DigitalOwl uses a proprietary Natural Language Processing (NLP) platform, developed exclusively for medical records that insurance companies use for underwriting and claims. Our solution automatically analyzes medical documents, including extracting medical data from imaged records. A deep understanding of the medical text creates a focused set of medical data points in a robust, meaningfully summarized format.
Matanya Hanan
matanya@digitalowl.com
Entrance D, Building C, Ha-Shlosha St 2, Tel Aviv-Yafo
0548076656
https://www.digitalowl.com
What is DigitalOwl?
By quickly and thoroughly analyzing the medical documents, including data from imaged records, DigitalOwl gets a deep understanding of the record no matter the quantity of pages analyzed. This understanding is then transformed into a focused set of medical data points in a meaningful, summarized format. To fully analyze medical records, the technology must be able understand the relationship between extracted entities and apply the right context. DigitalOwl’s proprietary NLP technology does that.
What are the Advance vs current solutions?
Today, insurance companies manually review all their medical records or send them offshore to a manual summarization service. DigitalOwl analyzes most cases in 3-5 minutes. Human reviewers can take up to 3-4 hours to review the same case and in some cases can take days to turn the summary around if sent offshore. In all cases, DigitalOwl typically identifies twice as many significant medical data points as the human reviewer at 95% plus accuracy.
What are the challenges?
There are a variety of styles and formats, requiring the understanding of the text and the absolute location of words. Inconsistent, poor scanning quality, grammatical errors, duplicated records, overlapping and highly contextual information from multiple sources are all challenges with scanned medical records that we have been able to solve for.
DigitalOwl technology
Using our proprietary, purpose-built Natural Language Processing (NLP) platform that was developed exclusively for medical records.
Market size
Manually reviewing medical records at scale is a huge drain on resources. The US industry spends $3.5B on labor reviewing medical records per year.