Question

Nlp useacases lifescience and healthcare

Answer 1

In this special guest feature, Simon Beaulah, Senior Director of Healthcare at Linguamatics, discusses how natural language processing (NLP) has become a crucial tool in healthcare and the life sciences as these sectors struggle to catch up to other industries and transform their big data into actionable data. Beaulah is responsible for the company’s healthcare products and solutions, including applications for clinical risk models, population health and medical research.

Healthcare has lagged behind other industries in the successful transformation of big data into actionable data that can be easily leveraged for business insights to improve efficiencies and lower costs. The ecosystem of drug company, payer and health system all need to make more effective use of Big Data to ultimately improve patient care, outcomes and wellness.

A key reason: much of the clinical insight into the health of patient populations isn’t in a structured format. This large realm of unstructured data includes qualitative information that contributes indispensable context in many different reports in the EHR, such as outside lab results, radiology images, pathology reports, patient feedback and other clinical reports. When combined with claims data this mix of data provides the raw material for healthcare payers and health systems to perform analytics. Outside the clinical setting, patient-reported outcomes can be hugely valuable, especially for life science companies seeking to understand the long-term efficacy and safety of therapeutic products across a wide population.

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