Coder

Coder is a web-based platform designed to streamline the process of clinical coding, particularly for safety-related data such as adverse events and concomitant medications. It supports standard medical dictionaries like MedDRA and WHODrug, as well as multilingual dictionaries, to facilitate both automatic and manual encoding of verbatim terms through advanced search mechanisms.

The system is integrated into electronic data capture (EDC) systems via a Web Service API, allowing seamless interaction with leading safety and clinical data management systems. It includes a review workflow that complies with 21CFR11, ensuring that coded information can be transferred back to the EDC system for reporting and queries, complete with a full audit history.

Key Features

• Powerful Autocoding: Automatically code data using MedCodr for medical dictionaries or UMA KODA for WHO drug dictionaries, supporting any language.
• Automated Term Matching: Automatically match terms against selected dictionaries, with options for review.
• Impact Analysis: Evaluate the effects of new dictionary versions on coded data and custom queries.
• Dictionary Explorer: Browse and compare dictionary terms across versions to identify differences.
• Synonym List Management: Manage synonyms by approving, rejecting, or reassigning candidates, and create synonyms based on verbatim and metadata.
• Term Review Queue: Place coded terms into a queue for independent review.
• User Interface: Offers an easy and intuitive UI compatible with all modern browsers.

Benefits

• Anywhere, Anytime Access: Access Coder from any location at any time for convenience.
• Configurable Integration: Use as a standalone system or integrate with your preferred EDC system, with setup support from a dedicated team.
• Regulatory Readiness: Standardizes language for reporting adverse events and medications, ensuring regulatory compliance.
• Efficient Coding: Save time and reduce costs by managing dictionaries and ensuring coding against the latest versions.

Medical coding is crucial for data cleaning in clinical trials, ensuring uniform interpretation of medical terms using standardized dictionaries like MedDRA and WHODrug. This process is essential for grouping data for meaningful analysis, with MedDRA being the recommended dictionary for medical events in clinical trials and WHO Drug Dictionary used for coding medications.