Stroke

Measurement

Quality Improvement and Implementation Science

Symposium

Transitions of Stroke Care Models using Big Data (602146)

Presenter(s)

• 

  Nneka Ifejika, MD MPH

  Section Chief of Stroke Rehabilitation, Associate Professor of Physical Medicine and Rehabilitation, Neurology and Neurotherapeutics and Clinical Sciences
  UT Southwestern Medical Center, Department of Physical Medicine and Rehabilitation
  Dallas, Texas

Moderator(s)

• 

  Marlene Vega, PsyD

  Assistant Professor PM&R
  UT Southwestern Medical Center
  Dallas, Ohio

There has been tremendous progress in stroke care but opportunities for improving rehabilitation care transitions remain. This
symposium will illustrate the use of Big Data applications to create probability models of post-stroke rehabilitation care, using data
from six primary and three comprehensive stroke centers within the Texas Health Resources/UT Southwestern Medical Center
(THR/UTSW) network. These stroke centers represent a cross sectional view of care, including community based hospitals, academic
medical centers, urban and rural locations. Our long-term goal is to streamline the post-acute rehabilitative care transfer process,
resulting in decongestion of acute stroke beds and decreased overall healthcare costs.

Learning Objectives:

• Review the impact of acute stroke treatments (e.g., tissue plasminogen activator therapy, endovascular revascularization therapy) on functional outcomes at 90 days.
• Identify gaps in rehabilitation knowledge from acute stroke hospitalization to the 90 day functional outcome assessment including limited standardization and variable practice settings.
• Evaluate the use of Big Data sets for cross utilization in outcomes based acute stroke and stroke rehabilitation research.