The Top 5 Advantages of AI-powered vs. Manual Medical Coding

The Top 5 Advantages of AI-powered vs. Manual Medical Coding

Recently, medical coding has seen a dramatic shift from manual to automated methods, and with good reason. Ultimately, automation helps improve accuracy and save time and money. But what are the tangible benefits of automatic coding versus manual, and how exactly do they play out in a healthcare setting? Here, we delve into the top five advantages that tip the scales in favor of automation.

Efficiency and Accuracy

Traditionally, medical coding has been a labor-intensive process, susceptible to human error and variability. However, automated systems, underpinned by advanced algorithms and artificial intelligence, have revolutionized this domain. They can swiftly parse through medical documentation, recommend suitable Current Procedural Terminology (CPT) codes, and precisely accomplish coding tasks.

For example, an automated system can process and accurately code a patient's complex visit note within seconds — a task that could take a human coder several minutes. This helps dramatically cut down on coding time and errors, elevating efficiency and accuracy.

Consistency and Compliance

Compliance with established coding guidelines and regulations is paramount. And AI workers excel here. Programmed with the latest coding rules and updates, they guarantee compliance with industry standards. While manual coding can diverge based on a coder's experience, knowledge, or guideline interpretation, automated systems ensure a uniform approach, drastically reducing inconsistencies and the risk of non-compliance. The benefit? No unexpected audit complications or financial penalties due to non-adherence.

Increased Productivity

Automation facilitates healthcare professionals to prioritize patient care and other critical responsibilities. Automated systems efficiently handle repetitive coding tasks, liberating time for medical coders to tackle more complex cases. This newfound productivity can fuel improved healthcare delivery and diminish administrative overheads.

A medical coder spends an average of 15 minutes manually reviewing a patient's case. An automated system could reduce that time to just a few minutes, freeing valuable time on more critical tasks.

Reduced Costs

The manual coding process is resource-intensive. It demands skilled coders, thorough training, and continuous education to remain current with ever-changing coding guidelines. Once set up, automated coding systems can substantially trim costs linked with manual labor, training, and potential coding inaccuracies. An automated system can provide significant long-term cost savings despite an upfront investment. For example, a coding error resulting in a rejected claim could cost a healthcare organization hundreds or thousands of dollars.

Data Analysis and Insights

Beyond mere coding, AI workers can gather and scrutinize vast volumes of coding data. This data can yield invaluable insights into coding patterns, reimbursement trends, and areas requiring further documentation or training. With this information, healthcare organizations can optimize their Revenue Cycle Management (RCM), identify coding gaps, and refine coding practices. For instance, data analysis might reveal a pattern of under-coding certain services. The provider can then address this issue to ensure accurate reimbursements every time.

Yet, while automated coding offers many compelling benefits, it's vital to stress that human supervision and expertise are still indispensable. By striking the right balance between human expertise and machine precision, healthcare organizations can capitalize on the benefits of automated medical coding.

Introducing Care Review

Our pioneering product, Coding and Notes Review, is underpinned by a two-step approach - Note Review and Charge Coding. These processes help to streamline documentation, enhance reimbursement rates, and increase overall productivity.

How does it work? AI workers can digest patient visit notes using optical character recognition (OCR) and provide feedback for length, accuracy, and completeness. This ensures providers share adequate information with payers to maximize payment rates. We then use Charge Coding to pull out diagnosis and procedural codes from the text and update the EHR with the relevant details. We also ensure that supporting materials like X-rays, test results, etc., are included in the claim — reducing time spent with charge capture by 80%. 

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Published On:

January 9, 2024

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