Rave Coder+

The Evolution of Automated Medical Coding Workflows for Rave EDC

Rave Coder+ provides medical coding for clinical trials in English and Chinese1 using WHODrug and MedDRA dictionaries2. Rave Coder+ is built on the ̨ͼⱦ Platform?unified platform with a connected, automated medical coding workflow for coding verbatim terms entered in Rave EDC.

Rave Coder+ features Code with Confidence’3 –? a new, unique coding algorithm that uses Machine Learning models trained with over 60 million historic coding decisions to deliver coding predictions with associated confidence levels.

Rave Coder+ Features and Benefits

In Partnership with Users

̨ͼⱦ developed Rave Coder+ in partnership with 38 of our customers and 200 users in a beta program of six releases, which enabled the rapid inclusion of customer feedback and rigorous testing of each new function.

Code with Confidence

Weve developed a new predictive coding algorithm using Machine Learning models, that are trained and tested with over 60 million historic coding decisions.

Rave Coder+ automatically codes verbatims if a generated prediction reaches a confidence threshold. At a High threshold, predictions are expected to be between 93-96% accurate, depending on the dictionary used. While browsing/searching to code a verbatim takes an average of 5 minutes, Rave Coder+ automatically codes in seconds.

Fast Configuration and Mid-Study Changes

All coding-related study configuration is contained within Rave Coder+, enabling faster study configuration and simpler and quicker mid-study changes without needing amendments to the EDC study build.

Streamlined Coding Workflow

Verbatims entered in Rave EDC for medical history, concomitant medications, adverse events, and any other field containing a symptom, drug, or procedure are automatically flagged to Rave Coder+ for coding. If the automatically generated predictions are not a good match, then using Rave Coder+s advanced browse and search capabilities, medical coders can quickly find their own dictionary matches. Coding decisions are automatically returned to Rave EDC to supplement the verbatim with the coded response.

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Modernizing Clinical Data Management to Be Scalable, Flexible, and Intelligent

This white paper provides a summary of why Clinical Data Management (CDM) must quickly adapt to the mounting data pressures in modern clinical trials and discusses the three pillars that form the foundation of a modern intelligent CDM platform that is needed to succeed in an increasingly complex clinical trial world.

Next-Generation Clinical Data Management

Clinical data capture and management processes and technologies need to evolve to keep pace with the acceleration in the adoption of decentralized clinical trials and the continuing increase of protocol complexity. Learn about ̨ͼⱦ䡯s approach to next-generation clinical data management.

Clinical Data Management and Capture Explorer

What are your biggest challenges and priorities for clinical data capture and management in your studies? Walk through our interactive tool to discover how ̨ͼⱦ䡯s solutions can help you address issues specific to your role, and receive a personalized action plan.

1.Mandarin
2.Japanese versions, the J-Drug dictionary, and other languages to be supported in later releases.
3.For English only in the first release. Chinese, Japanese and other languages to be supported in later releases.

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