Accuracy in medical coding is a vital aspect in aiding clinical trial operation success. It has presented an excellent opportunity for medical coders, working hand-in-hand with AI-enhanced computer-assisted coding systems, to quickly identify and validate the correct codes. Using natural language processing (NLP) and advanced Machine Learning algorithms, AI is transforming medical coding by improving coding accuracy. In this blog, we’ll explore what this transformation means for clinical trial organizations.
What is Medical Coding?
Medical coding is a critical process that involves assigning standardized codes to medical terms in clinical trial participant medical records, diagnoses, and procedures in order to accurately track and record a patient’s treatment data and that the research study is conducted ethically and efficiently. The medical coder will conduct searches in dictionaries (such as MedDRA, and WHO DRUG) to associate it with the right code in order to submit treatment results to regulatory authorities.
Why do you need AI-assisted Medical Coding?
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.
Benefits of AI Medical Coding
- 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. It provides an idea of what codes are being generated via documentation, allowing clinical trial teams to fix their notes if the data doesn’t apply to a specific patient encounter.
- Faster Coding: With the power of AI, companies can cut coding turnaround by days, not hours or minutes. This is owing to AI’s ability to quickly and intelligently map terms within the patient data with the right codes and provide suggestions to a coder to approve. This enables medical coders to simply accept the suggested term or choose from a list of suggested terms. Once a term has been accepted, all same terms in the study are automatically coded with the accepted term. 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.
Future of Clinical trials AI Medical Coding
In the recent few years, AI has been the go-to when it comes to clinical record keeping. AI medical coding has paved the way for translating patients’ complex symptoms, and clinicians’ efforts to address them, into clear and unambiguous classification codes, with precision and speed.
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!
