Webinar: Power the delivery of comprehensive care with Clinical Natural Language Processing
When: Tuesday 23 March, 2021
Time: 12:00pm EDT; 9:00am PDT; 4:00pm GMT; 5:00pm CET
Duration: 60 minutes
In healthcare the aim for all providers is to obtain optimum health for patients. Over the past several years, there has been a shift in focus from volume to quality – and as such, there is real focus on holistic and preventative care. This shift has driven the rise in organizations such as Integrated Delivery Networks which seek to manage patients across the continuum of care – from preventative care through to post-acute care – such as physical rehabilitation.
To successfully deliver this holistic care, clinicians need to base their decisions on the best possible view of their patient’s data. As approximately 80% of healthcare data is trapped within unstructured sources (i.e. nurse notes, HL-7 messages, radiology reports, pathology, etc.), rapid effective access to the knowledge buried in such documents is essential to both maximize patient benefits and do no harm. This webinar will offer a demonstration of a multi-mission clinical Natural Language Processing (NLP) platform and advanced clinical analytics. We will also show how clinical NLP, as a key AI technology, can enhance advanced machine learning models. Use cases span from precision medicine, clinical research to clinical operations.
What will you learn?
During the webinar we will review how a flexible, multi-mission clinical NLP platform can provide an enterprise solution that significantly reduces manual effort and time, and provides support across multiple areas in Healthcare including:
- NLP automation at scale
- Population Health initiatives
- Understanding Social Determinants of Health
- Analyzing Clinical Registries – Clinical care/research (i.e. Cancer)
- Improving Patient Safety and Quality (i.e. Radiology report safety nets)
Who should attend?
This webinar will be of interest to senior data, innovation and informatics leaders and stakeholders looking at using data driven approaches to improve patient health and care delivery.