Evidence map›Paper›PMID 40247904›Full record

ArticleLearning health systems2025

Setting the foundation for a national collaborative learning health system in acute TBI rehabilitation: CARE4TBI Year 1 experience.

Cynthia L Beaulieu, Jennifer Bogner, Chad Swank, Kimberly Frey, Mary K Ferraro, Candace Tefertiller, Timothy R Huerta, John D Corrigan, Erinn M Hade

Abstract read
In one paragraph

Article in Learning health systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Cynthia L BeaulieuDepartment of Physical Medicine and Rehabilitation The Ohio State University College of Medicine Columbus Ohio USA.ORCID https://orcid.org/0000-0002-4325-5578
Jennifer BognerDepartment of Physical Medicine and Rehabilitation The Ohio State University College of Medicine Columbus Ohio USA.
Chad SwankBaylor Scott & White Research Institute, Baylor Scott & White Institute for Rehabilitation Dallas Texas USA.
Kimberly FreyDepartment of Speech-Language Pathology Craig Hospital Englewood Colorado USA.
Mary K FerraroMoss Rehabilitation Research Institute, Jefferson Health Elkins Park Pennsylvania USA.
Candace TefertillerResearch Department Craig Hospital Englewood Colorado USA.
Timothy R HuertaDepartment of Family and Community Medicine The Ohio State University College of Medicine Columbus Ohio USA.
John D CorriganDepartment of Physical Medicine and Rehabilitation The Ohio State University College of Medicine Columbus Ohio USA.
Erinn M HadeDepartment of Population Health, Division of Biostatistics New York University Grossman School of Medicine New York New York USA.

Funding

Comparing Treatment Approaches to Promote Inpatient Rehabilitation Effectiveness for Traumatic Brain Injury (CARE 4 TBI)UH3NS117844 · NINDS · OHIO STATE UNIVERSITY · PI JENNIFER A BOGNER, Cynthia L. Beaulieu · 2023 to 2026
$9.5M
Comparing Treatment Approaches to Promote Inpatient Rehabilitation Effectiveness for Traumatic Brain Injury (CARE 4 TBI)UG3NS117844 · NINDS · OHIO STATE UNIVERSITY · PI BEAULIEU, CYNTHIA L., BOGNER, JENNIFER A · 2021 to 2022
$5.0M
NINDS NIH HHS UG3 NS117844NINDS NIH HHS UH3 NS117844
6 · The paper itself

Abstract

Introduction: 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. Methods: 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. Results: 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. Discussion: 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.

Indexed as

brain injuryelectronic medical recordsevidence‐based practicelearning health systemsrehabilitation

Identifiers

PMID40247904
PMCPMC12000765

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.