The Design of a Data Management System for a Multicenter Palliative Care Cohort Study.
The Design of a Data Management System for a Multicenter Palliative Care Cohort Study.
复制标题
多中心姑息治疗队列研究数据管理系统的设计。
DOI：
10.1016/j.jpainsymman.2022.03.006
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发表时间：
2022
影响因子：
4.7
通讯作者：
Feudtner,Chris
中科院分区：
文献类型：
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作者：
Nye,RussellT;Hill,DouglasL;Carroll,KarenW;Boyden,JackelynY;Katcoff,Hannah;Griffis,Heather;Campos,Diego;Hall,Matt;Wolfe,Joanne;Feudtner,Chris
对患有严重疾病的个体及其家庭成员（如接受姑息治疗的儿童及其父母）的前瞻性队列研究在数据管理方面提出了挑战。目的描述儿童姑息治疗研究网络共享数据与研究（SHARE）项目数据管理系统的设计和经验教训，该项目是一项针对接受儿科姑息治疗（PPC）的儿童及其父母的多中心前瞻性队列研究，并描述该系统的重要属性，为未来研究的设计提供具体考虑。SHARE研究包括2017年4月至2020年12月在美国7家儿童医院登记的643名PPC患者及其至多两名父母。在24个月的随访期间，在6个时间点直接从父母或患者处收集有关人口统计学、患者症状、护理目标和其他特征的数据，并以电子方式存储在集中位置。使用医疗记录编号，将收集到的主要数据与包含诊断和程序代码及其他数据元素的行政住院数据相关联。数据基础设施的重要属性包括主要数据和管理数据的链接；集中提供多语文问卷；电子数据采集和存储系统；文书完成的时间戳；还有一个独立但相互关联的研究管理数据库，用于跟踪登记情况。在设计数据管理系统时，计划未来多中心前瞻性队列研究的研究者可以考虑我们所描述的数据基础设施的属性。
ContextProspective cohort studies of individuals with serious illness and their family members, such as children receiving palliative care and their parents, pose challenges regarding data management.ObjectiveTo describe the design and lessons learned regarding the data management system for the Pediatric Palliative Care Research Network's Shared Data and Research (SHARE) project, a multicenter prospective cohort study of children receiving pediatric palliative care (PPC) and their parents, and to describe important attributes of this system, with specific considerations for the design of future studies.MethodsThe SHARE study consists of 643 PPC patients and up to two of their parents who enrolled from April 2017 to December 2020 at seven children's hospitals across the United States. Data regarding demographics, patient symptoms, goals of care, and other characteristics were collected directly from parents or patients at 6 timepoints over a 24-month follow-up period and stored electronically in a centralized location. Using medical record numbers, primary collected data was linked to administrative hospitalization data containing diagnostic and procedure codes and other data elements. Important attributes of the data infrastructure include linkage of primary and administrative data; centralized availability of multilingual questionnaires; electronic data collection and storage system; time-stamping of instrument completion; and a separate but connected study administrative database used to track enrollment.ConclusionsInvestigators planning future multicenter prospective cohort studies can consider attributes of the data infrastructure we describe when designing their data management system.