Literature Evaluation Table

This literature evaluation table summarizes articles on identifying surgical site infections in healthcare settings. It includes information on the author, journal, year published, research questions, design, setting/sample, methods, analysis, key findings, and recommendations. The articles cover topics such as the use of electronic health records, risk factors for surgical site infections, and the development of tools for assessing surgical site infections.

Literature Evaluation Table
Student Name:
Change Topic (2-3 sentences): Identifying surgical site infections in the healthcare settings
Criteria Article 1 Article 2 Article 3 Article 4
Author, Journal
(Peer-Reviewed),
and
Permalink or
Working Link to
Access Article
Grundmeier, R. W., Xiao, R.,
Ross, R. K., Ramos, M. J.,
Karavite, D. J., Michel, J.
J., ... & Coffin, S. E, Journal
of the American Medical
Informatics Association,
25(9), 1160-1166
https://www.ncbi.nlm.nih.go
v/pubmed/29982511
Chakravarthy M, Rangaswamy S,
George A, Anand T, Senthilkumar P,
Rose SA
J Patient Saf Infect Control
2017;5:73-7
http://www.jpsiconline.com/
text.asp?2017/5/2/73/223694
Martin, E. T., Kaye, K. S., Knott, C.,
Nguyen, H., Santarossa, M., Evans,
R., ... & Jaber, L.
infection control & hospital
epidemiology, 37(1), 88-99
https://www.shea-online.org/
index.php/journal-news/press-room/
press-release-archives/432-diabetes-
identified-as-a-risk-factor-for-
surgical-site-infections
Badia, J. M., A. L. Casey, N.
Petrosillo, P. M. Hudson, S. A.
Mitchell, and C. Crosby.
Badia, J. M., A. L. Casey, N.
Petrosillo, P. M. Hudson, S. A.
Mitchell, and C. Crosby
Journal of Hospital Infection,
96(1), 1-15.
https://www.ncbi.nlm.nih.gov/
pubmed/28410761
Article Title and
Year Published
Identifying surgical site
infections in electronic health
data using predictive
models., 2018
Risk stratification of surgical site
infection in a Tertiary Care Hospital:
A prospective case-control study.
2017
Diabetes and risk of surgical site
infection: a systematic review and
meta-analysis
2016
Impact of surgical site infection
on healthcare costs and patient
outcomes: a systematic review
in six European countries
2017
Research
Questions
(Qualitative)/Hy
pothesis
(Quantitative),
The objective of the study
was to prospectively validate
a rule for the detection of
cases for surgical site
infection in post ambulatory
The study aimed to identify factors
which are commonly associated with
surgical site infection for over a
period of two years in a tertiary
referral hospital.
The objective of the study is to
determine the independent
association between diabetes and
surgical site infections across
multiple surgical procedures
The study assessed and
evaluated on the evidence, cost
and quality of life burden of
surgical site infections in
various specialties in 6
© 2015. Grand Canyon University. All Rights Reserved.

and
Purposes/Aim of
Study
surgery. European countries
Design (Type of
Quantitative, or
Type of
Qualitative)
A qualitative study based on
electronic health record data.
Quantitative based Prospective study A qualitative based study based on
systematic reviews and meta-analysis
studies
A systematic review of studies
in electronic databases was
undertaken
Setting/Sample Ambulatory care surgical
facility. Surgical site
prediction rules were
obtained based on 30 months
of data. Models were
obtained with and without
the data.
The setting of the study was a tertiary
referral hospital in India
The studies used in this review were
obtained from pub med published
between 1985-2015
Studies were done in post-2005
in France, Germany, Italy,
Spain, Netherlands, and the UK
were included.
Methods:
Intervention/Inst
ruments
Regulated logistic regression
and random forests were
obtained from the data set.
The methodology applied involved
all surgical site infections for the
period of two years, where two sets
of data comprising of 10-12 patients
were utilized to identify weight risks
factor using logistic regression.
Meta-analysis based study Economic evaluations based on
cost-utility, cost minimization,
and a cost-benefit analysis was
performed
Analysis Surgical sites infections were
obtained from the data set.
Logistic regression was performed on
the two sets of data
Random effects met analysis
generated pooled estimates and meta-
regressions used to assess specific
sources of hetero generosity
The primary interest of focus
was direct and indirect health
care costs, cost drivers and the
related proxy outcomes.
Key Findings 234 surgeries were identified
with surgical site infection in
a group of 7910 surgeries
analyzed. An optimal
prediction rule was included
using a random forest model
with a sensitivity of 0.9 and a
positive predictive value of
After analysis, the stepwise
multivariate logistic analysis model
showed that body mass index,
preoperative duration, and utilization
of preoperative shower were
positively linked as predictors of
surgical site infection.
The meta-analysis found an
association of diabetes and SSI with
an odds ratio of 1.53 (95% pi). There
was observed high association
observed for cardiac surgery patients
with OR=2.03 (95% PI 1.3-4.05)
compared with other surgeries
There was limited evidence
found, however, SSI
continuously associated with
elevated costs compared to
uninfected patients. Various
studies reported longer periods
of stay in hospital, reoperation,
© 2017. Grand Canyon University. All Rights Reserved.

