5 The Application of Clinical Systems to the Study of Traumatic Brain Injury G.G. Walden University NURS 6051, Section 49, Transforming Nursing and Healthcare April 25, 2019 The Application of Clinical Systems to the Study of Traumatic Brain Injury An area of research that has always sparked a keen interest in me revolves around rehabilitation medicine. I used to volunteer at TIRR Memorial Hermann, a nationally known rehab facility that deals with patients in recovery from significant injuries. Their patient population includes persons recovering from a stroke, spinal cord injury, traumatic brain injury, and a multitude of other less common illnesses. Because of that passion, I am interested in how nursing technology has evolved to help patients recovering from traumatic brain injuries (TBI). This paper will summarize a brief literature search of five articles that apply clinical systems to TBI recovery. Informatics Database Caban and associates (2016) studied whether building a large-scale informatics database would facilitate collection of standardized clinical data and obtain trends of the longitudinal outcomes of service members diagnosed with mild TBI. The article written as a result of this study mentioned how the detailed clinical guidelines for treating mild TBI rely too heavily on behavior observations and subjective recollections (Caban et. al., 2016). Knowing there was a need for an informatics database, these researchers created one using a combination of several other electronic health records systems. This database will improve outcomes in TBI because it will provide immediate concrete information that is objective and can be used to determine treatment paths for new TBI patients. Prognosis Calculator In the article “The Aggressiveness of Neurotrauma Practitioners and the Influence of the IMPACT Prognostic Calculator,” researchers investigated how effective a prognosis calculator is improving outcomes for TBI patients. 154 medical professionals responded to a survey that specifically questioned them regarding the usefulness and effectiveness of the IMPACT prognosis calculator. The prognosis calculator is a clinical system that was created to assist with care planning for TBI patients. The calculator is supposed to provide an accurate estimate of the future prognosis of the patient so that doctors can know whether to use aggressive treatment strategies or not. Survey responses were collected using a research electronic data capture system and the responses were statistically analyzed using SPSS software (Letsinger, Rommel, Hirschi, Nirula, & Hawryluk, 2017). Although the IMPACT system is the most significant technological advances in modern TBI care, the results of this article reveal that physicians are not properly aware of the capabilities of this software (Lestinger et. al., 2017). Unfortunately, more medical professionals use it as a communication tool more than anything else. Assistive Technology for Cognition A ...

1. 5
The Application of Clinical Systems to the Study of Traumatic
Brain Injury
G.G.
Walden University
NURS 6051, Section 49, Transforming Nursing and Healthcare
April 25, 2019
The Application of Clinical Systems to the Study of Traumatic
Brain Injury
An area of research that has always sparked a keen interest
in me revolves around rehabilitation medicine. I used to
volunteer at TIRR Memorial Hermann, a nationally known rehab
facility that deals with patients in recovery from significant
injuries. Their patient population includes persons recovering
from a stroke, spinal cord injury, traumatic brain injury, and a
multitude of other less common illnesses. Because of that
passion, I am interested in how nursing technology has evolved
to help patients recovering from traumatic brain injuries (TBI).
This paper will summarize a brief literature search of five
articles that apply clinical systems to TBI recovery.
Informatics Database
Caban and associates (2016) studied whether building a large-
scale informatics database would facilitate collection of
standardized clinical data and obtain trends of the longitudinal

2. outcomes of service members diagnosed with mild TBI. The
article written as a result of this study mentioned how the
detailed clinical guidelines for treating mild TBI rely too
heavily on behavior observations and subjective recollections
(Caban et. al., 2016). Knowing there was a need for an
informatics database, these researchers created one using a
combination of several other electronic health records systems.
This database will improve outcomes in TBI because it will
provide immediate concrete information that is objective and
can be used to determine treatment paths for new TBI patients.
Prognosis Calculator
In the article “The Aggressiveness of Neurotrauma Practitioners
and the Influence of the IMPACT Prognostic Calculator,”
researchers investigated how effective a prognosis calculator is
improving outcomes for TBI patients. 154 medical professionals
responded to a survey that specifically questioned them
regarding the usefulness and effectiveness of the IMPACT
prognosis calculator. The prognosis calculator is a clinical
system that was created to assist with care planning for TBI
patients. The calculator is supposed to provide an accurate
estimate of the future prognosis of the patient so that doctors
can know whether to use aggressive treatment strategies or not.
Survey responses were collected using a research electronic
data capture system and the responses were statistically
analyzed using SPSS software (Letsinger, Rommel, Hirschi,
Nirula, & Hawryluk, 2017). Although the IMPACT system is
the most significant technological advances in modern TBI care,
the results of this article reveal that physicians are not properly
aware of the capabilities of this software (Lestinger et. al.,
2017). Unfortunately, more medical professionals use it as a
communication tool more than anything else.
Assistive Technology for Cognition
A common clinical system is the use of assistive technology to
aid in TBI recovery. Wang and associates (2016) created a
survey to investigate user experiences with a portable assistive
technology for cognition (ATC). Researchers wanted to improve

