Review Appraisal - Nursing Essays

Hi I need help with an assignment for a systematic review appraisal and qualitative review appraisal I will attach 6 total documents 2 are labeled example and 2 are labeled Qualitative Review template form and systematic Review template form you will use and the 2 articles are the articles that goes with each appraisal the systematic article with the systematic appraisal form and the qualitative article I have attached with the qualitative appraisal form. just use the examples as a guide to fill out the templates. Just wanna make it clear that two separate templates need to be filled out the two I have attached below each based on each article.

APPENDIX E
Appraisal Guide
Findings of a Qualitative Study
Citation:
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
Synopsis
What experience, situation, or subculture does the researcher seek to understand?
Does the researcher want to produce a description of an experience, a social process, or an event,
or is the goal to generate a theory?
How was data collected?
How did the researcher control his or her biases and preconceptions?
Are specific pieces of data (e.g., direct quotes) and more generalized statements (themes,
theories) included in the report?
What are the main findings of the study?
Credibility
Is the study published in a source
that required peer review?
Yes
No
Not clear
Were the methods used appropriate
to the study purpose?
Yes
No
Not clear
Was the sampling of observations or
interviews appropriate and varied
enough to serve the purpose of the study?
Yes
No
Not clear
*Were data collection methods
effective in obtaining in-depth data?
Yes
No
Not clear
Did the data collection methods
avoid the possibility of oversight,
underrepresentation, or
overrepresentation from certain
types of sources?
Yes
No
Not clear
Were data collection and analysis
intermingled in a dynamic way?
Yes
No
Not clear
Brown
APP E-1
*Is the data presented in ways that
provide a vivid portrayal of what was
experienced or happened and its
context?
Yes
No
Not clear
*Does the data provided justify
generalized statements, themes,
or theory?
Yes
No
Not clear
ARE THE FINDINGS CREDIBLE?
Yes All
Yes Some
No
Clinical Significance
*Are the findings rich and informative?
Yes
No
Not clear
*Is the perspective provided
potentially useful in providing
insight, support, or guidance
for assessing patient status
or progress?
Yes
Some
No
ARE THE FINDINGS
CLINICALLY SIGNIFICANT?
Yes All
Yes Some
Not clear
No
* = Important criteria
Comments
___________________________________________________________________________
___________________________________________________________________________
APP E-2
Brown
APPENDIX C
Appraisal Guide
Conclusions of a Systematic Review with Narrative Synthesis
Citation:
____________________________________________________________________________
____________________________________________________________________________
____________________________________________________________________________
Synopsis
What organization or persons produced the systematic review (SR)?
How many persons were involved in conducting the review?
What topic or question did the SR address?
How were potential research reports identified?
What determined if a study was included in the analysis?
How many studies were included in the review?
What research designs were used in the studies?
What were the consistent and important across-studies conclusions?
Credibility
Was the topic clearly defined?
Yes
No
Not clear
Was the search for studies and other
evidence comprehensive and unbiased?
Yes
No
Not clear
Was the screening of citations for
inclusion based on explicit criteria?
Yes
No
Not clear
*Were the included studies assessed
for quality?
Yes
No
Not clear
Were the design characteristics and
findings of the included studies displayed
or discussed in sufficient detail?
Yes
No
Not clear
*Was there a true integration (i.e., synthesis) of the findings—not
merely reporting of findings from
each study individually?
Yes
No
Not clear
Brown
APP C-1
*Did the reviewers explore why differences
in findings might have occurred?
Yes
No
Not clear
Did the reviewers distinguish between
conclusions based on consistent findings
from several good studies and those
based on inferior evidence (number or quality)?
Yes
No
Not clear
Which conclusions were supported by
consistent findings from two or more
good or high-quality studies?
List
____________________________________________________________________________
____________________________________________________________________________
____________________________________________________________________________
ARE THE CONCLUSIONS
CREDIBLE?
Yes All
Yes Some
No
Clinical Significance
*Across studies, is the size of the
treatment or the strength of the
association found or the
meaningfulness of qualitative findings
strong enough to make a difference
in patient outcomes or experiences of care?
Yes
No
Not clear
Are the conclusions relevant to the
care the nurse gives?
Yes
No
Not clear
ARE THE CONCLUSIONS
CLINICALLY SIGNIFICANT?
Yes All
Yes Some
No
Applicability
Does the SR address a problem,
situation, or decision we are addressing in our setting?
Yes
No
Not clear
Are the patients in the studies or a
subgroup of patients in the studies
similar to those we see?
Yes
No
Not clear
What changes, additions, training, or
purchases would be needed to implement
and sustain a clinical protocol based
on these conclusions?
Specify and list
____________________________________________________________________________
APP C-2
Brown
____________________________________________________________________________
Is what we will have to do to implement
the new protocol realistically achievable
by us (resources, capability, commitment)?
How will we know if our patients are
benefiting from our new protocol?
Yes
No
Not clear
Specify
____________________________________________________________________________
____________________________________________________________________________
ARE THESE CONCLUSIONS
APPLICABLE TO OUR SETTING?