0.28 and readmission which
increased SSI mortality rate.
Recommendatio
ns
Electronic health records can
facilitate surgical site
infection having adequate
sensitivity and positive
predictive value.
The three factors that affect SSI
include BMI, preoperative stay and
preoperative antiseptic shower.
The results obtained support the
usage of diabetes as an independent
risks factor for SSI in multiple
surgeries types.
There was observed disparity in
terms of cost reporting,
however, there was a general
observance of high costs
associated with SSI.
Explanation of
How the Article
Supports
EBP/Capstone
Project
This article is beneficial for
evidence-based practice
through the use of available
electronic health records for
surveying surgical site
infections hence leading to
the minimized occurrence of
SSI among postoperative
patients.
As utilization in evidence-based
practice scores can be assigned to
patients based on various factors with
preoper5taive days, body mass index
and antiseptic shower being
positively associated with SSI. Thus
used as predictors.
As a capstone key knowledge,
diabetes is a key factor in assessing
the occurrence of SSI among patients
undergoing surgery. Thus as a nurse
there is a need to take precautionary
measures among patients with
diabetes.
This study is crucial in that it
lays the funding for the nursing
recommendation and advising
patients on SSI costs process
and the how stakeholders and
health care practitioners can do
in order to alleviate the health
care costs on readmissions of
SSI.
Criteria Article 5 Article 6 Article 7 Article 8
Author, Journal
(Peer-Reviewed),
and
Permalink or
Working Link to
Access Article
Macefield, Rhiannon C.,
Barnaby C. Reeves, Thomas K.
Milne, Alexandra Nicholson,
Natalie S. Blencowe, Melanie
Calvert, Kerry NL Avery et al
Journal of infection prevention
18, no. 4 (2017): 170-179.
https://journals.sagepub.com/
doi/abs/
Du, Mingmei, Meng Li, Kexin Liu,
Jijiang Suo, Yubin Xing, Bowei Liu,
Rui Huo, Chunping Chen, and Yunxi
Liu.
American journal of infection
control, 45(4), 430-432.
https://www.ncbi.nlm.nih.gov/
pubmed/28185667
Mueck, Krislynn M., and Lillian S.
Kao.
Surgical infections, 18(4), pp.440-
446.
https://www.liebertpub.com/doi/
full/10.1089/sur.2017.058
Kunutsor, S. K., M. R.
Whitehouse, A. W. Blom, and
A. D. Beswick
Epidemiology & Infection,
145(9), 1738-1749
https://www.cambridge.org/
core/journals/epidemiology-
and-infection/article/
systematic-review-of-risk-
prediction-scores-for-surgical-
© 2017. Grand Canyon University. All Rights Reserved.

10.1177/1757177416689724 site-infection-or-
periprosthetic-joint-infection-
following-joint-arthroplasty/
8887D57F7F5C8DC198B075
843B7FE628
Article Title and
Year Published
Development of a single,
practical measure of surgical site
infection (SSI) for a patient
report or observer completion.
2017
A real-time surgical site infections
surveillance mode to monitor surgery
classification− specific, hospital-
wide surgical site infections in a
Chinese tertiary hospital.
2017
Patients at High-Risk for Surgical
Site Infection
2017
A systematic review of risk
prediction scores for surgical
site infection or per prosthetic
joint infection following joint
arthroplasty
2017
Research
Questions
(Qualitative)/Hy
pothesis
(Quantitative),
and
Purposes/Aim of
Study
The aim of the study was to
develop a measure to identify
surgical sites infections after
being discharged from the
hospital.
The goal of the study was to expand
surveillance which captures hospital-
wide infections
The study assessed on high risks
patients through the subjection of
preoperative counseling, resource
utilization and modifying
perioperative care to improve on
outcomes.
The study aimed at
determining the progress for
development and validation of
high risks based models for
SSI using systematic review
study
Design (Type of
Quantitative, or
Type of
Qualitative)
A multi-stage phase qualitative
study
A quantitative based study assessing
hospital records and post-discharge
SSI and readmission
Meta-analysis study Qualitative study
Setting/Sample The assessment was undertaken
among patients and
professionals from key five
specialties drawn from UK
hospital institutions.
The study was undertaken in a
tertiary hospital in China having a
capacity of 3,800 beds with an
approximate capacity of 270 surgical
operations on a daily basis.
The study searched studies done on
the identification of high risks
patients.
The study assessed articles on
MEDLINE, Web of sciences,
Cochrane and EMBASE
databases
Methods: Questionnaire-based study The study utilized ICD-9-CM VOL 3 Thematic based assessment study The study utilized systematic
© 2017. Grand Canyon University. All Rights Reserved.

