How to Separate Coding Errors From Documentation Deficiencies
When a claim is questioned, denied, or flagged during an audit, the immediate assumption is often that the coder made a mistake.
That assumption can be misleading.
A coding problem and a documentation deficiency are related, but they are not the same problem. A coder may select the wrong code even when the medical record clearly supports the correct one. Conversely, a coder may select an apparently reasonable code because the provider's documentation does not contain enough information to support a more specific or accurate code.
That distinction matters because the corrective action is different.
Coding errors require a coding correction. Documentation deficiencies require improvement in the clinical record.
The American Medical Association (AMA) describes CPT as the standardized language used to report medical services and emphasizes that codes should accurately describe the services performed. CMS likewise instructs providers to ensure that medical-record documentation supports the CPT, HCPCS, and ICD-10-CM codes reported on claims.
Understanding where the problem originated can make audits more useful, reduce recurring errors, and prevent practices from addressing the wrong part of the revenue cycle.
1. The Fundamental Difference
The simplest way to distinguish the two is to ask:
Does the record contain enough accurate information to support the code that should have been reported?
If yes, but the wrong code was submitted, the issue is primarily a coding error.
If no, and the record does not adequately establish the service, diagnosis, level, or other required elements, the issue may be a documentation deficiency.
There is also a third possibility:
The documentation and coding may both require correction.
This is why an effective audit should evaluate the clinical record before assigning responsibility.
2. What Is a Coding Error?
A coding error occurs when the available documentation supports a particular code or coding approach, but the submitted claim does not accurately reflect it.
Examples can include:
Incorrect CPT code selection
Incorrect ICD-10-CM code selection
Incorrect modifier
Incorrect number of units
Incorrect place of service
Incorrect sequencing
Failure to apply an applicable coding guideline
The key characteristic is that the information needed to make the correct coding decision is already present.
Example
The medical record clearly documents a particular service and all relevant coding elements.
The coder selects a different CPT code that does not accurately describe the documented service.
That is primarily a coding issue.
The documentation did not prevent correct coding; the coding decision did.
3. What Is a Documentation Deficiency?
A documentation deficiency occurs when the clinical record does not adequately describe the patient's condition, services provided, or other information necessary to support accurate coding and reporting.
Examples can include:
Missing clinical details
Incomplete assessment
Unclear diagnosis
Missing procedure details
Insufficient documentation of medical decision making
Missing information needed to distinguish between code choices
Conflicting information within the record
Here, the coder may not have enough reliable information to select a more specific or different code.
CMS specifically states that medical-record documentation should support the CPT, HCPCS, and ICD-10-CM codes reported on the claim. CMS also notes that medical necessity is a principal criterion for payment in addition to the applicable code requirements.
4. Why the Distinction Matters During an Audit
Consider two claims with the same incorrect code.
Claim A
The provider documented everything necessary, but the coder selected the wrong code.
Primary issue: Coding error.
Corrective action: Coding education, review, or workflow correction.
Claim B
The provider's note did not contain enough information to establish the appropriate code.
Primary issue: Documentation deficiency.
Corrective action: Provider documentation education or a compliant clarification process, where appropriate.
Treating both cases as "coder error" would fail to address the underlying problem.
5. A Practical Audit Framework
When reviewing a potentially incorrect claim, work through the following sequence.
Step 1: Review the Submitted Code
Identify:
CPT/HCPCS code
ICD-10-CM code
Modifiers
Units
Place of service
Other relevant claim elements
Step 2: Read the Supporting Documentation
Do not review only the portion of the note that appears relevant to the disputed code.
Consider the complete available record and determine what the provider actually documented.
Step 3: Compare Documentation With the Code
Ask:
Does the record support the submitted code?
If yes, the code may be appropriate.
If no, determine why.
Step 4: Determine Whether the Correct Information Exists Elsewhere
Sometimes the required information is documented in another part of the record.
