ESS - Collaborative Research: Modelling the Patient's Perspective on Organ Acceptance

该研究项目的资金是根据工程服务部门（ESS）计划公告的探索性研究提供的。 器官共享联合网络（United Network for Organ Sharing，UNOS）负责管理国家器官捐献和分配系统。 当器官共享网络向移植患者提供器官时，患者决定接受它或继续等待。 因此，目前的研究问题是：如果提供器官，病人应该在什么时候决定接受？ 这个问题具有重大的实际意义，因为它是每年成千上万的人面临的生死攸关的决定，而且还在不断增加。 这项研究将只关注肝脏，但所使用的方法适用于其他器官。 对这一决策过程进行建模的关键问题是对患者可用信息的假设。 在所有情况下，肝脏的相关特征在提供报价时都是已知的，病人的健康也是如此。 不确定的是病人相对于等候名单上其他病人的排名，以及未来提供服务的时间。 这个问题最简单的版本是存在活体捐赠者的情况。 然而，供体通常是尸体。 在后一种情况下，肝脏供应随机发生，患者相互“竞争”肝脏，而不知道他们在等待名单上的相对位置。该研究项目将为活体捐赠者和尸体捐赠者的情况制定数学模型，其目标是最大化，例如，“质量调整后的预期寿命”或其他目标。 将为等候名单的组成是公开信息的假设情况制定一个模型。 具体来说，到达团队将制定这些情况作为马尔可夫决策过程，并从事数值和分析研究所产生的最佳政策。 数值研究将利用广泛的临床数据，确定将指导分析研究的模式，并允许研究人员探索公布等待名单的潜在价值。 分析研究将确定最优政策具有吸引人的、一致的结构的条件。 值得注意的是，大多数现有的文献都集中在从UNOS的角度来模拟器官移植问题，而不是从患者的角度来考虑。然而，请注意，这项研究可能会对这一政策视角的研究路线产生影响，因为其目标之一是研究涉及公布等候名单的政策变化。

Funding for this research project is provided under the Exploratory Research on Engineering the Service Sector (ESS) program announcement. The United Network for Organ Sharing (UNOS) manages the national organ donation and allocation system. When UNOS offers an organ to a transplant patient, the patient decides to either accept it or to continue waiting. The research question at hand is therefore: if offered an organ, when should a patient decide to accept it? This question is of great practical importance, as it is a life-or-death decision faced by thousands of people per year, and growing. This research will focus only on livers, however the methodology used is applicable to other organs. The key issue in modeling this decision process is the assumption made regarding the information available to the patient. In all cases, the pertinent characteristics of the liver are known at the time an offer is made, as is the patient's health. What is uncertain is the ranking of the patient relative to the other patients on the waiting list, and the timing of future offers. The simplest version of this problem is the case in which a living donor exists. Typically, however, donors are cadaveric. In the latter situation, liver offerings occur randomly and patients "compete" with each other for livers without knowing their relative position on the waiting list. This research project will formulate mathematical models for the living-donor as well as the cadaveric-donor situation, in which the objective is to maximize, for instance, "quality-adjusted life expectancy" or some other objective. A model will be developed for the hypothetical situation in which the composition of the waiting list is public information. Specifically, the reach team will formulate these situations as Markov decision processes and engage in numerical and analytical study of the resulting optimal policies. Numerical study will make use of extensive clinical data, identify patterns that will guide the analytical study, and allow the researchers to explore the potential value in publishing the waiting list. Analytical study will determine conditions under which the optimal policies have appealing, consistent structure. It is interesting to note that most of the existing literature focuses on modeling the organ transplant problem from UNOS's perspective, rather than from the patient's perspective as considered here. Note, however, that the research may have an impact on this policy-perspective line of research, since one of the objectives is to study the policy change that involves the publication of the waiting list.