Estimating the Causal Effect of Liver Allocation Policy Reflecting the Heterogeneity from Age and Geography
Estimating the Causal Effect of Liver Allocation Policy Reflecting the Heterogeneity from Age and Geography
批准号:
10738502
负责人:
Tomohiro Tanaka
金额:
$14.72万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2028-07-31
中文摘要
项目总结/摘要
肝移植的最佳器官分配政策仍然是一个关键但未满足的需求。公平而有效率
器官分配常常是不相容的目标。尽管移植界已经取得了进展,
多年来分配政策的变化,差异包括但不限于地理区域,年龄,
疾病类型持续存在。这是有问题的,因为器官代表着非常有限的资源(例如,在2020年,
中位移植前死亡率仍然很高[12.2每100等待名单年]),
和死亡的背景这一竞技场的一个主要挑战是,随机对照试验实际上是
不可能的尽管如此,基于证据的政策制定是必要的,因此难以准确评估
政策的因果效应。因此,必须使用以下方法来估计这些政策的因果影响:
观察数据和严格的方法,模仿随机试验。职业发展奖
旨在为申请人作为卫生政策/服务研究人员的职业生涯做好准备,重点是因果推理
该组织适用于慢性肝病/移植,其工作涉及各种健康差异。
这将通过申请人在慢性肝病和肝脏疾病方面扎实的临床领域专业知识得到加强。
移植这一目标将在爱荷华州大学的基础设施内实现。
医学和公共卫生学院通过(a)具体的研究生课程,(B)导师咨询
委员会,(c)精心挑选的会议和讲习班,以及(d)指导研究计划。具体
拟议研究的目的是估计(1)基本肝脏分配政策的因果效应
(the Share-35和Acuity Circle政策),这些政策为
用于确定以下医疗优先级的标准(终末期肝病模型评分; MELD)
分配,(2)现有肝脏分配优先规则对儿科和青少年候选人的因果影响
以及(3)制定一项政策,建议使捐赠者和接受者的年龄相匹配,
(捐助者-受援者年龄匹配)和潜在政策执行的成本效益,所有这些都在
美国(U.S.)。这些估计将严格计算使用自然和准实验,
一个覆盖因果推理框架,使用一个完善的全国性观察移植队列。
在这个职业发展奖结束时,候选人将做好充分的准备,成为一个独立的
在卫生政策、卫生服务、流行病学和因果推理方面具有专长的科学家
框架/计量经济学集中于医疗保健中的各种差异(即,种族,性别,年龄,地域,
社会经济因素和疾病类型),具有慢性肝病(包括肝病)的特定专业知识
移植我们的研究结果将为美国现行肝脏分配政策的修订提供信息,
未来的研究旨在了解指导慢性肝病/肝脏的健康政策的因果影响
移植,这将构成候选人的第一个R 01提交的基础。
英文摘要
Project Summary / Abstract
An optimal organ allocation policy for liver transplantation remains a critical yet unmet need. Fair and efficient
organ allocation are often incompatible goals. Although the transplant community has made incremental
changes to allocation policies over the years, disparities including, but not limited to, geographic region, age,
and disease type persist. This is problematic, as organs represent severely limited resources (e.g., In 2020,
median pretransplant mortality rate remained high [12.2 per 100 waiting list-years]) that are allocated in a life-
and-death context. One major challenge in this arena is that randomized controlled trials are virtually
impossible. Nevertheless, evidence-based policy making is necessary, making it difficult to accurately assess
the causal effects of policies. Thus, it is essential to estimate the causal effects of these policies using
observational data and rigorous methods that emulate the randomized trial. This Career Development Award
aims to prepare the applicant for a career as a health policy/services researcher focusing on causal inference
applied to chronic liver diseases / transplantation and whose work addresses a variety of health disparities.
This will be strengthened by the applicant’s solid clinical domain expertise in chronic liver disease and liver
transplantation. This goal will be accomplished within the infrastructure of the University of Iowa College of
Medicine and College of Public Health through (a) specific graduate coursework, (b) a Mentorship Advisory
Committee, (c) carefully selected conferences and workshops, and (d) a mentored research plan. The specific
aims of the proposed studies are to estimate (1) the causal effects of the fundamental liver allocation policies
(the Share-35 and the Acuity Circle policies), which designate different geographic boundaries and cutoffs for
the criterion (Model of End-stage Liver Disease score; MELD) that is used to determine medical priority for
allocation, (2) the causal effect of existing liver allocation priority rules in pediatric and adolescent candidates
and (3) the potential causal impact of formulating a policy proposing to match the age of donors and recipients
(donor-recipient age matching) and the cost-effectiveness of the potential policy implementation, all in the
United States (U.S.). These estimates will be computed rigorously using natural- and quasi-experiments with
an overlying causal inference framework, using a well-established nationwide observational transplant cohort.
At the end of this Career Development Award, the candidate will be well-prepared to become an independent
scientist with expertise in health policy, health services, epidemiology, and causal inference
frameworks/econometrics focused on various disparities in healthcare (i.e., race, gender, age, geography,
socioeconomic factors, and disease type), with specific expertise in chronic liver disease including liver
transplantation. Our study findings will inform revisions to the current liver allocation policy in the U.S. and
future studies designed to understand the causal effects of health policies guiding chronic liver disease/liver
transplantation, which will form the foundation of the candidate's first R01 submission.
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