For example:
Assessment and plan
Procedure note
Medication record
Relevant test result
Other contemporaneous clinical documentation
A coder should not assume that information is missing simply because it is not located in one section of the note.
Step 5: Identify the Root Cause
Classify the finding as:
Coding error
Documentation deficiency
Both
Unable to determine from the available record
That final category is important. Audits should distinguish uncertainty from a confirmed error.
6. Common Coding Errors
Wrong CPT Selection
The documented service is clear, but the submitted CPT does not accurately represent it.
Incorrect Modifier
The record supports use of a modifier, but it was:
Omitted
Incorrectly selected
Applied to the wrong service
Incorrect Units
The documentation supports a particular number of units, but the claim reports a different quantity.
Incorrect Diagnosis Code
The provider clearly documents a diagnosis, but the submitted ICD-10-CM code does not accurately represent the documented condition.
Incorrect Sequencing
The diagnoses or services may be documented correctly, but the claim sequencing does not follow the applicable coding requirements.
7. Common Documentation Deficiencies
Diagnosis Is Not Clearly Established
The record may contain symptoms or clinical findings without a sufficiently clear provider diagnostic statement.
AHIMA notes that diagnosis coding is based on the provider's diagnostic statement and emphasizes the importance of distinguishing clinical documentation from other information contained within the health record.
Required Service Details Are Missing
A procedure may be documented, but important elements needed for accurate reporting may be absent.
Medical Decision Making Is Insufficiently Supported
For E/M services where MDM is the basis for code selection, the record needs to support the relevant MDM elements.
The AMA's current E/M guidance describes the three MDM elements as:
Number and complexity of problems addressed
Amount and complexity of data reviewed and analyzed
Risk of complications and/or morbidity or mortality of patient management
Documentation Is Contradictory
Different portions of the record may describe the condition or service differently.
Contradictions should be resolved through an appropriate clarification process rather than silently choosing whichever information supports a preferred code.
8. E/M Coding Is a Good Example of Why the Distinction Matters
E/M services demonstrate how coding and documentation can become intertwined.
The AMA's E/M revisions eliminated history and physical examination as elements determining the level of office/outpatient E/M service. For most office or other outpatient E/M visits, the level is selected using either medical decision making or total time, depending on the applicable CPT guidance.
That means an audit should not automatically conclude:
"The history is short, therefore the E/M code is incorrect."
Instead, the reviewer should ask:
What method was used for code selection?
If MDM was used, does the documentation support the relevant MDM elements?
If time was used, is the required time documentation present?
Was the correct CPT guideline applied?
This illustrates an important point:
Auditing a code without understanding the rule used to select it can produce the wrong conclusion.
9. Do Not Confuse Missing Documentation With Unsupported Coding
There is an important difference between:
"The provider did not document the service."
and
"The coder did not identify the documentation that supports the service."
Before labeling a claim as a documentation deficiency, the reviewer should examine the complete available record.
AHIMA's guidance emphasizes that documentation integrity involves ensuring that the health record accurately represents the patient's clinical status and that coding professionals should work within a structured documentation-validation process.
10. What About Provider Queries?
When documentation is incomplete, unclear, or conflicting, a compliant query process may sometimes be appropriate.
However, a query should be used to clarify the clinical record, not to manufacture documentation that supports a desired code.
This distinction has become particularly relevant with the increasing use of automated and AI-assisted coding tools.
In its September 2026 update, AHIMA reported that AI-generated prompts, EHR alerts, and computer-assisted coding tools can identify potential documentation gaps before a human reviewer examines the record. AHIMA and ACDIS emphasize that these workflows still need to follow compliant query principles.
Technology can identify a question.
It should not determine the clinical answer.
11. AI Makes Root-Cause Classification Even More Important
AI and computer-assisted coding systems are increasingly being used to identify potential coding and documentation issues.
That can improve audit coverage, but it also creates a new risk:
A system may identify that something looks wrong without identifying why it is wrong.
