Is Your Organization Ready for Autonomous Medical Coding?

What the Autonomous Coding Readiness Assessment Measures

The assessment looks at eight parts of your coding operation that can influence how smoothly autonomous coding fits into your organization:

• Clinical documentation: Variation in note structure, format, and completeness can show how much preparation may be needed before more encounters can move through autonomous coding.
• EHR environment: The number of EHRs and how standardized they are can affect the integration work required to bring a new coding platform into your organization.
• Coding turnaround: Persistent backlogs and DNFB can point to mid-revenue cycle bottlenecks that slow coding and keep encounters from moving forward. They also show where automation may have the greatest operational impact.
• Coder capacity: Open positions, overtime, and outsourcing can signal that your team needs another way to handle volume without simply adding more manual coding capacity.
• Coding and documentation-related denials: These trends help show whether coding and documentation issues are already affecting revenue and need to be addressed as part of an automation strategy.
• Compliance and auditing: Your current audit and QA processes can show whether you already have the oversight needed for autonomous coding or whether you need to put new processes in place.
• AI readiness: How comfortable your team is with AI when deciding how to introduce it. Some organizations may want coders reviewing AI-generated codes first, while others may be comfortable allowing eligible encounters to move through autonomously.
• Rollout foundations: IT resources, executive sponsorship, clean code sets and data, and defined success metrics indicate whether your organization has the support needed to implement and evaluate a rollout.

Taken together, these factors show both your current readiness and the areas that may need attention before you move further with autonomous coding.

How the Autonomous Coding Readiness Assessment Works

You can complete the assessment in about two minutes.

There’s no data gathering or preparation needed beforehand; just answer based on how your coding operation works today:

1. 1. Answer Questions About Your Current Coding Workflow

   Work through eight questions based on your current coding environment.

   Select the option that best reflects your organization today, including the resources and processes you already have in place.

2. 2. Get Your Readiness Score Across the 8 Factors

   The tool evaluates your responses together to calculate an overall readiness score out of 100.

   You’ll also receive a readiness profile that puts the score into context for your organization.

3. 3. Review Your Personalized Recommendations

   Your results highlight what to focus on next based on your responses.

   This could mean preparing certain parts of your operation for automation or exploring where to introduce autonomous coding first.

What Your Autonomous Coding Readiness Result Means

Your score gives you an overall view of how prepared your organization is for autonomous coding.

The ranges are:

Common Concerns About Autonomous Coding Adoption

Autonomous coding changes how coding work is completed, reviewed, and monitored. However, some teams may be skeptical about adopting an autonomous coding solution.

Here are the four most common concerns:

Can We Trust the Coding Accuracy?

Your team needs a way to evaluate how accurately the technology codes the types of encounters you plan to automate.

Look for a solution that lets you review coding results and measure accuracy before expanding automation. Starting with AI-assisted coding and human review lets coders compare AI-generated codes with their own decisions, identify recurring errors, and improve medical coding accuracy before more encounters move to autonomous coding.

How Much Oversight Will Our Coders Have?

Coding leaders need to know where coders remain involved as more work is automated.

Look for flexibility in how encounters are handled. Some may be appropriate for autonomous coding, while cases that need human judgment should go to coders for review. Your team should also be able to define which encounters require that review.

Will We Be Able to Audit the AI-Generated Codes?

Compliance teams need visibility into how coding decisions were made, not just the final codes.

Look for an audit trail that shows what the AI originally coded, any changes a coder made and why, and subsequent auditor edits. This gives your team a record of what happened throughout the coding process.

What Will Implementation Require From Our Teams?

IT and HIM leaders need to understand what their teams will need to do to bring autonomous coding into the existing workflow.

Consider the integration work involved, the internal resources required, and whether you can introduce the solution in a defined area before a broader rollout. You should also be able to set measures for accuracy, turnaround, and other goals you want to track as automation expands.

How DeliverHealth Supports Your Next Step

DeliverHealth supports coding teams through InstaCode, an autonomous medical coding solution.

With InstaCode, you can choose where AI handles the coding and where your coders stay involved, using AI-assisted, autonomous, human, or hybrid workflows based on the work being coded.

Here’s how our tool can help you:

Why Revenue Cycle Leaders Choose DeliverHealth

Bringing AI into coding requires trust in both the technology and the team responsible for it. We have built our solutions around the needs of healthcare organizations and the teams using them every day.

Here are a few reasons organizations work with DeliverHealth:

• 40,000+ healthcare providers: Our technology supports more than 40,000 healthcare providers, giving us experience with documentation and administrative workflows across a large healthcare user base.
• Built specifically for healthcare: We focus on clinical documentation, medical coding, and other administrative workflows that affect the mid-revenue cycle.
• Advanced AI with healthcare context: We use multiple AI models based on the workflow and partner's needs, including Gemini models through our work with Google Cloud.
• Security built into our technology: We maintain healthcare-focused security and privacy practices. Our eSOne platform, which powers InstaNote, is HITRUST certified.
• Used by healthcare organizations in real workflows: Organizations such as DCH Health System use our technology in their clinical documentation operations, showing how our solutions are being used in healthcare environments today.

When you’re ready to discuss what your assessment result means for your coding operation, schedule a demo, and we'll walk you through your options.

Turn Your Readiness Score Into a Coding Roadmap

Once you know where your organization stands, the next question is what to work on first.

Your readiness profile gives you a more specific next step based on the pattern across your answers:

• Hold for Now: Start by improving documentation consistency, establishing a formal audit process, and defining the metrics you will use to measure coding performance. Get these foundations in place before introducing coding automation.
• Foundation First: Get the documentation you want to code with AI into a more consistent shape. Standardize the note formats and workflows that vary today, then look at where AI-assisted coding can be introduced.
• Augmentation Ready: Put AI-assisted coding to work with coders reviewing the output. Start with one service line or a specific group of encounters, and use what your team sees in the results to decide when more of that work can move to autonomous coding.
• Autonomy Ready: Choose the encounters that can move to autonomous coding and set clear rules for what goes back to a coder. Monitor the coding accuracy, exceptions, and audit results as you add more eligible encounters.

Take the Quiz to Find Your Readiness Stage