Evidence map›Paper›PMID 27170908›Full record

ArticleIEEE journal of translational engineering in health and medicine2015

Integration of New Technology for Research in the Emergency Department: Feasibility of Deploying a Robotic Assessment Tool for Mild Traumatic Brain Injury Evaluation.

Vignesh Subbian, Jonathan J Ratcliff, Jason M Meunier, Joseph J Korfhagen, Fred R Beyette, George J Shaw

Abstract read
In one paragraph

Article in IEEE journal of translational engineering in health and medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  5. Article
  6. Article
  7. Wearable Improved Vision System for Color Vision Deficiency Correction.IEEE journal of translational engineering in health and medicine · 2017
    Article
  8. 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

6 authors.

Vignesh Subbian
Jonathan J Ratcliff
Jason M Meunier
Joseph J Korfhagen
Fred R Beyette
George J Shaw

Funding

TrainingU54EB007954 · NIBIB · UNIVERSITY OF CINCINNATI · PI BEYETTE, FRED RICHARD · 2007 to 2011
$9.4M
NIBIB NIH HHS U54 EB007954
6 · The paper itself

Abstract

unlabelledThe objective of this paper is to demonstrate the effective deployment of a robotic assessment tool for the evaluation of mild traumatic brain injury (mTBI) patients in a busy, resource-constrained, urban emergency department (ED).

methodsFunctional integration of new robotic technology for research in the ED presented several obstacles that required a multidisciplinary approach, including participation from electrical and computer engineers, emergency medicine clinicians, and clinical operations staff of the hospital. Our team addressed many challenges in deployment of this advanced technology including: 1) adapting the investigational device for the unique clinical environment; 2) acquisition and maintenance of appropriate testing space for point-of-care assessment; and 3) dedicated technical support and upkeep of the device. Upon successful placement of the robotic device in the ED, the clinical study required screening of all patients presenting to the ED with complaints of head injury. Eligible patients were enrolled and tested using a robot-assisted test battery. Three weeks after the injury, patients were contacted to complete follow-up assessments.

resultsAdapting the existing technology to meet anticipated physical constraints of the ED was performed by engineering a mobile platform. Due to the large footprint of the device, it was frequently moved before ultimately being fully integrated into the ED. Over 14 months, 1423 patients were screened. Twenty-eight patients could not be enrolled because the device was unavailable due to operations limitations. Technical problems with the device resulted in failure to include 20 patients. A total of 66 mTBI patients were enrolled and 42 of them completed both robot-assisted testing and follow-up assessment. Successful completion of screening and enrollment demonstrated that the challenges associated with integration of investigational devices into the ED can be effectively addressed through a collaborative patient-oriented research model.

conclusionEffective deployment and use of new robotic technology for research in an urban academic ED required significant planning, coordination, and collaboration with key personnel from multiple disciplines. Clinical Impact: A pilot clinical study on mTBI patients using the robotic device provided useful data without disrupting the ED workflow. Integration of this technology into the ED serves as an important step toward pursing active clinical research in an acute care setting.

Indexed as

Clinical engineeringemergency departmentneurological assessmenttechnology integration

Identifiers

PMID27170908
PMCPMC4848098

What OpenQuestion holds

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Registered trials

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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.