多中心姑息治疗队列研究的数据管理系统设计。
The Design of a Data Management System for a Multicenter Palliative Care Cohort Study.
机构信息
Justin Ingerman Center for Palliative Care (R.T.N., D.L.H., K.W.C., J.Y.B., C.F.), The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA; Data Science and Biostatistics Unit (R.T.N., H.K., H.G.), Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Justin Ingerman Center for Palliative Care (R.T.N., D.L.H., K.W.C., J.Y.B., C.F.), The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA; Division of General Pediatrics (D.L.H., J.Y.B., C.F.), The Children's Hospital of Philadelphia Philadelphia, Pennsylvania, USA.
出版信息
J Pain Symptom Manage. 2022 Jul;64(1):e53-e60. doi: 10.1016/j.jpainsymman.2022.03.006. Epub 2022 Mar 23.
CONTEXT
Prospective 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.
OBJECTIVE
To 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.
METHODS
The 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.
CONCLUSIONS
Investigators planning future multicenter prospective cohort studies can consider attributes of the data infrastructure we describe when designing their data management system.
背景
针对患有重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，在数据管理方面存在挑战。
目的
描述儿科姑息治疗研究网络共享数据和研究（SHARE）项目的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，特别考虑到未来研究的设计。
方法
SHARE 研究包括 2017 年 4 月至 2020 年 12 月期间在美国 7 家儿童医院招募的 643 名 PPC 患者和最多 2 名父母。在 24 个月的随访期间，通过 6 个时间点直接从父母或患者收集有关人口统计学、患者症状、照护目标和其他特征的数据，并将其电子存储在一个集中的位置。使用病历号码，将主要收集的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进行链接。数据基础设施的重要属性包括主要和行政数据的链接；多语言问卷的集中可用性；电子数据收集和存储系统；仪器完成的时间戳；以及用于跟踪入组的单独但相关的研究管理数据库。
结论
计划未来多中心前瞻性队列研究的研究人员在设计其数据管理系统时，可以考虑我们描述的数据基础设施属性。
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