AHIMA has specifically noted that errors may originate from flawed documentation, inefficient workflows, or information being located in the wrong part of the record—not necessarily from coder incompetence.
Therefore, automated audit alerts should be treated as review triggers, not final conclusions.
12. A Simple Decision Tree for Auditors
When an audit identifies a questionable claim, use this sequence:
Question 1:
Is the service documented?
No → Potential documentation deficiency
Yes → Continue
Question 2:
Does the documentation contain the information needed for code selection?
No → Potential documentation deficiency
Yes → Continue
Question 3:
Was the appropriate coding guideline applied?
No → Coding error
Yes → Continue
Question 4:
Does the submitted code accurately represent the documented service?
No → Coding error
Yes → Code may be appropriate
Question 5:
Is documentation conflicting or clinically unclear?
Yes → Consider appropriate clarification/query process
No → Finalize audit finding
This approach helps prevent the common mistake of assigning every billing discrepancy to the coding department.
13. Match the Corrective Action to the Root Cause
Finding | Primary Issue | Appropriate Response |
Wrong CPT selected despite clear documentation | Coding | Coding review/education |
Wrong modifier despite supporting record | Coding | Coding workflow correction |
Required clinical detail absent | Documentation | Provider documentation education |
Conflicting clinical information | Documentation/clinical clarity | Appropriate clarification process |
Correct documentation exists but was overlooked | Workflow/coding | Improve record review process |
Code and documentation both inconsistent | Both | Address both processes |
Insufficient information to determine cause | Undetermined | Additional review |
The goal is not simply to find an error.
The goal is to prevent the same error from recurring.
14. Track Audit Findings by Root Cause
Instead of maintaining a single category called "coding errors," practices can divide findings into:
Coding selection
Modifier
Diagnosis coding
Documentation completeness
Documentation clarity
Medical necessity support
Charge capture
Workflow
Payer-specific issue
System configuration
T
his produces more useful management information.
For example, if 70% of findings relate to incomplete documentation rather than incorrect coding, additional coder training alone is unlikely to solve the problem.
15. What High-Quality Audits Should Measure
A mature audit program can monitor:
Coding Accuracy
How frequently are submitted codes supported and correctly selected?
Documentation Sufficiency
How frequently does documentation contain the information needed for accurate reporting?
Root-Cause Distribution
Are problems primarily associated with coding, documentation, workflow, or other factors?
Repeat Findings
Are the same errors recurring after corrective action?
Financial Impact
What revenue is being delayed, denied, underpaid, or placed at risk?
Education Effectiveness
Do targeted interventions reduce recurrence?
AHIMA's CDI leadership resources recommend using audit findings to develop action plans and then monitoring implementation and impact through appropriate metrics and KPIs.
16. A Better Way to Think About Coding Audits
A coding audit should not simply ask:
"Was the code correct?"
It should ask:
What was documented?
What should have been reported based on that documentation and the applicable rules?
What was actually reported?
Where did the discrepancy originate?
What process change would prevent recurrence?
That framework shifts the audit from fault-finding to process improvement.
It also creates a clearer relationship between coding, clinical documentation, compliance, and revenue cycle management.
Conclusion
Coding errors and documentation deficiencies can produce similar outcomes—denials, payment delays, audit findings, and revenue risk—but they require different solutions.
A coding error generally means the available documentation was sufficient, but the coding decision was incorrect.
A documentation deficiency means the record itself does not adequately support accurate coding or reporting.
The distinction becomes particularly important as healthcare organizations adopt more automated coding and documentation-review technologies. The AMA continues to update CPT guidance, while AHIMA is actively addressing compliant documentation-query practices in an environment where AI and automated tools increasingly identify potential gaps.
For medical practices, the most effective audit is therefore not one that simply produces a list of mistakes.
It is one that identifies where the mistake originated, why it occurred, and what needs to change to prevent it from recurring.
That is how a coding audit becomes a revenue-cycle improvement tool rather than simply a compliance exercise.
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