Manual medical coding processes can be inefficient and time consuming. Auditors are often faced with time constraints when reading complicated clinical notes and regularly miss or underspecify medical codes. The use of automated medical coding through artificial intelligence (AI) has the ability to combat this issue. 

Powered by natural language processing (NLP) and AI, Semantic Health’s Information Platform provides users with an easy-to-use software that produces quality coding results.  It identifies data quality deficiencies and assigns medical codes based on clinical evidence. All insights are then presented to medical coders and auditors in an intuitive user interface to improve coding efficiency and accuracy, focusing auditing efforts on high-value opportunities.

Semantic Health’s Information Platform improves workflows and significantly reduces the review time of clinical charts with automatic code suggestions. It gives coders and auditors additional resources at their fingertips and provides them with an interactive summary of long and complex documentation.

Working with the Hospital for Sick Children in Toronto, Semantic Health has transformed SickKids’ clinical data and documentation processes, contributed to data-driven insights that drive towards SickKids’ long-term vision of precision medicine and helped to optimize internal reporting, operations and research.

Overview
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Type of Technology
AI
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Project Year
2020
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Status
In-progress