In clinical trials, patient data such as adverse events and concomitant medications is coded against standard medical dictionaries. However, this process comes with challenges. A large number of codes require manual review and duplicate work, making the task labor-intensive and highly inefficient. These manual efforts can lead to inconsistencies in coded terms across coders and studies, delays, and increased costs, which ultimately slow down the time to market for clinical trials. Many teams are leveraging AI for higher-quality clinical trials but fail to make the most of AI’s potential when it comes to medical coding.
Push past medical coding challenges with AI from CluePoints.
A Closer Look at Medical Coding Challenges
The standard medical coding workflow uses a rules-based automated coding tool, followed by manual review by two human coders. Basic auto-coding tools coupled with synonym lists typically effectively code 70–80% of input terms, leaving 20–30% of terms needing to be manually coded.
The Labor-Intensive Nature of Medical Coding
The many manual aspects of medical coding place a significant burden on coders. They spend countless hours meticulously reviewing and verifying codes, yet there remains a possibility of human error. More manual reviews also mean more bottlenecks, slowing down the time to market for trials.
Inconsistencies & Quality Control Issues
Manual coding introduces the risk of inconsistencies across different coders and studies. Even experienced coders can have varying interpretations, leading to discrepancies that compromise the quality and accuracy of the data. These inconsistencies necessitate additional quality control checks, which consume valuable time and resources, further delaying the process.
The Use of Synonym Lists
Synonym lists are often used to aid in the coding process. However, these lists become less accurate with changes in medical dictionaries such as MedDRA and WHODRUG, as the new dictionary versions may include terms not previously seen. This leads to more terms needing to be manually coded, adding additional effort for coders.
Delays & Increased Costs
The traditional approach to medical coding typically involves a two-step process in which one coder assigns the codes and another expert performs a secondary review for those terms that are not autocoded. This not only adds to the workload but also introduces delays and additional unnecessary costs. The need for extensive manual review prolongs the time to market for clinical trials, affecting the overall efficiency of the process.
The Need for Intelligent Medical Coding
Recognizing these challenges, CluePoints developed a medical coding solution designed to dramatically improve the coding process. This solution addresses the inefficiencies and obstacles of conventional methods, offering a more automated approach that significantly enhances the accuracy, efficiency, and quality of results.
One major CRO saved 55% of time spent coding with CluePoints’ Intelligent Medical Coding tool.
With CluePoints, medical coding becomes a swift and harmonious blend of automation and human expertise. The benefits of CluePoints’ Intelligent Medical Coding are significant:
- Automate even more of the coding process
- Increase accuracy with DL algorithms
- Reduce manual effort and improve productivity
- Introduce greater consistency and quality control
- Streamline coding workflows and speed time to market
Learn more about our Intelligent Medical Coding solution to experience the fundamental improvements that will optimize your operations. Contact CluePoints today.
