Medical Record Abstraction in 2026: How to Abstract EHR Documentation for Accurate Medical Coding

Janine Mothershed CPC, CPC-I

Medical record abstraction is one of the most important skills a medical coder can develop. Before you can assign the correct CPT®, ICD-10-CM, or HCPCS Level II code, you must first understand what happened during the patient encounter.

In 2026, coders often work inside complex electronic health record (EHR) systems filled with progress notes, medication lists, diagnostic reports, operative notes, laboratory results, copied information, and historical diagnoses. Therefore, successful coding requires more than finding a diagnosis or procedure in one section of the chart.

Instead, medical coders must learn how to identify the documentation that matters, separate current conditions from historical information, recognize conflicting details, and determine which services and diagnoses are supported by the record.

This guide explains how to abstract information from an EHR for medical coding, what information coders should look for, common abstraction mistakes, and practical tips for CPC students learning to code real-world medical records.

Key Takeaways

• Medical record abstraction means reviewing a patient’s documentation and extracting the clinical information needed for coding, reporting, reimbursement, and other approved purposes.
• Coders should review the entire relevant record rather than relying only on the problem list, charge ticket, or one note.
• Accurate abstraction requires identifying diagnoses, procedures, dates, laterality, anatomical sites, encounter details, complications, and other information that affects code selection.
• Never assign a diagnosis simply because it appears in the patient’s history or EHR problem list.
• CPT®, ICD-10-CM, and HCPCS Level II codes should always be verified against the appropriate coding resources and guidelines.
• Artificial intelligence and computer-assisted coding tools can help locate information; however, coders still need to validate documentation and code assignment.
• Privacy and security remain essential when working with electronic protected health information (ePHI).
• CPC students should practice abstraction because certification questions and real-world coding cases require them to identify relevant information within clinical documentation.

What Is Medical Record Abstraction?

Medical record abstraction is the process of reviewing a patient’s health record and identifying specific clinical information needed for a defined purpose.

For medical coders, abstraction usually means finding the documentation necessary to assign accurate diagnosis, procedure, and service codes. However, abstraction may also support quality reporting, research, audits, registries, risk adjustment, reimbursement, and healthcare analytics.

For example, an operative report may contain several pages of documentation. Nevertheless, the coder may need to identify a relatively small group of critical details:

• Procedure performed
• Anatomical location
• Laterality
• Surgical approach
• Devices or implants
• Procedures performed in addition to the primary procedure
• Complications
• Diagnosis or reason for surgery
• Provider documentation supporting medical necessity

The goal is not simply to collect as much information as possible. Instead, the coder needs to identify the right information for the coding task.

Why EHR Abstracting Matters in Medical Coding

Accurate codes begin with accurate abstraction.

A coder can understand the ICD-10-CM and CPT® manuals extremely well and still make mistakes if important information gets missed during chart review. Likewise, choosing codes before understanding the complete encounter can lead to unsupported diagnoses, incorrect procedures, sequencing errors, and missed specificity.

In addition, healthcare records have become increasingly complex. One encounter may include information from physicians, nurses, therapists, laboratory systems, radiology systems, medication records, and other sources.

Therefore, coders need a repeatable method for reviewing documentation.

AHIMA emphasizes that healthcare data quality depends on characteristics such as accuracy, completeness, consistency, and timeliness. Those principles also apply directly to the information coders use when abstracting medical records.

What Information Should a Medical Coder Abstract From an EHR?

The exact information depends on the type of encounter. However, coders commonly look for the following elements.

Patient and Encounter Information

First, confirm that you are reviewing the correct patient and encounter.

Look for:

• Date of service
• Place of service
• Type of encounter
• Rendering provider
• Admission and discharge dates when applicable
• Patient status
• Reason for encounter

These details can directly affect coding and billing.

Diagnoses and Conditions

Next, identify the conditions documented as relevant to the encounter.

Pay attention to:

• Confirmed diagnoses
• Signs and symptoms
• Acute versus chronic conditions
• Laterality
• Severity
• Stage
• Complications
• Manifestations
• Associated conditions
• History versus active disease
• Status conditions

Do not automatically code every condition listed somewhere in the EHR.

