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

这项研究项目的资金是根据服务部门工程探索性研究（ESS）计划公告提供的。器官共享联合网络（UNOS）管理着全国器官捐赠和分配系统。当美国器官共享中心向接受移植的病人提供器官时，病人决定要么接受，要么继续等待。因此，手头的研究问题是：如果提供了一个器官，病人应该在什么时候决定接受它？这个问题具有重大的实际意义，因为这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，但所使用的方法也适用于其他器官。建模决策过程的关键问题是对患者可用信息的假设。在所有情况下，在提出建议时，肝脏的相关特征是已知的，病人的健康状况也是如此。不确定的是患者相对于等待名单上其他患者的排名，以及未来提供的时间。这个问题最简单的版本是活体供体存在的情况。然而，通常情况下，捐赠者都是尸体。在后一种情况下，肝脏供应是随机发生的，患者在不知道自己在等待名单上的相对位置的情况下相互“竞争”肝脏。这个研究项目将为活体捐献者和尸体捐献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”或其他一些目标。将开发一个模型，用于假设等候名单的组成是公开信息的情况。具体来说，reach团队将把这些情况制定为马尔可夫决策过程，并对所产生的最优策略进行数值和分析研究。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候名单的潜在价值。分析研究将确定在何种条件下最优政策具有吸引人的、一致的结构。值得注意的是，大多数现有文献侧重于从UNOS的角度对器官移植问题进行建模，而不是像本文所考虑的那样从患者的角度进行建模。然而，请注意，这项研究可能会对这种政策视角的研究产生影响，因为研究的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.