At present ICD-10 has over 14000 codes for diagnosis. Do you think artificial intelligence has
brought us a way to clear all the specialty coding confusions during your busy schedule? WHO had
stated already about the introduction of ICD-11 coding in January 2022. The revision of codes again
begins. Well, how do you stop your denials from errors through coding? Is it not the right time to
slightly change your strategy towards practice?
To the matter of fact, the coding numbers are substantially more than the numbers mentioned above.
Enhanced version of ICD-10 has around 1,40,000 classification codes, 7000 diagnosis codes and 70000
for classification of treatments. Expected ICD-11 codes will have several times more codes than they
are currently ,which also includes treatment codes and large number of diagnosis codes as well.
Even though human intelligence is considered as super computer, it’s not practically possible to
remember all of these codes between patient responsibility and other important tasks. Healthcare
professionals have been relying on coding books for decades that slow down the revenue cycle process
as well as practice.
How Artificial Intelligence increases coding efficiency?
Artificial intelligence has become more advanced and succeeded in its way to different industries.
As medical billing and coding practices involve large amount of data input analysis . Medical coders
or healthcare professionals must analyze and work towards entering the data inputs in to the
computer regarding the treatment, procedures and diagnosis in coding format for revenue generation.
1.Text Processing:
Artificial intelligence has developed itself in analyzing texts in regards to billing and specialty
coding. They are programmed in a way to identify the keywords and code accurately according to the
treatment and diagnosis mentioned.
By generating the relevant codes automatically from the medical report, the errors in code selection
and coding inputs decreases.
The text processing level may vary depending on analyzing digital records and scanning the files.
Some programs can also analyze handwriting by making the transcription process much easier.
Handwritten files are transcribed into digital format with AI.
The above process reduces risk of errors and also maintains accuracy while submitting the claims.
Some AI processes are capable of reading accurate cursive writing.
The more comprehensive Artificial intelligence is, the more medical coders will be able identify
medical codes for treatment.
2.Accuracy :
One of the main reasons for denials and rejections is inaccurate medical billing and coding.
Specialty coding errors can damage the practice revenue to maximum extent.
Insurance companies are more cautious about the medical billing and coding errors where even a small
coding mistake can lead to the denial or rejection of the claim.
Artificial intelligence can assist in increasing the claim accuracy and stop denials and rejections
from halting revenue payments.
Inaccuracy is one of the main reasons to Artificial intelligence implementation in medical billing
industry to make the claim process accurate and perfect.
Accuracy is not only about analyzing text and records, but to determine those procedures which
require perfect billing.
Not all of those CPT and ICD codes refer to individual treatment and diagnosis. Some specialty
coding includes multiple procedures intended for few cases at once.
Artificial intelligence helps to enter these bundled codes meant for the greater use of practice by
entering several different codes without mistakes which refers to same case.
Artificial intelligence is capable of recognizing these appeared bundled codes and update them all
into a single code without compromising in accuracy and benefits in time management by allowing
specialty coders to keep tracking those claims all together.
Adaptation to changes in medical billing industry:
Medical codes or specialty codes will not have changes in large scale but often are updated with
needs of healthcare professionals.
Previous year, the coding updates brought around 392 new codes, 216 deleted codes and eight revised
titles. Sometimes, total revision on coding standards also involves adjustments to the existing and
new codes.
During these changes, healthcare professionals might require time to get used to these new updates
and it can meanwhile lead to more errors at the time of learning process as the codes are new and
updated.
Artificial intelligence can facilitate these adjustments by suggesting new codes or avoiding
entering of codes that no longer exists. It also reminds the new changes and speeds up the process
of coders adapting to future changes.
Decreased Processing Times:
Another most challenging issue faced by medical billing and coding industry is the processing time.
The present process involves and consumes a lot of time for claim process and takes extra time for
insurance companies to accept claims and clear the payments.
These payments make reimbursements very late and cause huge discomfort for patients, healthcare
professionals and also insurance companies.
Processing time management starts from medical coders. All the processes mentioned including text
processing through artificial intelligence can actually save coders time in compiling and automating
procedure and billing information.
This increases coding efficiency and fastens the process benefitting healthcare professionals,
patients as well as payers.
When artificial intelligence comes to rescue in means of time and resources, healthcare
professionals can concentrate more on patient care and maintain accuracy during most complicated
coding situations.
These can predominantly improve healthcare professionals’ income and reimbursement rates as well as
healthcare industry’s growth.
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