For example, a diagnosis on the problem list may represent a historical condition that did not affect the current encounter. Consequently, the coder must determine whether the documentation supports reporting it under the applicable coding rules.

Procedures and Services

Coders must also determine exactly what the provider performed.

Important details may include:

• Procedure name
• Anatomical site
• Laterality
• Approach
• Technique
• Number of lesions, units, or services
• Imaging guidance
• Device placement
• Diagnostic versus therapeutic intent
• Separate procedures
• Complications

For surgical cases, the operative report often provides the details needed for accurate CPT® coding.

Medications and Supplies

Medication documentation can also provide important clues. However, medication use alone should not automatically establish a diagnosis.

Depending on the service, review:

• Medication administered
• Dosage
• Route
• Units
• Supply information
• Infusion or injection details
• Start and stop times when relevant

Additionally, HCPCS Level II reporting may require specific information about drugs, biologicals, equipment, or supplies.

How to Abstract a Medical Record Step by Step

A consistent workflow makes abstraction faster and more accurate.

Step 1: Identify the Purpose of the Review

Before reading the chart, know what you are trying to accomplish.

Are you coding a physician office visit? Reviewing an operative report? Coding diagnoses for risk adjustment? Abstracting information for an audit?

The purpose determines which information matters most.

Step 2: Review the Entire Relevant Record

Avoid coding from a single field when additional documentation is available and relevant.

Depending on the encounter, review:

• Chief complaint
• History of present illness
• Past medical history
• Review of systems when relevant
• Examination
• Assessment and plan
• Procedure or operative report
• Laboratory results
• Imaging
• Pathology
• Discharge documentation

Additionally, watch for contradictions between sections.

Step 3: Determine What Happened During the Encounter

Ask yourself:

Why was the patient seen, what conditions were evaluated or treated, and what services were actually performed?

This question helps separate relevant information from background material.

For example, a patient’s chart may list hypertension, diabetes, arthritis, depression, and a previous fracture. However, that does not automatically mean every condition should be coded for every encounter.

Step 4: Identify the Most Specific Documentation

Specificity matters.

Look for documentation such as:

• Right versus left
• Acute versus chronic
• Initial versus subsequent encounter
• Open versus closed
• Type of fracture
• Location of lesion
• Severity
• Stage
• Surgical approach
• Number or size of lesions

Missing one word can sometimes change the code.

Step 5: Separate Current Conditions From History

EHR problem lists can become crowded over time.

Therefore, determine whether a condition is:

• Current
• Historical
• Resolved
• Ruled out
• Suspected
• Being evaluated
• Being treated
• Relevant to the current service

Never assume that an old problem-list entry represents an active diagnosis.

Step 6: Verify Codes in the Coding Resources

After abstracting the clinical information, begin code assignment.

For ICD-10-CM, start with the Alphabetic Index and then verify the selection in the Tabular List. Additionally, review instructional notes, inclusion terms, Excludes notes, laterality, seventh-character requirements, and applicable coding guidelines.

For CPT®, use the CPT® Index as appropriate and verify the code in the main section. Then, review guidelines, parenthetical instructions, symbols, bundling considerations, and modifier requirements.

For more help with this process, read our guide to Medical Coding Correctly Using CPT, ICD-10 & HCPCS.

Step 7: Validate the Final Code Against the Documentation

Finally, return to the medical record.

Ask:

Can I support every code I selected with the documentation in this chart?

If not, investigate before finalizing the claim.

This last check can catch assumptions, specificity errors, and codes carried over from another encounter.

EHR Abstracting and AI in 2026

Artificial intelligence, natural language processing, and computer-assisted coding tools continue to change how healthcare organizations locate and analyze information within electronic records.

These tools may help identify diagnoses, procedures, documentation patterns, or possible codes. Nevertheless, technology does not eliminate the need for trained medical coders.

Coders still need to determine whether documentation supports a code, whether information belongs to the current encounter, and whether coding guidelines permit reporting it.

