Tool automates data extraction from electronic health records.
The Agency for Healthcare Research and Quality developed the Quality and Safety Review System (QSRS) to provide a consistent way to measure patient safety. Human data abstractors answer questions based on information in the medical record and enter information into QSRS. QSRS uses that data to calculate and report adverse event rates for 21 types of hospital-acquired conditions. Manual data abstraction is time consuming and error prone. That’s why Octo created a tool that uses artificial intelligence (AI) to automate the process. By leveraging a combination of natural language processing to extract data from electronic health records and a neural network to automatically answer algorithm driven questions, the program provides data that can be used to report a variety of findings such as adverse event rates for hospital-acquired conditions.
Potential Use Case
Hospitals across the United States can benefit from this tool, saving time and money in data extraction for QSRS reporting. Nursing homes, medical offices, and other facilities can also benefit from automating the process that tracks adverse events that occur with patients. Additionally, the AI used to automate reporting for QSRS could be used to perform entity extraction from any text corpus, extract data about people, places, or things from unstructured data or text, and/or answer questions about people, places, or things.
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