Constrained optimization methods are used by health care researchers to identify the best solution to an issue that has a number of potential approaches and constraints. In health care, for example, optimization methods have been used to determine what approaches offer the best outcomes for diagnosing diseases, designing clinical trials, and creating treatment algorithms.
“By ‘optimal,’ we refer to the best possible solution given the complexity of system inputs, outputs/outcomes, and constraints,” said the report’s lead author, William H. Crown, PhD, chief science officer of OptumLabs, Cambridge, MA, USA.
“Many health care problems have a common mathematical structure—for example, maximizing societal health care benefits subject to a budget constraint or identifying optimal treatment pathways for patients given their proximity to available services. Failing to identify a truly ‘optimal’ solution in such cases represents a missed opportunity to improve clinical outcomes for patients and economic efficiency in the delivery of care,” said Crown.
“Up to one-third of health care expenditure is wasted, producing no clinical benefit for patients,” noted senior author, Kalyan S. Pasupathy, PhD, Mayo Clinic, Rochester, MN, USA. “All stakeholders from patients to policy makers and physicians want to improve health care system efficiency. By treating patients optimally, we have the potential to improve population health and enhance the value associated with health care expenditure. For individual patients, this can translate to providing treatment with the most appropriate therapy in a timely manner. For physicians, this can help provide optimal health outcomes for their patients, enhance the performance of their medical practice, and offer more efficient health care delivery.”
This new ISPOR Good Practices for Outcomes Research Task Force Report explains how constrained optimization methods provide a means for identifying the best policy choice or clinical intervention given a specific goal and set of constraints. The article provides a comprehensive overview of the methodology, including: (1) definitions, key concepts, and the main steps in building an optimization model; (2) the types of problems where an optimal solution can be determined in real-world health applications; and (3) how to choose the appropriate optimization methods for these problems.
Additional information on the Optimization Methods in Health Care Delivery: Emerging Good Practices Task Force can be found here. The full, open-access article of the task force report can be found here.
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