For example, an automated system may identify a diagnosis because the words appear somewhere in the chart. However, the coder may discover that the condition appears only in past medical history, was ruled out, or does not meet the applicable reporting requirements.

Therefore, treat automated suggestions as information to review—not as automatic coding decisions.

Medical Record Abstraction and Data Quality

Poor abstraction can create poor healthcare data.

When coders extract incomplete or inaccurate information, the effects may extend beyond the claim. Coding data can influence reimbursement, audits, quality measures, research, population health programs, and healthcare analytics.

As a result, accuracy matters throughout the entire process.

Coders should pay particular attention to:

• Completeness
• Accuracy
• Consistency
• Specificity
• Timeliness
• Relevance

Furthermore, discrepancies should be resolved through the organization’s approved processes rather than through assumptions.

HIPAA and Privacy When Abstracting EHR Records

Medical coders routinely work with protected health information. Therefore, privacy and security must remain part of the abstraction workflow.

The HIPAA Security Rule requires regulated entities to use administrative, physical, and technical safeguards to protect electronic protected health information. In addition, HIPAA’s minimum necessary standard generally requires reasonable efforts to limit certain uses, disclosures, and requests for PHI to what is needed for the intended purpose.

Coders should follow employer policies regarding:

• EHR access
• Password security
• Remote access
• Printing records
• Downloading information
• Sharing screenshots
• Storing PHI
• Discussing patient information

Most importantly, never access a medical record simply because you have the technical ability to open it. Access should relate to your authorized job duties.

Example of Medical Record Abstraction

Consider this simplified documentation:

Patient presents with worsening right knee pain due to documented primary osteoarthritis. Conservative treatment has failed. The physician performs a right total knee arthroplasty.

The coder should abstract several important facts:

• Condition: primary osteoarthritis
• Site: knee
• Laterality: right
• Procedure: total knee arthroplasty
• Reason for procedure: documented osteoarthritis
• Treatment status: conservative treatment failed

After reviewing the complete documentation and applicable guidelines, the coder may evaluate M17.11 for unilateral primary osteoarthritis of the right knee and 27447 for total knee arthroplasty.

However, the coder should still verify both codes against the current code sets, documentation, payer rules, and applicable coding instructions before finalizing the claim.

This process demonstrates why abstraction comes before code selection.

Common Mistakes to Avoid When Abstracting Medical Records

Coding Directly From the Problem List

A problem list can help you understand the patient’s history. However, it does not automatically establish that every listed condition should be reported for the current encounter.

Reading Only the Assessment

The assessment may provide diagnoses, but another section may contain information that affects specificity or code selection. Therefore, review all relevant documentation.

Coding From Test Results Alone

Laboratory, pathology, and imaging reports provide valuable information. Nevertheless, coders must follow applicable coding guidelines regarding when findings can support code assignment and who may document specific information.

Assuming Missing Details

Never add laterality, severity, causal relationships, or other details because they seem logical.

Instead, use the documentation and applicable coding guidelines.

Confusing History With Current Disease

A previous myocardial infarction, resolved infection, or past malignancy may require different coding than an active condition.

Consequently, words such as “history of,” “resolved,” “status post,” and “current” matter.

Accepting EHR or AI Suggestions Without Verification

Encoders and AI tools can improve efficiency. However, coders remain responsible for verifying that the final code selection matches the documentation and applicable rules.

Failing to Read Operative Reports Carefully

Procedure titles do not always tell the whole story.

Instead, review the body of the operative report to determine what the surgeon actually performed.

CPC Student Tips for Learning Medical Record Abstraction

If you are preparing for the CPC® exam, do not focus only on memorizing code ranges.

Instead, practice finding the information hidden inside medical documentation.

Start by asking four questions for every case:

1. Why is the patient here?
2. What diagnosis or symptoms are documented?
3. What service or procedure occurred?
4. What details affect code selection?

Next, underline or highlight words that change specificity, such as right, left, acute, chronic, initial, subsequent, open, closed, or specific anatomical locations.

Additionally, practice complete cases rather than isolated code questions. Our 2026 AAPC CPC Certification Guide explains the broader skills needed for CPC certification.

