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Medical Coding: Another Doomed Job?

A medical coder translates medical diagnoses and procedures into standardized alphanumeric codes for billing. These codes are used in patient documentation to generate accurate bills, ensuring timely reimbursement for the doctor’s services from payers.

TL, DR: medical coding exists so doctors get paid fairly.

Why then, is such an important job doomed?

Don’t get us wrong; medical coding remains one of the most valuable practices in the healthcare industry. Every healthcare provider bogged under millions of patient records is in need of a medical coder who can translate their charts and SOAP notes into appropriate medical code. 

However, this need for high data accuracy is also the same reason why medical coding becomes prone to human errors, data oversight, wrong ICD-10 code assignment, extreme administrative burden, under-coding,  and eventually, loss of revenue.

But how does it affect doctors?

One line of incorrect medical code can cost millions of doctors their fair share of the revenue. Moreover, the American Medical Association (AMA) proved this fear right by estimating that every coding error costs the healthcare industry approximately $36 billion annually.

Things get worse, as incorrect medical code leads to :

Researchers in varied fields of data analysis have procured the primary causes of medical coding errors, with the most common being:-

Coders would get frustrated,” says Dr David Provenghi, ProSciento, “It could take so long to find a suitable match that when they saw something that looked close they chose it.”

Here is Where Technology Comes to Rescue

Outsourcing skilled medical coders can be one of the solutions, but all the more an expensive one, which many hospitals cannot afford.

With so much in line, the healthcare industry has finally confided in technology to rescue its administration from inaccuracy, burnout and lost revenue. Automation’s beauty lies in precision and enhancing speed, mostly in the fields of administration and documentation.

The use of cutting-edge AI technology like Machine and Deep Learning in the suggestion of appropriate medical codes has promised accuracy by reducing coding errors by up to 42%. Automation in medical coding, therefore, leads to:-

Doctors can loosen the rope of extensive paperwork around their necks and focus on what they signed up for; treating their patients.  AI saved 50% of physicians from exhaustive non-clinical burnout and wiped off 38% of the administrative paperwork load for hospital staff. 

However, medical coders are still questioning what their jobs would look like In the future.

So, will AI replace human medical coders?

Let’s be clear here. When we raised the question of whether coding jobs are doomed, we sincerely meant “traditional” medical coding. This involves extreme manual shortages, and a painstaking load on medical coders to sift through heaps of documents to get one code right. 

Without AI, inefficiency in administration is horribly eating away at a doctor’s paycheck and a patient’s apt treatment. Therefore, medical coders should forgo the traditional coding mechanism, and adapt to COLLABORATING with AI.

Verdict: Not Replaced, but Enhanced Medical Coding

AI meets the following scenarios where the expertise of a medical coding professional is superior:-

It’s time medical coding and AI meet halfway through, not replace one another. 

That being said, routine tasks that cost manual labor and administrative burnout, or un-clinical tasks for which doctors need assistance, are slowly fading from the scope of employment.

AI has proven to excel in repetitive systemic tasks. Yet,  it is the true expertise of professionals that healthcare still embraces as the top priority in patient care and a thriving force in the industry.

Myth- ” Medical Coding jobs are Doomed”: Successfully debunked!

Follow RevMaxx, a doctor’s personal coding assistant, to understand the nuance of healthcare behind mainstream news.

1 Comment

  • I like the efforts you have put in this, appreciate it for all the great posts.

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