PURPOSE: To discuss what “real” optimization is, what it isn’t, the various types of optimization methods including linear, nonlinear, dynamic and stochastic programming and the types of healthcare challenges that can be addressed. Session content draws upon material from the task force’s foundational paper.  It is a primer for administrators, healthcare professionals and researchers that strive to optimize healthcare delivery systems under constrained resource conditions. DESCRIPTION: The healthcare sector faces numerous challenges pertaining to achieving ideal clinical outcomes, managing scarce resources within institutions, identifying best payment models and determining policy solutions that do not compromise one entity for another, etc.  In common vernacular, “optimal” is often used to refer to any demonstrated superiority among a small set of alternatives in specific settings, without demonstrating optimality from a mathematical sense. This is a missed opportunity that could easily result in poor decisions and/or policy choices—e.g., selection of policies that are not proven to be mathematically optimal, and hence leading to inefficient use of resources.  By “optimal” we mean the best possible solution for a given problem given the complexity of the system inputs, outputs and outcomes -- within defined constraints.  Attendees will learn about the applicability and relevance to problems and research questions that health care administrators, professionals and researchers face, and how optimization can also inform quality improvement initiatives.  Join the task force members who have used optimization to further research and improve the practice of care delivery.