It seems that computers have become a part of all medical care services in that they are used to make appointments, check in for those appointments, verify eligibility, even accept payment. Providers have them in their hands before, during, and after patient encounters, which allows them access to records grouped within a provider network where they can see an test results and labs that were ordered by, performed by, and documented by other providers, replacing the copy, print, or securely sent medical records through old technology methods. Even certain medical decisions now require providers to run the request through AI to identify if medical necessity for more expensive types of medical services is sufficient. The following are a few ways in which computers are used to improve on the way medical coding occurs to ensure accuracy for the claims submission process.

Computer-Assisted Medical Coding (CAC)

CAC represents a blend of human expertise and technological support in the medical coding process. CAC uses software and algorithms to support human coders in the assignment of CPT, ICD-10, and HCPCS codes to medical records. CAC systems analyze clinical documentation, including diagnoses, procedures, and treatments, and provide a list of suggested codes based on programmed rules and guidelines. The human coder reviews the suggested codes, accepts or rejects them, adds any missing codes, and once approved, completes the claim. This allows the coder to review services for complete an accurate code assignment before claim submission. 

Advantages of CAC

• Efficiency: Coders can be much faster using CAC than when they were manually assigning codes, which improves their efficiency through automating time-consuming tasks. The computer's ability to quickly analyze large amounts of complicated data and generate code suggestions within seconds, allows coders to complete coding assignments faster and frees up their time to focus on more complex cases, ultimately increasing productivity.
• Accuracy: CAC reduces the likelihood of human errors in medical coding. By leveraging algorithms and programmed, predefined rules, the system minimizes coder review, improves code selection, and reduces coding inconsistencies. The result is improved accuracy, coding consistency, reduced claim denials, and improved revenue cycle management.
• Compliance and Consistency: CAC systems are programmed to adhere to established coding guidelines, which if programmed correctly, ensure regulatory compliance. These systems can incorporate updates to coding standards promptly, reducing the risk of non-compliance. Additionally, CAC promotes coding consistency, as it applies coding rules uniformly. This means where one coder may have more experience than another in assigning codes to certain specialties or service types over another coder, the engine applies the rules consistently, minimizing coding variations that can arise from human interpretation based on experience.

Autonomous Medical Coding

Autonomous medical coding takes it to another level completely, by leveraging artificial intelligence (AI) and machine learning algorithms to assign codes without any human intervention. These advanced systems analyze incredible amounts of data, learn from patterns, and continuously adapt to coding practices and guidelines. This makes them increasingly accurate over time. One example of this is coding EKGs or simple x-rays. These two services are performed hundreds, if not thousands of times a day in the hospital and the documentation requirements for them are straightforward and simple to identify within the documentation. Why should a coder spend countless hours coding these simple healthcare services when the engine can quickly do it and with near 100% accuracy? These coders can have their time freed up to work on the more complex coding scenarios that require human intelligence and problem solving.

Advantages of Autonomous Coding

• Speed and Scalability: Autonomous coding systems process massive volumes of medical data in real-time with incredible speed and offer scalability. With the ability to swiftly assign accurate codes, these systems contribute to faster reimbursement processes as well as improving efficiency in coding processes in large hospital settings where thousands of services are provided daily. 
• Continuous Learning: AI-driven autonomous coding systems are constantly learning and evolving through the process of analyzing coding patterns and adhering to guidelines. These systems easily adapt to changing coding requirements, ensuring accuracy even as medical practices and coding standards change and evolve. The ability to learn and improve over time enhances the system's long-term efficacy, and may require only minimal human intervention.
• Resource Optimization: While autonomous coding reduces the heavy reliance on human coders for routine coding tasks, there will always be a need for human coders. Where autonomous completes routine coding tasks, more complex tasks must be completed by human coders who are and will remain valuable resources. Organizations can assign coding professionals to more complex coding challenges, clinical documentation improvement initiatives, or other critical areas where human expertise is crucial. The optimization of coding resources in this manner, can lead to cost savings and improved assignment of more skilled coding staff. 

Computer-assisted medical coding (CAC) and autonomous medical coding are transforming the way healthcare organizations document and process patient information. While CAC uses technology to assist human coders in assigning codes more efficiently and accurately, autonomous coding takes automation to the next level by independently assigning codes based on AI algorithms. Both approaches offer significant advantages, including increased efficiency and accuracy, compliance with coding standards, and the use and assignment of valuable coding resources to optimize outcomes. As the healthcare industry continues to embrace this technology, the human coder who continues to gain knowledge and experience, promote their education in fields of advanced coding and auditing, will continue to be a valuable asset to any healthcare organization in ways these systems may not be able to. Additionally, coders and healthcare organizations who embrace technology will find a world of new opportunities in the field of CAC and autonomous coding, as they are poised to play pivotal roles in streamlining documentation processes, improving patient care outcomes, and ensuring correct reimbursement.