You can also review What Is on the AAPC CPC Exam in 2026? to understand the areas tested on the current exam.

Finally, read How to Excel in Medical Coding in 2026 for additional strategies to improve documentation review, accuracy, and coding confidence.

A Practical EHR Abstraction Checklist

Before completing a chart, ask:

• Did I confirm the correct encounter?
• Did I identify why the patient received care?
• Did I review all relevant documentation?
• Did I distinguish current diagnoses from history?
• Did I capture laterality and anatomical specificity?
• Did I identify the actual procedures performed?
• Did I review applicable coding guidelines?
• Did I verify codes in the proper coding resources?
• Did I avoid making assumptions?
• Does the documentation support every final code?

A repeatable checklist can improve accuracy while also increasing speed over time.

Authoritative Resources for Medical Record Abstraction

Coders should rely on authoritative sources when learning documentation, coding, privacy, and data-quality requirements.

Helpful resources include:

• AAPC for medical coding education, certification, and professional resources.
• Centers for Medicare & Medicaid Services (CMS) for Medicare coding, billing, compliance, and reimbursement guidance.
• AHIMA for health information management, clinical documentation, data integrity, and data-quality resources.
• U.S. Department of Health and Human Services HIPAA Resources for federal HIPAA privacy and security guidance.

These resources are especially important because EHR technology continues to change while coding, privacy, documentation, and compliance requirements remain central to healthcare operations.

Frequently Asked Questions About Medical Record Abstraction

What is medical record abstraction?

Medical record abstraction is the process of reviewing a patient’s health record and extracting specific clinical information for a defined purpose. For medical coding, that generally means identifying diagnoses, procedures, services, and documentation details needed for accurate code assignment.

What is EHR abstracting in medical coding?

EHR abstracting means reviewing information stored in an electronic health record and identifying the documentation relevant to coding. This may include physician notes, operative reports, laboratory results, imaging reports, medications, assessments, and other clinical information.

What information does a medical coder abstract from a chart?

Coders may abstract diagnoses, symptoms, procedures, anatomical sites, laterality, encounter type, severity, complications, devices, medications, and other details. However, the information needed depends on the type of encounter and applicable coding rules.

Is medical record abstraction the same as medical coding?

No. Abstraction and coding are closely connected, but they are not identical. First, the coder abstracts the relevant clinical information from the record. Next, the coder applies coding guidelines and assigns the appropriate CPT®, ICD-10-CM, or HCPCS Level II codes.

Can medical coders code directly from the EHR problem list?

Coders should not automatically report every diagnosis on the problem list. Instead, they must review the relevant documentation and determine whether each condition meets the applicable reporting requirements for that encounter.

Can AI perform medical record abstraction?

AI can help identify information within large electronic records and may suggest diagnoses or codes. However, trained coders still need to validate the documentation, apply coding guidelines, identify context, and determine whether the suggested information supports final code assignment.

How can CPC students get better at abstracting medical records?

Practice complete medical records and case studies rather than relying only on individual code questions. Additionally, learn to identify the reason for the encounter, diagnoses addressed, procedures performed, and documentation details that affect code specificity.

Why is medical record abstraction important in 2026?

Healthcare organizations rely heavily on electronic data for coding, reimbursement, audits, quality programs, analytics, and patient care. Therefore, accurate abstraction helps ensure that the coded information accurately reflects the documentation while supporting compliance and reliable healthcare data.

Final Thoughts

Medical record abstraction is the bridge between clinical documentation and accurate medical coding.

In 2026, coders have access to increasingly sophisticated EHR platforms, encoders, computer-assisted coding systems, and AI tools. However, technology does not change the basic responsibility of the medical coder: understand the documentation, identify the relevant facts, apply the official coding rules, and verify every final code.

Therefore, new coders should practice abstraction as seriously as they practice CPT®, ICD-10-CM, and HCPCS Level II code lookup.

The stronger your abstraction skills become, the easier it is to recognize relevant diagnoses, understand procedures, catch missing documentation, avoid assumptions, and select accurate codes.

Ultimately, excellent medical coding begins before you ever open the code book. It begins with knowing how to read the medical record.