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The differences between medical insurance coders and medical biller coders can be seen in a few details. Each job has different responsibilities and duties. While it typically takes 1-2 years to become a medical insurance coder, becoming a medical biller coder takes usually requires 6-12 months. Additionally, a medical biller coder has an average salary of $38,756, which is higher than the $32,709 average annual salary of a medical insurance coder.
The top three skills for a medical insurance coder include patients, insurance verification and medicaid. The most important skills for a medical biller coder are patients, medical billing, and ICD-10.
| Medical Insurance Coder | Medical Biller Coder | |
| Yearly salary | $32,709 | $38,756 |
| Hourly rate | $15.73 | $18.63 |
| Growth rate | -3% | 11% |
| Number of jobs | 81,028 | 54,861 |
| Job satisfaction | - | 5 |
| Most common degree | Associate Degree, 33% | Associate Degree, 30% |
| Average age | 46 | 45 |
| Years of experience | 2 | 12 |
Medical insurance coders and medical biller coders have different pay scales, as shown below.
| Medical Insurance Coder | Medical Biller Coder | |
| Average salary | $32,709 | $38,756 |
| Salary range | Between $27,000 And $38,000 | Between $30,000 And $49,000 |
| Highest paying City | - | San Francisco, CA |
| Highest paying state | - | California |
| Best paying company | - | University of California, Berkeley |
| Best paying industry | - | Professional |
There are a few differences between a medical insurance coder and a medical biller coder in terms of educational background:
| Medical Insurance Coder | Medical Biller Coder | |
| Most common degree | Associate Degree, 33% | Associate Degree, 30% |
| Most common major | Health Care Administration | Health Care Administration |
| Most common college | University of Pennsylvania | University of Pennsylvania |
Here are the differences between medical insurance coders' and medical biller coders' demographics:
| Medical Insurance Coder | Medical Biller Coder | |
| Average age | 46 | 45 |
| Gender ratio | Male, 10.8% Female, 89.2% | Male, 10.0% Female, 90.0% |
| Race ratio | Black or African American, 12.1% Unknown, 4.3% Hispanic or Latino, 18.1% Asian, 6.8% White, 57.9% American Indian and Alaska Native, 0.8% | Black or African American, 9.3% Unknown, 4.2% Hispanic or Latino, 17.8% Asian, 8.0% White, 59.5% American Indian and Alaska Native, 1.3% |
| LGBT Percentage | 7% | 9% |