Intervention/Inst
ruments
surgical codes and the ICD 10
disease codes
review to assess studies done .
Analysis A multi-stage based study based
16 items score
SSI algorithms were run on a
computer
The study analyzed how high risks
patients are identified at the health
care institutions.
The study identified risks
scores ranging between 4-45.
The C-Index ranged from
0.56-0.74, while three scores
reporting discriminative
ability.
Key Findings The assessments of the existing
tools noted key 19 domains
effective for assessing SSIs.
Further refinement obtained 16
items which are easily
understood by patients and
observers
The new established surgical site
surveillance mode developed is
efficient in establishing rates of each
type of surgery among hospital-based
patients.
The study found out that surgical
patient can be identified based on
individual risk factors. Further, the
study proposes statistic models and
risks calculators are beneficial in the
prediction of infections in SSIs.
Risk models for hip and knee
arthroplasty surgery were
better off tool for use in
clinical set up for risks scores
while the rest were not ready
for use.
Recommendatio
ns
The study came up with a single
tool for assessing SSI patients.
The new developed SSM is relevant
in establishing the rates and trends of
SSI as per specific surgery
There exist multiple strategies for
patient identifications having a high
risk for SSI, however, there is no
strategy which is superior.
There is a need for a wide
based study to assess effective
predictive models for risk
scores identification.
Explanation of
How the Article
Supports
EBP/Capstone
The research article offers an
insightful assessment protocol
for SSI patients. The tool is
essential for nursing care in
assessing post discharge risks
for SSI infections and associated
care.
The tool developed is key in
assessing the prevalence of SSI in
hospital setups
The study is beneficial for
evidenced-based studies in that no
strategy is effective in SSI patient
identification, hence adopting various
mechanism is crucial for nursing
practice for patient identification
having high risks SSI.
The study offers an insight into
evidenced-based practice in
that there are no studies which
offer effective risks predictive
model for use in SSI, thus
combining various methods
can be helpful.
References
© 2017. Grand Canyon University. All Rights Reserved.

Badia, J. M., Casey, A. L., Petrosillo, N., Hudson, P. M., Mitchell, S. A., & Crosby, C. (2017). Impact of surgical site infection on healthcare costs
and patient outcomes: a systematic review in six European countries. Journal of Hospital Infection, 96(1), 1-15.
Chakravarthy, M., Rangaswamy, S., George, A., Anand, T., Senthilkumar, P., & Rose, S. A. (2017). Risk stratification of surgical site infection in
a Tertiary Care Hospital: A prospective case-control study. Journal of Patient Safety and Infection Control, 5(2), 73.
Du, M., Li, M., Liu, K., Suo, J., Xing, Y., Liu, B., ... & Liu, Y. (2017). A real-time surgical site infections surveillance mode to monitor surgery
classification− specific, hospital-wide surgical site infections in a Chinese tertiary hospital. American journal of infection control, 45(4),
430-432.
Grundmeier, R. W., Xiao, R., Ross, R. K., Ramos, M. J., Karavite, D. J., Michel, J. J., ... & Coffin, S. E. (2018). Identifying surgical site infections
in electronic health data using predictive models. Journal of the American Medical Informatics Association, 25(9), 1160-1166.
Kunutsor, S. K., Whitehouse, M. R., Blom, A. W., & Beswick, A. D. (2017). Systematic review of risk prediction scores for surgical site infection
or periprosthetic joint infection following joint arthroplasty. Epidemiology & Infection, 145(9), 1738-1749.
Macefield, R. C., Reeves, B. C., Milne, T. K., Nicholson, A., Blencowe, N. S., Calvert, M., ... & Blazeby, J. M. (2017). Development of a single,
practical measure of surgical site infection (SSI) for patient report or observer completion. Journal of infection prevention, 18(4), 170-
179.
Martin, E. T., Kaye, K. S., Knott, C., Nguyen, H., Santarossa, M., Evans, R., ... & Jaber, L. (2016). Diabetes and risk of surgical site infection: a
systematic review and meta-analysis. infection control & hospital epidemiology, 37(1), 88-99.
Mueck, K. M., & Kao, L. S. (2017). Patients at High-Risk for Surgical Site Infection. Surgical infections, 18(4), 440-446.
© 2017. Grand Canyon University. All Rights Reserved.