Christiana Care Health System, Value Institute, John H. Ammon Medical Education Center, Newark, DE, USA (MC, KDW).
Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN, USA (AK).
Med Decis Making. 2017 Nov;37(8):849-859. doi: 10.1177/0272989X17705636. Epub 2017 Apr 19.
The Operations Research Interest Group (ORIG) within the Society of Medical Decision Making (SMDM) is a multidisciplinary interest group of professionals that specializes in taking an analytical approach to medical decision making and healthcare delivery. ORIG is interested in leveraging mathematical methods associated with the field of Operations Research (OR) to obtain data-driven solutions to complex healthcare problems and encourage collaborations across disciplines. This paper introduces OR for the non-expert and draws attention to opportunities where OR can be utilized to facilitate solutions to healthcare problems.
Decision making is the process of choosing between possible solutions to a problem with respect to certain metrics. OR concepts can help systematically improve decision making through efficient modeling techniques while accounting for relevant constraints. Depending on the problem, methods that are part of OR (e.g., linear programming, Markov Decision Processes) or methods that are derived from related fields (e.g., regression from statistics) can be incorporated into the solution approach. This paper highlights the characteristics of different OR methods that have been applied to healthcare decision making and provides examples of emerging research opportunities.
We illustrate OR applications in healthcare using previous studies, including diagnosis and treatment of diseases, organ transplants, and patient flow decisions. Further, we provide a selection of emerging areas for utilizing OR.
There is a timely need to inform practitioners and policy makers of the benefits of using OR techniques in solving healthcare problems. OR methods can support the development of sustainable long-term solutions across disease management, service delivery, and health policies by optimizing the performance of system elements and analyzing their interaction while considering relevant constraints.
医学决策制定学会（SMDM）中的运筹学兴趣小组（ORIG）是一个多学科专业兴趣小组，专注于对医学决策制定和医疗保健提供采取分析方法。ORIG 希望利用与运筹学（OR）领域相关的数学方法，为复杂的医疗保健问题获得数据驱动的解决方案，并鼓励跨学科合作。本文面向非专业人士介绍运筹学，并提请注意可以利用运筹学来促进解决医疗保健问题的机会。
决策制定是指针对特定指标，在问题的各种可能解决方案之间进行选择的过程。OR 概念可以通过有效的建模技术，在考虑相关约束的情况下，帮助系统地改进决策制定。根据问题的不同，可以将运筹学（例如线性规划、马尔可夫决策过程）中的方法或从相关领域（例如统计学中的回归）派生的方法纳入解决方案中。本文强调了已应用于医疗保健决策制定的不同 OR 方法的特点，并提供了新兴研究机会的示例。
我们使用先前的研究示例来说明医疗保健中的 OR 应用，包括疾病的诊断和治疗、器官移植和患者流程决策。此外，我们还提供了利用 OR 的一些新兴领域。
及时向从业者和决策者通报使用 OR 技术解决医疗保健问题的好处是很有必要的。OR 方法可以通过优化系统要素的性能和分析它们的相互作用，同时考虑相关约束，为疾病管理、服务提供和卫生政策制定方面的可持续长期解决方案提供支持。
