A Learning Health System Infrastructure for Precision Rehabilitation After Stroke.
A Learning Health System Infrastructure for Precision Rehabilitation After Stroke.
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用于中风后精准康复的学习健康系统基础设施。
DOI：
10.1097/phm.0000000000002138
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发表时间：
2023
影响因子：
3
通讯作者：
Celnik,Pablo
中科院分区：
文献类型：
--
作者：
French,MargaretA;Daley,Kelly;Lavezza,Annette;Roemmich,RyanT;Wegener,StephenT;Raghavan,Preeti;Celnik,Pablo
脑卒中后的功能恢复和对康复干预的反应是高度可变的。了解这种可变性将促进中风的精确康复，使我们能够在正确的时间向正确的人提供有针对性的干预措施。利用大型、异构的数据集，例如那些通过临床护理产生并保存在电子健康记录中的数据集，可以导致对中风后变异性的理解。然而，由于数据质量、隐私问题和数据提取所需的资源，从电子健康记录中访问数据可能具有挑战性。因此，需要建立克服这些挑战的基础设施，并有助于建立一个学习型卫生系统，以实现中风后的精确康复。我们描述了精确康复数据存储库的创建，该存储库便于访问从电子健康记录中系统收集的数据，作为学习健康系统的一部分，以推动精确康复。具体来说，我们描述了(1)标准化功能评估文件，(2)获得监管批准，(3)定义患者队列，以及(4)为精确康复数据库提取数据的过程。在其他机构开发类似的基础设施可以帮助生成大型异构数据集，以推动中风后护理向精确康复方向发展，从而在高效的医疗保健系统中最大限度地发挥中风后功能。
Functional recovery and the response to rehabilitation interventions after stroke are highly variable. Understanding this variability will promote precision rehabilitation for stroke, allowing us to deliver targeted interventions to the right person at the right time. Capitalizing on large, heterogeneous data sets, such as those generated through clinical care and housed within the electronic health record, can lead to understanding of poststroke variability. However, accessing data from the electronic health record can be challenging because of data quality, privacy concerns, and the resources required for data extraction. Therefore, creating infrastructure that overcomes these challenges and contributes to a learning health system is needed to achieve precision rehabilitation after stroke. We describe the creation of a Precision Rehabilitation Data Repository that facilitates access to systematically collected data from the electronic health record as part of a learning health system to drive precision rehabilitation. Specifically, we describe the process of (1) standardizing the documentation of functional assessments,(2) obtaining regulatory approval,(3) defining the patient cohort, and (4) extracting data for the Precision Rehabilitation Data Repository. The development of similar infrastructures at other institutions can help generate large, heterogeneous data sets to drive poststroke care toward precision rehabilitation, thereby maximizing poststroke function within an efficient healthcare system.