10 Medical Coding Mistakes That Could Cost You

1. Inaccurate Medical Necessity Determination

One of the most important steps in medical coding is determining if a service or procedure was medically necessary. Medical necessity directly impacts reimbursement and coverage. Failure to accurately assess necessity can lead to improper code selection, claim denial, and allegations of fraud.

Be sure to review the entire medical record and follow payer policies to justify necessity. Obtain physician confirmation if documentation is unclear. Code non-covered services correctly to avoid rejected claims or false claim submission.

2. Missing Required Code Modifiers

Code modifiers provide extra detail to convey specific circumstances about a procedure. Modifiers are required in certain situations to maximize reimbursement or avoid claim denials. For example, using modifier -25 with an E/M code tells payers it was a separately identifiable service from another procedure done the same day.

Refer to payer guidelines regularly for correct modifier usage. Omitting modifiers when required can lead to improper payments and compliance risks. Double check modifiers before claim submission.

3. Incorrect Code Linking and Unbundling

Medical policies often bundle services together under a single code to maximize reimbursement. Splitting or “unbundling” the codes is prohibited. For example, coding for insertion and removal of a catheter as two separate procedures instead of using the bundled code.

Likewise, some codes must be linked together per policy rules. Failing to link codes properly can lead to denials or allegations of unbundling fraud. Thoroughly review all National Correct Coding Initiatives (NCCI) edits before coding complex cases.

4. Inaccurate Diagnosis Code Selection

Choosing the most specific ICD diagnosis code to reflect the documented condition is critical for accurate coding. Payers require the highest level of specificity to justify medical necessity and determine benefits.

Incomplete physician documentation and complex code subsets can lead to inaccurate code selection. For example, coding unspecified chest pain (R07.9) rather than acute myocardial infarction (I21.3). Get physician clarification to assign the right code.

5. Inconsistent Code Assignment

Code selection should be standardized across an organization and reflect proper compliance guidelines. Inconsistent code selection can make benchmarking difficult and lead to incorrect payments.

Provide regular training and coding resources to staff. Perform internal audits to identify coding variation. Get multiple coder reviews for complex cases. Develop facility coding guidelines.

6. Inappropriate Use of “Not Otherwise Specified” Codes

Assigning NOS (not otherwise specified) codes should be limited to cases with inadequate documentation to assign a more specific code. Overusing NOS codes when more detail is available can shortchange reimbursement and mask quality data.

Always seek clarification from physicians to obtain details to code to the highest specificity possible. Develop policies on proper use of NOS codes. Educate physicians on needed documentation.

7. Missing Present on Admission (POA) Indicators

Failure to properly assign present on admission (POA) indicators for hospital inpatient diagnosis codes can lead to improper payment adjustments and inaccurate quality data.

Make sure POA guidelines are followed consistently. Use correct POA indicators when coding from initial admission notes before all results are known. Audit POA designations and obtain physician confirmation if unsure when a condition started.

8. Incorrect E/M Service Level Selection

Choosing the wrong evaluation and management (E/M) service level can lead to overpayment, underpayment, audits, or fraud allegations. Payers scrutinize E/M coding for over-billing.

Use proper E/M coding guidelines and documentation rules to support your code selection. Do not automatically default to high-level codes without reviewing the record. Get ongoing E/M coding training. Audit documentation and coding accuracy.

9. Missing Code Specificity for Quality Reporting

Data specificity is critical for accurate quality measurement. Vague coding can skew quality results and undermine initiatives aimed at improving outcomes.

Seeking clarification to pinpoint diagnoses demonstrates a commitment to data integrity. Develop protocols to review documentation and optimize code selection for quality data. Partner with physicians to improve documentation.

10. Outdated Coding Practices

Coding guidelines and payer policies change frequently. Using outdated coding conventions and assumptions can lead to improper reimbursement and compliance issues.

Regularly review coding updates from major payers, CMS, AMA, and AHIMA. Attend continuing education workshops on changing coding practices. Modify internal protocols to align with current standards and directives.