3. the timing and effectiveness of activities of daily living in
veterans diagnosed with a TBI by teaching them how to use a
portable ATC. A smartphone and other similar technologies
qualify as being labeled an ATC. The three most challenging
areas of activities of daily living were remembering names and
faces, staying focused on a task, and locating items (Wang,
Ding, Teodorski, Mahajan, & Cooper, 2016). The results of this
study showed how the TBI participants were pleased with the
functionality of the portable ATC, even though they may have
faced some initial difficulty with learning how to work it. The
most significant part of the findings in this article was the fact
that TBI patients are able to improve their daily functioning
with the use of a portable ATC as it helps them to overcome
their cognitive limitations.
EEG
I would not be able to research clinical systems useful in
improving TBI outcomes without making mention of the
electroencephalogram. Most people are aware that an EEG is
used to measure electrical activity in the brain and to find any
potential issues. EEGs are especially significant in treating TBI
patients because the exaggerated neurological trauma creates a
perfect recipe for many complications. Disorganized electrical
activity can result in seizures which can further complicate
recovery. In the article “Is Routine Continuous EEG for
Traumatic Brain Injury Beneficial,” researchers wanted to
determine whether using a continuous EEG would improve
outcomes in TBI patient. With the use of continuous EEG, the
TBI patient remains connected to the machine for a specific
time period following their injury (Aquino et. al., 2017). The
time period is generally based on how critical the patient
remains. Unfortunately, researchers found less than a 5 percent
incidence of catching seizures after continuous EEG use. As a
result of such low incidences and the significant cost of a
continuous EEG, this clinical application was not recommended.
Chronic Phase MRI
The last article I found involved the use of magnetic resonance

4. imaging to predict outcomes in TBI patients. Ledig and
associates (2017) analyzed MRI images in TBI patients and
used segmentation to estimate brain measurements from both
acute and chronic patients. This article was very interesting to
read because the researchers used simple measurements to
predict the sizes of neurological structures. These measurements
then allowed them to determine whether a TBI patient would
have a favorable outcome. As previously mentioned, predictions
are significant in treating TBI patients because medical
professionals need to get an accurate account of how
aggressively they need to treat the injury. Being able to know
the appropriate size estimates of neurological organs, such as
the amygdala and hippocampus, will help physicians determine
just how swollen a patients’ brain is following their TBI. The
more swelling they are suffering from, the more aggressive the
treatment options should be.
Conclusion
Although this was a brief literature review, the usefulness of
clinical applications to improved treatment outcomes is a
popular area of research. A TBI is a life-changing injury with a
prognosis that gets poorer as the level of injury increases. More
aggressive initial treatments have been shown to improve
outcomes and create a better prognosis. Because of that, clinical
systems are needed to aid in this process. Nursing informatics is
all about making the best use of available technology, and
systems that target TBI recovery do just that.

5. References
Aquino, L., B.A., Kang, C. Y., M.D., Harada, M. Y., B.A., Ko,
Ara,M.D., M.P.H., Do-Nguyen,
A., Ley, E. J., M.D., . . . Alban, R. F., M.D. (2017). Is routine
continuous EEG for traumatic brain injury beneficial? The
American Surgeon, 83(12), 1433-1437. Retrieved from
https://ezp.waldenulibrary.org/login?url=https://search-
proquest-
com.ezp.waldenulibrary.org/docview/1991564748?accountid=14
872
Caban, J. J., PhD., Bonnema, A.,U.S.A.F.M.C., Bueno, E. R.,
M.B.A., DeGraba, T., M.D.,
Grammer, G.,M.C.U.S.A., Greenhalgh, W.,M.C.U.S.N., & Kass,
S.,M.C.U.S.N. (2016). A large-scale informatics database to
advance research and discovery of the effects of mild traumatic
brain injury. Military Medicine, 181(5), 11-22.
doi:http://dx.doi.org.ezp.waldenulibrary.org/10.7205/MILMED-
D-15-00138
Ledig, C., Kamnitsas, K., Koikkalainen, J., Posti, J. P., Takala,
R. S. K., Katila, A., . . . Rueckert,
D. (2017). Regional brain morphometry in patients with
traumatic brain injury based on acute- and chronic-phase
magnetic resonance imaging.PLoS One, 12(11)
doi:http://dx.doi.org.ezp.waldenulibrary.org/10.1371/journal.po
ne.0188152
Letsinger, J., Rommel, C., Hirschi, R., Nirula, R., & Hawryluk,
G. W. (2017). The
aggressiveness of neurotrauma practitioners and the influence of
the IMPACT prognostic calculator. PloS one, 12(8), e0183552.
Wang, J., M.S., Ding, D., Teodorski, E. E., M.S., Mahajan, H.
P., PhD., & Cooper, R. A., PhD.
(2016). Use of assistive technology for cognition among people
with traumatic brain injury: A survey study. Military

