Medical coding is the process of assigning standardized codes to medical terms in patient records, diagnoses, and procedures. Medical coders use dictionaries like MedDRA and WHO DRUG to associate the correct codes with medical terms and accurately track and record a patient’s treatment data, efficiently conduct ethical research studies, and submit treatment results to regulatory authorities.

Medical coders typically spend over 200 hours per month on repetitive tasks, which translates to a significant amount of time and cost. Thankfully, AI and Machine Learning are making their way into the medical coding world and are expected to improve efficiencies significantly by reducing the amount of manual labor that goes into coding patient data. . AI medical coding reduces the time to code and reduces human errors leading to a reduction in study duration and costs. All of this helps bring drugs to the market faster and enables patient well-being.

• Increased Accuracy: AI medical coding acts as a guidance system for electronic health records (EHRs) that works at superspeed, to ultimately improve a clinician’s accuracy. Clinical trial teams can fix their notes if the data doesn’t apply to a specific patient encounter by understanding the codes generated through documentation.
• Faster Coding: Using AI in medical coding can greatly improve the efficiency and effectiveness of the process. AI’s ability to quickly and accurately map terms within patient data to the correct codes, and provide suggestions for coders to approve, greatly reduces coding timelines.This statement suggests that using automation in the coding process can lead to faster turnaround times, fewer errors, and improved accuracy of patient records. By enabling coders to simply accept the suggested term or choose from a list of suggested terms, the use of AI in medical coding streamlines the process and increases the speed and accuracy of the process. This automation greatly reduces coding timelines.
• Reduce Risk: AI Medical Coding is helping organizations to streamline their coding processes, reduce errors, and ensure that the proper codes are being used for each term. This reduces the risk of incorrect coding, improving data quality and study outcomes.

AI can act as a strategic partner for clinical trial teams worldwide, maintaining decades of patient data and transforming trial models to best suit futuristic clinical research. Based on that, AI in clinical trials is only set to grow, especially in the realm of medical coding.

Clinion specializes in AIML technologies that are transforming the medical coding process in the clinical trials industry. To learn more on why clinical trial organisations should consider embracing this cutting-edge technology, hop onto our website now!

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