Yes All
Yes Some
No
SHOULD WE PROCEED TO DESIGN
A PROTOCOL INCORPORATING
THESE CONCLUSIONS?
Yes All
Yes Some
No
* = Important criteria
Comments
____________________________________________________________________________
____________________________________________________________________________
Brown
APP C-3
Interventions to reduce the incidence of medical error and its financ… health care systems: A systematic review of systematic reviews – PMC
2/15/24, 10:51 AM
As a library, NLM provides access to scientific literature. Inclusion in an NLM database does
not imply endorsement of, or agreement with, the contents by NLM or the National Institutes
of Health.
Learn more: PMC Disclaimer | PMC Copyright Notice
Front Med (Lausanne). 2022; 9: 875426.
PMCID: PMC9363709
Published online 2022 Jul 27. doi: 10.3389/fmed.2022.875426
PMID: 35966854
Interventions to reduce the incidence of medical error and its financial burden in health
care systems: A systematic review of systematic reviews
Ehsan Ahsani-Estahbanati, 1 Vladimir Sergeevich Gordeev, 2 , 3 and Leila Doshmangir
1,4,*
Abstract
Background and aim
Improving health care quality and ensuring patient safety is impossible without addressing medical er‐
rors that adversely aﬀect patient outcomes. Therefore, it is essential to correctly estimate the incidence
rates and implement the most appropriate solutions to control and reduce medical errors. We identified
such interventions.
Methods
We conducted a systematic review of systematic reviews by searching four databases (PubMed, Scopus,
Ovid Medline, and Embase) until January 2021 to elicit interventions that have the potential to decrease
medical errors. Two reviewers independently conducted data extraction and analyses.
Results
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
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Seventysix systematic review papers were included in the study. We identified eight types of interven‐
tions based on medical error type classification: overall medical error, medication error, diagnostic er‐
ror, patients fall, healthcare-associated infections, transfusion and testing errors, surgical error, and pa‐
tient suicide. Most studies focused on medication error (66%) and were conducted in hospital settings
(74%).
Conclusions
Despite a plethora of suggested interventions, patient safety has not significantly improved. Therefore,
policymakers need to focus more on the implementation considerations of selected interventions.
Keywords: medical error, financial burden, hospital, intervention, quality of care, public health
Introduction
A medical error is a preventable adverse eﬀect of medical care (“iatrogenesis”). It can be defined as the
“failure of a planned action to be completed as intended or the use of a wrong plan to achieve an aim”
(1). As the associated burden is evident, medical errors have drawn considerable attention from acade‐
mics, hospital managers, and major health stakeholders. Medical errors have a significant adverse im‐
pact on patients’ outcomes and workers’ mental health. They are associated with a considerable finan‐
cial burden and undermine public trust in the health system (2–4). Medical errors, including healthcarerelated adverse events, occur in 8–12% of hospitalisations in Europe (5). At least 50% of hospitalized
patients’ harm could be preventable (6). Overall, healthcare-associated infections incidence is estimated
at 4.1 million patients a year in Europe, with the four main types of error being urinary tract infections
(27%), lower respiratory tract infections (24%), surgical site infections (17%), and bloodstream infec‐
tions (10.5%) (5). In the US (2007), 1.7 million healthcare-associated infections occur annually. They
result in excess healthcare costs of $35.7–$45 billion for inpatient hospital services (7, 8).
The medical errors can be classified based on their content or “what went wrong” (e.g., medication,
surgical, transfusion, healthcare-associated infection) (9–15); location or “where did it happen” (e.g.,
intensive care unit, operation theater, emergency department, children’s ward) (15–18); staﬀ or “who
made an error” (e.g., doctor, pharmacists, nurse) (10, 19, 20); error’s severity or “how harmful was it”
(e.g., error, no harm, near miss) (21–25); and “who was aﬀected” (e.g., patient, family, medical staﬀ)
(26, 27). Depending on the type of medical errors, studies suggest various solutions, from simple activi‐
ties (e.g., hand hygiene to prevent healthcare-associated infection) to more complex ones such as using
technological instruments or methods to prevent retained surgical instruments errors (7, 15).
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Despite the ongoing eﬀorts to reduce and prevent the burden of medical errors and related patient harm,
global eﬀorts have not yet achieved substantial change over the past 15 years due to various reasons (6).
Unclear policies, insuﬃcient or unreliable data to drive patient safety improvements, unskilled health
care professionals, lack of organizational leadership capacity, and non-participation of patients and fam‐
ilies in the care process led to unsustainable and insignificant improvements in health care safety (2).
Hence the primary goal of this article was to conduct a systematic review of systematic reviews to elicit
interventions that can reduce medical errors or medical error costs in hospitals and analyse interven‐
tions implementation results where available. Specifically, we focused on interventions that can reduce
health care costs, patient’s harm and death, improve health services quality, patient’s satisfaction, and
safety.
