Published Jun 2017
Crown, W, Buyukkaramikli B, Thokala P, et al. Constrained optimization methods in health services research—an introduction: report 1 of the ISPOR Optimization Methods Emerging Good Practices Task Force. Value Health. 2017;20(3):310-319.
Providing health services with the greatest possible value to patients
and society given the constraints imposed by patient characteristics,
health care system characteristics, budgets, and so forth relies heavily
on the design of structures and processes. Such problems are complex
and require a rigorous and systematic approach to identify the best
solution. Constrained optimization is a set of methods designed to
identify efficiently and systematically the best solution (the optimal
solution) to a problem characterized by a number of potential
solutions in the presence of identified constraints.
This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of “regular” and “severe” patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning.
Keywords: decision making, care delivery, modeling, policy.
Copyright © 2017, International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc.