An article in Forbes joked that, if medical school was based on what being a doctor is actually like, then 'Medical school admissions essays would be on “why I really want to do paperwork when I grow up.”' Paperwork is the top issue ruining medicine for many doctors in the U.S. It's not the best use of their time and significantly reduces available time for patients. Doctors spend at least 50% of their time on paperwork . This includes everything from clinical summaries to surgery notes that are needed for their own records, insurance claims, drug records, and patient’s medical charts; a good amount of their time is spent filling out Electronic Health Records (EHRs).

Nonetheless, documentation is an important part of a physician’s work. What they wrote down needs to be converted into actionable items. Natural Language Processing (NLP) leverages artificial intelligence (AI) to understand and work with unstructured data. Allganize's NLU can automatically scan what's written down to extract  information to and from EHRs and even give EHRs speech-recognition capabilities during doctor's visits.

However, interpreting doctor's notes isn't enough to get them paid. They need to be accurately documented, converted and assigned a billing code in order to receive payments. If you miss something or made a mistake in the billing code, you are not going to get paid. An investigation of medical malpractice cases found that data entry shortcomings contributed to about 20% of malpractice claims that pointed to EHRs as part of the reason for a patient safety event. Allganize's NLU can easily decipher unstructured text automatically and extract diagnosis to convert into ICD-10 and billing code, minimizing time and error.

There is an urgent need for medicine to automate using natural language processing. We hope our technology can decrease paperwork time, increase face time with patients, minimize human error, and increase safety.

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