Following best practices can help avoid common pitfalls:

• Improve documentation specificity. Partnering with physicians to improve documentation leads to more accurate code selection and higher reimbursement. Provide education on needed details, regular feedback, and tools to streamline documentation.
• Perform internal auditing. Regular coding audits using clinical validation can identify problem areas before external audits. Review a sample of records across all coding staff to improve consistency. Share feedback and additional training opportunities.
• Stay up-to-date on medical policies and coding. Coding is a dynamic field requiring ongoing continuing education. Dedicate time every week for coders to review latest guidelines and brush up on standards. Renew credentials on schedule.
• Address coding variation. Get a second opinion from lead coders on complex cases. Have monthly coding discussions to review difficult cases as a team. Reach consensus for standardized practices.
• Enhance clinical knowledge. Coding accuracy hinges on understanding clinical care in addition to coding conventions. Build this knowledge through case review, clinician shadowing, and cross-training.
• Leverage coding technology. Encoder software with updated edits and automated prisoner validation reduce mistakes and oversight. Computer-assisted coding uses AI to boost coder productivity and accuracy.
• Audit proactively. Perform regular internal audits and risk analysis across specialties to proactively address problem areas. External audits should hold no major surprises.
  

Below outlines potential consequences that underscore the importance of avoiding coding mistakes:

• Payment delays and claim denials – Incorrect coding often triggers payer scrutiny and slowed payments or rejected claims. Resubmission and appeal processes drain staff time and delay revenue.
• Underpayment – Vague, inaccurate codes shortchange reimbursement levels relative to the care provided. Underpayment represents lost revenue from proper reimbursement.
• Overpayment/false claims – Payers can recoup overpayments identified from audits. Intentional overbilling can be construed as fraudulent claims subject to fines under the False Claims Act.
• Contract termination – Health plans can end provider network contracts when fraudulent billing or excessive error rates are suspected as a breach of agreement.
• Fines and penalties – Regulators impose civil monetary penalties and sanctions based on the level of billing and compliance errors. Substantial fines into the millions can result from upcoding and falsified billing.
• Program exclusion – Repeated violations may lead to temporary or permanent exclusion from federal health programs like Medicare and Medicaid. This severe action limits a provider’s access to patients and revenue.
• Reputation damage – Coding noncompliance that reaches settlement or court judgements generates negative publicity and reputational damage. Patients may lose trust in providers exposed for fraud.
• Increased scrutiny and audits – Providers with high denial rates, billing variance, and suspected noncompliance face increased scrutiny and external audits. More audits consume added staff time and resources.
• Loss of quality data – Inaccurate coding skews key quality metrics, preventing robust analysis of clinical outcomes and population health management.
• Staff turnover – Coding staff may become disengaged and seek new jobs when trabal environments are overly stressful from constant claim denials and external auditing.
  

Improving coding quality requires an organizational commitment to best practices:

• Provide ongoing education – Support coding staff with sufficient continuing education, current reference materials, encoders and ample training tools. Stress the importance of accuracy.
• Enable collaboration – Foster culture of collaboration so coding staff can discuss challenging cases. Develop standardized facility policies to drive consistency.
• Conduct peer audits – Perform regular peer audits to identify variations and opportunities for improvement in a supportive way. Share results during group discussions.
• Review denials – Analyze reasons for claim denials to find problem areas and educate coders. Denials signal coding gaps.
• Validate with clinicians – Enable coders to easily request clarification from clinicians when documentation lacks necessary details to support accurate coding.
• Provide coding resources – Invest in current technologies and software to optimize coding accuracy and efficiency. Automated processes reduce mistakes.
• Report metrics – Compile coding metrics by staff and department to spot high error rates needing support. Common metrics include denials, coding variance, and audit results.
• Reward accuracy – Recognize coding staff who achieve high standards for accuracy and productivity to motivate quality. Make it a component of performance evaluations.