/M code suggestions help prevent undercoding, aligning reimbursement with the actual care delivered.
How DeepScribe Integrates Coding Intelligence
DeepScribe’s ambient AI platform includes built-in coding intelligence designed to enhance documentation and ensure coding accuracy:
- ICD-10 code inclusion: Integrates relevant diagnostic codes into the clinical note automatically.
- HCC nudges: Identifies HCC codes that require recapture and prompts clinicians to address those conditions – before and during the visit.
- E/M recommendations: Displays the accurate E/M code based on the recorded complexity and content of the visit.
These capabilities not only lighten the cognitive load for clinicians but directly support financial health and regulatory compliance for their organizations.
Wrap-Up
The power of ambient technology should not stop at documentation. Its true potential lies in augmenting the clinical workflow with intelligence that supports care delivery, compliance, and reimbursement – and it’s why we’ve created The DeepScribe Ambient Operating System.
By embedding AI coding intelligence into the documentation process, ambient AI becomes a strategic asset – advancing medical groups’ quality of care and financial sustainability.
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