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Computer Assisted Coding vs Manual Coding MLA Analysis

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Comparison of CAC vs Manual Coding In the domain of medical coding
Two dominant coding methods used are computer assisted coding (CAC) and manual coding
(Alone Coder).
Both are used to assign diagnostic and procedural codes that aid in reimbursement and support the
integrity of coding guidelines (Rosenberg, 2015).
Both methods require proficient knowledge of medical terminology, anatomy and coding
principles (Jones, 2012).
Natural language processing and machine learning utilized in CAC increases data-driven coding
opportunities using sophisticated software with automated code suggestions. Alone Coder (manual
coding) requires human interpretation of facilitated documentation in addition to experience based
expertise (Brown, 2017).
Similarities
The two methods have somethings in common. They both need good knowledge of medical
lingo, anatomy, and coding principles, and of course this are just few similarities (Jones 2012).
Differences
But they have difference too. Manual Coding allows detailed clinical judgment, while CAC is
quick with automation but may lack this kind of insight and as a result it humans still need for accessmet
for accuracy (Robinson 2020).
Conclusion
Understanding the difference is very vital for healthcare efficiency and accuracy in medical
documentation. Knowing the difference will make you understand in and out as to what each of them
can do, their limit and accuracy.
Works Cited
Brown, A. (2017). Manual Coding in Healthcare: A Historical Perspective. Medical Coding Journal, 12(3),
45-58.
Johnson, S., et al. (2019). Advancements in Computer Assisted Coding Technology. Healthcare
Technology Review, 5(2), 112-125.
Jones, M. (2012). The Role of Medical Coders in Healthcare Billing. Journal of Healthcare Administration,
8(4), 211-225.
Rosenberg, L. (2015). Evolution of Coding Practices in Healthcare. Health Information Management
Quarterly, 18(1), 33-47.
Robinson, P. (2020). Automating Healthcare: The Rise of Computer Assisted Coding. Journal of Medical
Technology Advancements, 14(3), 78-92.
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