Clinical documentation integrity

Navigating outpatient best practices, part 2: How AI-powered workflows drive appropriate documentation accuracy and reimbursement

In the second installment of our series on navigating the shifting healthcare reimbursement landscape, we explore why Hierarchical Condition Categories (HCCs) in the outpatient care setting matter, why timing is everything, and how AI helps organizations drive clinical documentation excellence.

Risk-Adjusted Factor (RAF) scores were reset on January 1. It’s a massive task, requiring outpatient clinics across the nation to review patient charts to ensure Hierarchical Condition Categories (HCCs) are correctly documented for each patient. But, with an AI-first approach to clinical documentation integrity, it needn’t be.

In the previous article in this series, we looked at how and why the reimbursement landscape is shifting. This time, we’ll dive into the challenges health systems face to ensure appropriate reimbursement in the new world of value-based care. We’ll explore why it’s vital that organizations act now to protect next year’s revenue—and how AI can help make it much easier.

Why do HCCs matter?

One of the ongoing impacts of the COVID-19 pandemic is the downward pressure on healthcare organizations’ margins. With very little room to maneuver on profitability, it’s important that organizations are properly reimbursed for the care they provide. As we continue toward risk-adjusted reimbursement models, documenting HCCs accurately—for every patient, every year—is fundamental to a health systems’ ability to generate enough revenue to remain profitable.

Effective capture and recapture of HCCs, and detailed clinical documentation on how patient conditions are being addressed, are essential, and complex tasks.

For example, simply documenting that a patient has diabetes isn’t adequate. Is their diabetes type 1 or type 2? Is it controlled or uncontrolled? Is it progressing and affecting other systems? How is it being treated? The answers to all these questions must be documented to produce the correct HCC code and accurately assess patient risk.

Timing is everything

HCC codes for each patient’s chronic conditions are used to create a RAF score. These scores are then aggregated to assess the average risk of managed populations, and determine reimbursement for the following year.

RAF scores reset to zero every calendar year, so if HCCs aren’t documented in time, organizations must wait an entire year to see the appropriate reimbursement. If organizations can document diagnoses and how they’re managing chronic conditions earlier in the year, it can have a significant impact on reimbursement—and eliminate the end-of-year rush to sift through massive volumes of unstructured data in patient charts.

AI improves clinical documentation integrity—and ensures appropriate reimbursement

Using manual methods, it’s difficult for outpatient clinics to accurately track multiple chronic conditions, identify intervention opportunities, and illuminate risk factors. With HCC definitions constantly changing, expecting clinicians to keep up with all the latest coding standards is a tough ask.

Computer-assisted physician documentation (CAPD) tools allow AI to do the heavy lifting of analyzing the vast quantities of patient data. Using analytical insights, these tools can provide relevant in-workflow guidance to help physicians improve documentation, add diagnosis specificity, and document HCCs efficiently and accurately.

By using AI to build a foundation for clinical documentation excellence, organizations gain a broader view of each patient, helping outpatient clinics identify risks and intervention opportunities,

capture and recapture HCCs, and increase RAF scores.

AI-powered CAPD tools help organizations drive appropriate reimbursement by:

  • Analyzing historical data to discover undocumented and unspecified diagnoses
  • Offering guidance and prompts to help physicians identify intervention opportunities and risk factors
  • Prioritizing information to help physicians focus on the right opportunities at the right time
  • Providing automated coding assistance to make it simple to document the correct HCC codes at the point-of-care
  • Identifying areas for improvement in HCC capture and opportunities for proactive patient outreach

Next time

In the final article in this series, we’ll share insights and advice from an expert panel on how AI supports clinical documentation excellence. Until then, explore our outpatient CAPD resources to see how you can improve reimbursement and patient care.

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Mike Jones

About Mike Jones

Mike Jones is the GM of the Clinical Quality and Integrity LOB, focused on expanding and delivering outcomes and growth for Nuance's clients in these areas.