Philip Payne seminar

Описание: How are biomedical data science and informatics research helping to realise the potential of EHR technologies in creating an Learning Healthcare System?

00:00 Introduction by Daniel Capurro
44:05 Q & A

A Learning Health System (LHS) can be defined as an environment in which knowledge generation processes are embedded into daily clinical practice in order to continually improve the quality, safety, and outcomes of healthcare delivery.
While still largely an aspirational goal, the promise of the LHS is a future in which every patient encounter is an opportunity to learn and improve that patient’s care, as well as the care their family and broader community receives.
The foundation for building such an LHS can and should be the Electronic Health Record (EHR), which provides the basis for the comprehensive instrumentation and measurement of healthcare services, as well as a means of delivering new evidence at the patient- and population levels.
While much has been written about the challenges associated with the use of current EHRs, the promise of these technology platforms remains vast and mostly under-realized.
In this presentation, we will explore the ways in Biomedical Data Science and Informatics research are helping to realize the potential of EHR technologies in the context of creating an LHS, from the optimization of workflow and human factors, to the generation of reproducible and systematic clinical phenotypes, to the delivery of emergent knowledge to both providers and patients via advance clinical decision support systems.

Philip Payne is the Janet and Bernard Becker Professor and founding Director of the Institute for Informatics at Washington University in St Louis. He is also the Associate Dean for Health Information and Data Science and Chief Data Scientist for the Washington University School of Medicine, while holding additional appointments as a Professor of Medicine and Computer Science and Engineering. Dr. Payne is an internationally recognized leader in the field of translational bioinformatics (TBI) and clinical research informatics (CRI).