Beaulieu Cynthia L, Bogner Jennifer, Swank Chad, Frey Kimberly, Ferraro Mary K, Tefertiller Candace, Huerta Timothy R, Corrigan John D, Hade Erinn M
Department of Physical Medicine and Rehabilitation The Ohio State University College of Medicine Columbus Ohio USA.
Baylor Scott & White Research Institute, Baylor Scott & White Institute for Rehabilitation Dallas Texas USA.
Learn Health Syst. 2024 Dec 16;9(2):e10454. doi: 10.1002/lrh2.10454. eCollection 2025 Apr.
A learning health system (LHS) approach is a collaborative model that continuously examines, evaluates, and re-evaluates data eventually transforming it into knowledge. High quantity of high-quality data are needed to establish this model. The purpose of this article is to describe the collaborative discovery process used to identify and standardize clinical data documented during daily multidisciplinary inpatient rehabilitation that would then allow access to these data to conduct comparative effectiveness research.
CARE4TBI is a prospective observational research study designed to capture clinical data within the standard inpatient rehabilitation documentation workflow at 15 TBI Model Systems Centers in the US. Three groups of stakeholders guided project development: therapy representative work group (TRWG) consisting of frontline therapists from occupational, physical, speech-language, and recreational therapies; rehabilitation leader representative group (RLRG); and informatics and information technology team (IIT). Over a 12-month period, the three work groups and research leadership team identified the therapeutic components captured within daily documentation throughout the duration of inpatient TBI rehabilitation.
Data brainstorming among the groups created 98 distinct categories of data with each containing a range of data elements comprising a total of 850 discrete data elements. The free-form data were sorted into three large categories and through review and discussion, reduced to two categories of prospective data collection-session-level and therapy activity-level data. Twelve session data elements were identified, and 54 therapy activities were identified, with each activity containing discrete sub-categories for activity components, method of delivery, and equipment or supplies. A total of 561 distinct meaningful data elements were identified across the 54 activities.
The CARE4TBI data discovery process demonstrated feasibility in identifying and capturing meaningful high quantity and high-quality treatment data across multiple disciplines and rehabilitation sites, setting the foundation for a LHS coalition for acute traumatic brain injury rehabilitation.
学习型健康系统（LHS）方法是一种协作模式，它不断检查、评估和重新评估数据，最终将其转化为知识。建立该模型需要大量高质量的数据。本文旨在描述用于识别和标准化日常多学科住院康复期间记录的临床数据的协作发现过程，从而能够获取这些数据以进行比较效果研究。
CARE4TBI是一项前瞻性观察性研究，旨在在美国15个创伤性脑损伤（TBI）模型系统中心的标准住院康复文档工作流程中收集临床数据。三组利益相关者指导项目开发：治疗代表工作组（TRWG），由职业治疗、物理治疗、言语治疗和娱乐治疗的一线治疗师组成；康复领导代表组（RLRG）；以及信息学和信息技术团队（IIT）。在12个月的时间里，这三个工作组和研究领导团队确定了住院TBI康复期间日常文档中记录的治疗组成部分。
各小组之间的数据头脑风暴产生了98个不同的数据类别，每个类别包含一系列数据元素，总共850个离散数据元素。自由格式数据被分为三大类，通过审查和讨论，减少为两类前瞻性数据收集——会话级和治疗活动级数据。确定了12个会话数据元素，识别出54项治疗活动，每项活动包含活动组成部分、实施方法以及设备或用品的离散子类别。在这54项活动中总共确定了561个不同的有意义数据元素。
CARE4TBI数据发现过程证明了在多个学科和康复地点识别和获取有意义的大量高质量治疗数据的可行性，为急性创伤性脑损伤康复的LHS联盟奠定了基础。
