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2019 HSR&D/QUERI National Conference Abstract

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4074 — The PREVENT Quality Improvement Program to Enhance Care for Veterans with Transient Ischemic Attack: An Example of VHA as a Learning Healthcare System

Lead/Presenter: Dawn Bravata,  COIN - Indianapolis
All Authors: Bravata DM (Precision Monitoring to Transform Care (PRISM) QUERI), Bravata DM (Precision Monitoring to Transform Care (PRISM), Quality Enhancement Research Initiative (QUERI); Center for Health Information and Communication; Department of Medicine, Indiana University School of Medicine) Myers LJ (Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI); Center for Health Information and Communication) Homoya BJ (Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI); Center for Health Information and Communication) Miech EJ (Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI); Center for Health Information and Communication; Department of Medicine, Indiana University School of Medicine) Rattray NA (Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI); Center for Health Information and Communication) Perkins AJ (Department of Biostatistics, Indiana University School of Medicine) Zhang Y (Department of Biostatistics, Indiana University School of Medicine) Myers J (Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI); Center for Health Information and Communication) Cheatham AJ (Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI); Center for Health Information and Communication) Damush TM (Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI); Center for Health Information and Communication; Department of Medicine, Indiana University School of Medicine)

Objectives:
Veterans with transient ischemic attack (TIA) are at high risk of recurrent vascular events. However, programs that emphasize timely management can reduce that risk by 70%. The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) project sought to develop and evaluate a quality improvement (QI) program aligned with Learning Healthcare System principles to improve TIA care.

Methods:
PREVENT development was based on: VA staff interviews, electronic quality measure validation; baseline quality of care assessment identified QI targets; and the literature. PREVENT includes five components: reporting system based on validated electronic measures; clinical programs that use existing VA infrastructure; staff education programs; protocols and templates; and QI support including a virtual collaborative. A stepped-wedge implementation and mixed-methods evaluation (e.g., interviews, QI activities, change in care quality) is underway at six VA sites.

Results:
Interim data demonstrate that PREVENT advances three aspects of a learning healthcare system. LEARNING FROM DATA: the PREVENT hub (unlike static performance dashboards) allows sites not only to examine their performance data, but also to interact with data to explore hypotheses, plan QI activities, and evaluate change over time. A patient identification tool provides sites with patient-level, actionable information to identify patients in real-time to ensure that every Veteran receives all the care they need. LEARNING FROM EACH OTHER: Site teams participate in monthly virtual collaborative calls to learn about relevant topics, share strategies for overcoming challenges to providing highest care quality, and cultivate a sense of community. PREVENT teams are multidisciplinary; providing opportunities to learn across disciplines. SHARING BEST PRACTICES: Facility-based teams share tools and best practices in a rich and growing library of diverse resources. Participating staff report that sharing a tool they develop may be useful to other facilities provides a strong sense of professional satisfaction and motivates them in their work.

Implications:
PREVENT is a positive example of a Learning Healthcare System in action with the VHA that features data sharing, knowledge-creation and evidence-based decision-making.

Impacts:
The PREVENT model may generalize to other clinical conditions in VHA where patient care spans settings and where care coordination across specialties is paramount.