6. Medicine, 181(6), 560-566.
doi:http://dx.doi.org.ezp.waldenulibrary.org/10.7205/MILMED-
D-14-00704
University of Phoenix Material
Identifying Statistical Tests in the Literature Worksheet
Research in the University Library to find three empirical (those
containing data) research articles using one of the analytic
methods studied this week (i.e., z test, independent sample t
test, repeated measures t test).
Select articles that are of interest to you and include the
citations at the end of this document.
Fill out the following tables and answer each question in 1 to 2
sentences.
Title of Article: Workplace stress and associated factors among
healthcare professionals working
in public health care facilities in Bahir Dar City, Northwest
Ethiopia, 2017
Question
Answer
What is the null hypothesis (implied or explicitly stated)?
The null hypothesis is implied to be that gender, work shift,
illness, marital status, and work are not associated with
workplace stress.
What is the research hypothesis (implied or explicitly stated)?
Bonita 2
What was the type of analysis (z test, independent sample t test,
repeated measures t test) chosen, and why was it appropriate?

7. Bonita 3
Title of Article: Internet Risks: An Overview of Victimization
in Cyberbullying, Cyber Dating Abuse, Sexting, Online
Grooming and Problematic Internet Use
Question
Answer
What is the null hypothesis (implied or explicitly stated)?
Donette 4
What is the research hypothesis (implied or explicitly stated)?
Donette 5
What was the type of analysis (z test, independent sample t test,
repeated measures t test) chosen, and why was it appropriate?
Felicia 6
Title of Article: Prevalence and Risk Factors for Early
Motherhood Among Low-Income, Maltreated, and Foster Youth
Question
Answer
What is the null hypothesis (implied or explicitly stated)?
Felicia 7
What is the research hypothesis (implied or explicitly stated)?
Shonda 8
What was the type of analysis (z test, independent sample t test,
repeated measures t test) chosen, and why was it appropriate?
Shonda 9
Title
ABC/123 Version X
1
Identifying Statistical Tests in the Literature Worksheet

8. PSYCH/625 Version 5
1
Font, S. A., Cancian, M., & Berger, L. M. (2019). Prevalence
and Risk Factors for Early Motherhood
Copyright © XXXX by University of Phoenix. All rights
reserved.
Copyright © 2018 by University of Phoenix. All rights reserved.
among Low-Income, Maltreated, and Foster Youth.
Demography, 56(1), 261–284. Retrieved from
http://search.ebscohost.com/login.aspx?direct=true&AuthType=
shib&db=eoh&AN=1754527&site=eds-live&scope=site
Gebeyehu, S., & Zeleke, B. (2019). Workplace stress and
associated factors among healthcare
professionals working in public health care facilities in Bahir
Dar City, Northwest Ethiopia, 2017. BMC Research Notes,
12(1), 249. https://doi.org/10.1186/s13104-019-4277-1
Machimbarrena, J. M., Calvete, E., Fernández-González, L.,
Álvarez-Bardón, A., Álvarez-Fernández, L.,
& González-Cabrera, J. (2018). Internet Risks: An Overview of
Victimization in Cyberbullying, Cyber Dating Abuse, Sexting,
Online Grooming and Problematic Internet Use. International
Journal Of Environmental Research And Public Health, 15(11).
https://doi.org/10.3390/ijerph15112471
DataGenderAgeSupervisorTelecommuteCoworkersHappinessEn
gagementOverall
Rating12911278152324139101913911145812521258131271115
49233312781523631287151283139817134323881623221268142
31111751223811168142273127916229412891712641288161394
13981714011168142372117916237312971612932278151293129
71613021167132363139918130312771423021287152354128816

9. 12732399182312138816238112681423831288161342115611228
31299181292227815132422881613522399181353127714237212
89172293128816140412981722741187151272114610134112871
52341217512225222981722511156112292128816130312991813
0312781523522166122344139918
InformationVariableDescription of ValuesGender1= Male,
2=FemaleAgeChronological Age (in years)Relationship With
Direct Supervisor1 = negative relationship, 2 = neutral
relationship, 3 = positive relationship, 4 = great
relationshipTelecommute Schedule1= no ability to telecommute,
2 = able to telecommute at least 2 days per weekRelationship
With Coworkers1 = negative relationship, 2 = no relationship, 3
= positive relationshipWorkplace Happiness RatingScale 0-10, 0
= no happiness, 10 = completely happyWorkplace Engagement
RatingScale 0-10, 1 = no engagement, 10 = highly
engagedOverall Combined RatingScale 0-20, 0 = not happy and
not engaged, 20 = completely happy and highly engaged
1
2
3
4
5
6
7
8
9
A
B
C
D
Gender
Age
Supervisor
Telecommute
1

10. 29
1
1
2
32
4
1
1
39
1
1
1
25
2
1
1
27
1
1
2
33
3
1
2
36
3
1
1
28
3
1