Big data in organ transplantation: registries and administrative claims.

Big data in organ transplantation: registries and administrative claims.
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DOI:
10.1111/ajt.12777
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发表时间:
2014-08
期刊:
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
影响因子:
--
通讯作者:
Segev DL
Segev DL
中科院分区:
其他
文献类型:
--
作者:
Massie AB;Kucirka LM;Segev DL

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器官移植领域受益于研究人员可获得的大型,全面,特定于移植的国家数据集。除了广泛使用的基于OPTN的登记系统(UNOS和SRTR数据集)和USRDS数据集外,还有其他公开可用的国家数据集,这些数据集并非专门针对移植,但在移植领域一直未得到充分利用。特别令人感兴趣的是全国住院病人样本(NIS)和国家住院病人数据库(SID),由卫生保健研究和质量机构(AHRQ)制作。美国肾脏数据系统(USRDS)数据库提供了与肾移植研究相关的广泛数据。将公开可用的数据集与外部数据源(如私人索赔或药房数据)联系起来,为基于注册的研究提供了更多资源。虽然这些资源可以超越基于OPTN的注册表数据的某些限制,但它们也有自己的局限性,必须理解这些局限性以避免有偏见的推断。本综述讨论了美国现有的不同的基于注册的数据源,以及基于注册的研究的适当设计和实施。
The field of organ transplantation benefits from large, comprehensive, transplant-specific national datasets available to researchers. In addition to the widely-used OPTN-based registries (the UNOS and SRTR datasets) and USRDS datasets, there are other publicly available national datasets, not specific to transplantation, which have historically been underutilized in the field of transplantation. Of particular interest are the Nationwide Inpatient Sample (NIS) and State Inpatient Databases (SID), produced by the Agency for Healthcare Research and Quality (AHRQ). The United States Renal Data System (USRDS) database provides extensive data relevant to studies of kidney transplantation. Linkage of publicly available datasets to external data sources such as private claims or pharmacy data provides further resources for registry-based research. Although these resources can transcend some limitations of OPTN-based registry data, they come with their own limitations, which must be understood to avoid biased inference. This review discusses different registry-based data sources available in the United States, as well as the proper design and conduct of registry-based research.
融合了等待列表结果的例外和速率。
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