There is tide sweeping across the medical landscape where government regulators and insurance companies are trying to control escalating medical costs by encouraging digital transformation. Physicians’ records and notes contain a wealth of medically useful data. These notes are often easily lost, hard to keep track of or difficult to decipher, and even when captured in Electronic Medical Record (EMR) systems, coordinating one doctor’s notes on a patient with their other files is a time consuming process.
Using Natural Language Processing (NLP) can be revolutionary for healthcare professionals by analyze reams of medical records and identify (and derive meaning from) hidden correlations between symptoms, diagnoses, medications and treatments. This gives healthcare providers new tools to manage quality care initiatives. For example, considering risk predictions for illnesses based on extracted insights.
Linguistic-based solutions can infer words’ intended meanings, which allows healthcare providers to build never-before-seen insights into physician notes. There are now applications that can both detect and notify administrators when new patients are at high risk for re-admittance, in real-time while the patient is still being treated at the hospital.
Using cutting-edge cloud based technology from our partber ezDI, information from the EMR can be converted from unstructured to structured data, and can be used to create knowledge graphs which can be made sense of using AI and a machine learning.