(This is the second of a three-part series* about medical coding during clinical trials.)
The medical coding system used for clinical trials or safety verbatim-term coding usually contains multiple terminologies such as MedDRA and WHODrug dictionaries. Due to the variety and complexity of the dictionaries, the days when a coding solution only needed a verbatim term for coding are over. Today’s solutions often require additional information. In this post, I will discuss the integration of the coding system with the data collection process.
Here’s how a typical coding process works: Verbatim terms are collected — for example, in an EDC solution — and are sent to a coding system. When considering a match of a verbatim term with the official terminology, the first approach is to consider an exact match. For example, the verbatim term Leg pain is an exact match with a lower level term (LLT) in MedDRA. However, if the system does not automatically find a match with a terminology term, a coder will perform the manual process of mapping the verbatim term to a terminology term.
This means that a coding system doesn’t collect verbatim terms or any other subject/patient data. Therefore, a coding system cannot function without having data coming from other software products. Consequently, a coding system must be designed for integration, so the coder can use the same coding solution independent of the verbatim terms’ data sources.
Since a lot of the coding processes require data or metadata from other systems, a coding solution should be designed with a well-documented API to aid integration projects. Given the currently available technology, I recommend selecting a coding system with a representational state transfer (REST) API. However, you also need to consider that your data collection systems could be using older technologies, and therefore, your coding solution should be able to receive and send data via text files in case the REST APIs cannot be used directly.
For drug coding, it often is relevant to know the country, form and dosage, together with the verbatim term to be able to accomplish the appropriate coding. In addition to this information directly aiding in the coding process, the coding system must also have a back-pointer into the data collection systems, so that the coder can navigate to the appropriate page in a specific data collection system and find other relevant information. The coder would, of course, need to have appropriate privileges to access this data.
Another import issue in data exchange is the data the coding solution returns to the data collection systems. Especially with the FDA requirement to use WHODrug B3/C3 by 15-Mar-2019, it is important to validate if the data collection systems can receive and store drug names of up to 1,500 characters long. If that is not the case, you might have to evaluate a different data collection system or build a different solution for SDTM generation when you need to work with the longer drug names.
Finally, as new terminology versions are released, your coding solution must be able to show the impact on ongoing trials and allow you to up-version your trial data at the appropriate time.
Over the past 20 years, an increasing number of coding solutions have been launched, and that makes it harder to choose the right solution. However, when you do evaluate a solution, remember that it needs to work with your existing solution as well as your future solution. Therefore it is important that you select a coding system designed for integration.
About the Author
Kim Rejndrup recently joined OmniComm as senior vice president-Product Development. Mr. Rejndrup spent nearly 20 years at Oracle Corporation, where he was a vice president of development for many clinical research applications, including systems for electronic data capture (EDC), clinical trials management, data management, medical coding and data warehousing. His experience is driving OmniComm’s products to new levels of innovation.
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