Session ID: 
183

Using Artificial Intelligence and Natural Language Processing to Uncover Population Social Determinants of Health Factors

4:00pm - 5:00pm Wednesday, February 13
Orlando - Orange County Convention Center
W311A

Description

Mt. Sinai Health System explains how the provider uses machine learning and a natural language processing (NLP) algorithm to uncover social determinants of health (SDoH) in unstructured data contained in EMRs. The session speakers describe key factors for success in creating NLP ontologies, illustrate lessons learned and outline effective approaches to deploying NLP-based solutions for mining social determinants and other key data captured in progress, admission, procedure and consultation notes and discharge summaries. Attendees will be able to take away best practices for applying NLP solutions to their specific settings and care objectives for effectively identifying SDoH factors and other important clinical data residing in clinical notes.

Learning Objectives: 

  • Discuss how social determinants of health help providers improve clinical models, understand disease progression and identify phenotypes
  • Identify how to cost effectively and accurately extract SDoH data by exploiting the rich content in unstructured clinical notes
  • Define and create an initial ontology set (best practices for?)
  • Recognize how to leverage artificial intelligence (text mining?) and NLP to review existing data (i.e., clinical notes existing in provider EMR), accurately identify SDoH in patient records and scale for application to a variety of initiatives

Speaker(s): 

IT Director, Analytics and Data Management,
Mount Sinai Medical Center
Senior Vice-President & Global Practice Leader,
Cognizant Healthcare Consulting Practice

Audience: 

CIO, CTO
C-Suite
CMIO/CMIO

Level: 

Intermediate