Time: 8:00am PDT, 11:00am EDT, 4:00pm BST, 5:00pm CEST
Duration: 60 minutes
In order to promote healthy outcomes, it is essential to identify barriers that may hinder this goal. Social Determinants of Health (SDoH) are the cornerstone to understanding a complete view of the patient, allowing for the identification of inequities so such disparities may be addressed. There is a multitude of information available in unstructured data that could improve our understanding of the hardship facing patients.
Providers and payers have access to various rich information via existing EHR data feeds, (such as clinical notes, patient portal messages, call center notes) and other information such as claims that allow the capture of SDoH from routine clinical interactions. SDoH and health equities are also of interest to life sciences teams as they seek to do things like improve study design, understand barriers to access, better communicate and inform patients and healthcare professionals and develop support programs. This webinar will demonstrate innovative ways to use natural language processing (NLP) to find and understand SDoH. Use cases span from an array of touchpoints to address patient care.
What will you learn?
During the webinar we will review how NLP can reduce manual effort and provide support accessing Social Determinants of Health data (SDoH) including:
- Learn why SDoH is essential in healthcare outcomes
- Discuss opportunities for mining unstructured data to identify SDoH
- Understand challenges around curating SDoH data quality
- Identifying issues in existing coding standards and the potential for NLP to augment organizational efforts
Who should attend?
This webinar will be of interest to Provider groups studying health inequities as well as Outcomes research leaders and teams who are looking to innovate and evolve their approaches to SDoH and want to learn more about tangible methods to do so.