E/M-Code-Sense AI:
User Guide & Best Practices
Welcome to the E/M-Code-Sense AI. Powered by advanced artificial intelligence and strictly adhering to the most current AMA Evaluation and Management (E/M) guidelines, this tool acts as your on-demand, personal coding auditor. Our algorithms are continuously updated to reflect the most current guidance for E/M coding and documentation.
This guide will help you understand how to use the tool, interpret your results, and get the most accurate codes possible.
How to Use the Tool
Select Your Encounter Type
Before pasting any text, select the correct Encounter Type from the dropdown menu (e.g., Established Office Patient, Initial Hospital Care, Emergency Department).
The AI uses this selection to determine the correct baseline rules. For example, it knows that Emergency Department visits cannot be billed by time, and it will apply the correct code sets (e.g., 99281-99285) based on your selection.
Enter Total Time
Enter the total time (in minutes) spent on the patient on the date of the encounter. This includes both face-to-face and non-face-to-face time.
The AI evaluates both Time and Medical Decision Making (MDM) simultaneously. By entering your total time, the AI will automatically calculate and recommend whichever method results in the highest justified level of care.
Paste Your Clinical Note
Paste your raw clinical documentation into the text area. You do not need to format the text perfectly. You can paste your entire note, just the HPI and Assessment/Plan, or even type a quick summary.
Analyze
Click the “Analyze Encounter” button. The AI will process your documentation in seconds, calculating both Total Time and Medical Decision Making (MDM) complexity to determine the mathematically optimal code.
Understanding Your Results
Once the analysis is complete, you will receive a detailed breakdown categorized into four distinct sections:
1. The Result & Financials
The AI will present the highest justified CPT code. It states whether this code was selected based on Time, MDM, or Both. It also provides estimated 2026 Medicare Reimbursement and national utilization percentages for context.
2. Audit Risk Flags
The AI acts as your compliance shield, aggressively cross-referencing your documentation against your selected encounter type.
3. Prevent Inadvertent Undercoding
Optimize reimbursement by preventing inadvertent undercoding. The AI calculates exactly how close you are to the next billing tier (CDI) based on your documentation.
4. EHR Coding Rationale
A perfectly formatted, audit-defensible justification for your code, ready for a patient’s chart.
Privacy, Security & HIPAA
We take data privacy seriously. The E/M-Code-Sense AI features a powerful Pre-Flight PHI Scrubber driven by an advanced AI model.
When you click “Analyze,” the tool instantly evaluates your text using the HIPAA Safe Harbor method to identify and scrub Protected Health Information (PHI). Before any data is processed for coding analysis, the following information is automatically redacted and replaced with placeholders:
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✓ Patient Names[REDACTED NAME]
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✓ Social Security Numbers[REDACTED SSN]
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✓ DOBs & Exact Dates[REDACTED DATE]
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✓ Phone / Fax Numbers[REDACTED PHONE]
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✓ Email Addresses[REDACTED EMAIL]
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✓ Medical Record Numbers[REDACTED MRN]
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✓ Physical Addresses[REDACTED ADDRESS]
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✓ Health Plan / Acct #s[REDACTED ACCT]
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✓ Device IDs & IPs[REDACTED DEVICE]
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✓ Geographic ZIP Codes[REDACTED ZIP]
Important User Responsibility
While our automated scrubber catches standard numerical PHI, it cannot always accurately distinguish between a highly unique patient’s name and a standard medical term. Please do not paste Patient Names, actual Medical Record Numbers (MRNs), or specific physical addresses into the text box.
Pro Tips for the Best AI Results
To get the most accurate E/M code, ensure your pasted text contains the specific details the AMA guidelines require:
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Be Specific with Tests
Instead of saying "ordered labs," say "ordered CBC, CMP, and Lipid panel." The AI needs to count unique tests to score your Data complexity.
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State Your Interpretations
If you looked at an X-ray yourself, state "independently reviewed and interpreted CXR."
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Include Time Statements
If you want the AI to consider Time as a billing factor, explicitly state your total time.
(e.g., "Total time spent on the date of the encounter was 45 minutes, including face-to-face and charting.") -
Identify External Discussions
If you spoke with another physician, note it.
(e.g., "Discussed case management with Dr. Smith in Cardiology.")