Methods
Literature search and study selection
Inclusion criteria for articles considered in this review were as follows: (a) systematic reviews; (b) stud‐
ies published in English language; (c) studies on solutions regarding medical error reduction or medical
error costs; (d) studies on interventions in hospitals or the whole of the healthcare sector, which entered
the study regardless of whether these reviews were based on reported errors, an examination of medical
profiles, observational studies or other methods. We excluded studies (a) published in languages other
than English; (b) studies conducted in settings other than the hospital; (c) studies focused only on a spe‐
cific type of medical error/activity/patient subgroup, or a sporadic type of medical error (e.g., wrongsite surgery in neurosurgery); (d) studies focusing on a particular group of employees where generalis‐
ability to other groups would not be feasible (i.e., only nurses, physicians, pharmacists); (e) conference
abstracts, narrative reviews, editorial and other types of studies but systematic reviews; (f) studies relat‐
ed to adverse events only; and (g) studies with no eﬀect on medical errors.
Search strategy
To identify relevant interventions, we searched the four databases (PubMed, Scopus, Ovid Medline and
Embase) from Oct 1977 until January 2021 and selected English-only publications. Multiple keywords
related to medical errors were researched and customized for each database. We used the filters for
searching papers on interventions to reduce medical error to maximize the sensitivity of our literature
search. We did not make any limitations on the outcomes. Additionally, references from the included
systematic reviews were checked and added to selected studies. Our search strategy was adjusted for
each database accordingly. For example, following combination was used for Pubmed database:
((((((((((((((((medical errors[MeSH Terms] OR “recording error”[Title/Abstract]) OR “no harm”[Ti‐
tle/Abstract] OR “patient fall*”[Title/Abstract]) OR “hospital infection”[Title/Abstract]) OR “transfu‐
sion error”[Title/Abstract]) OR “prescription error”[Title/Abstract]) OR “prescribing error”[Title/Ab‐
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stract]) OR “CPR error”[Title/Abstract]))) OR “medication error”[Title/Abstract]) OR “near miss”[Ti‐
tle/Abstract]) OR “suicide”[Title/Abstract]) OR “sentinel event”[Title/Abstract]) OR “never event”[Ti‐
tle/Abstract]) AND systematic[sb]). An overview of the full search strategy can be found in Appendix
1.
Data extraction
Two researchers independently extracted data from selected reviews. A third reviewer resolved any dis‐
agreements between the two reviewers. The following data were extracted: author, year, aim of the
study, setting, medical error type, interventions, and the overall results if reported. Only reviews that
met our selection criteria were extracted and analyzed.
Data analysis
The interventions of reviews were classified based on the medical error types. We additionally checked
for the overlap between primary studies included in systematic reviews. Since there was no complete
overlap between the reviews, none of the studies were excluded.
Results
Search results
The initial search provided 2108 records (Figure 1). After eliminating duplicate papers, titles and ab‐
stract screening, 181 reviews underwent the full-text assessment. In total 76 reviews met the inclusion
criteria, 105 were excluded for various reasons (Figure 1).
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Figure 1
PRISMA flow diagram for the review process.
Characteristics of the included systematic reviews
More than half of systematic reviews (67%) were published between 2013 and 2020 (n = 51). 66% of
reviews were about medication error (n = 49), and 74% were related to all hospital settings (n = 56).
The included studies reported on interventions for eight types of medical errors: overall medical error
(13 interventions), medication error (37 interventions), patients’ fall (11 interventions), healthcare-asso‐
ciated infections (21 interventions), diagnostic errors (7 interventions), transfusion and testing errors (8
interventions), surgical errors (3 interventions), and patients’ suicide (13 interventions) (Table 1).
Table 2 provides an overview of the impact of interventions on medical error reduction by intervention
group. A more detailed overview of the impact of studies, including their aim, setting, and overall re‐
sults can be found in Supplementary Table 1.
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Table 1
Interventions to reduce medical error by medical error category.
Medical error category
Interventions groups
Number of
interventions
Overall medical error (1–10)
Medication error (4, 5, 7, 11–57)
Use of electronic systems
7
Process interventions
4
Patient-centered intervention
1
Inter-professional education
1
Use of electronic systems
10
Pharmacists and clinical pharmacist role
1
Process interventions
Leadership or managerial manners and strategies
19
Smart pumps impact
6
1
Patients’ fall (5, 58–62)
Education and professional skills
3
Methods/tools evaluating patients’ fall risk
3
Process and patient care programs
Hourly rounding programs
3
Organizational and workplace culture
1
1
Healthcare-associated infections (18, 21,
Caregivers’ education and behavioral change
42, 58, 61, 63–69)
interventions
4
Process interventions
8
Managerial and organizational interventions
5
Use of medication interventions
Environment/equipment cleaning
3
1
Diagnostic errors (5, 70, 71)
Digital and electronic interventions
3
Patient identification and checking
2
Quality improvement methodologies
2
Transfusion and testing errors (72, 73)
Identification of patients (labeling and barcoding)
8
Surgical errors (18, 42, 74, 75)
Use of checklists and counting materials
2
Use of radio-frequency identification technology
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Table 2
Impact of interventions on medical error reduction by intervention group.
Overall Medication Patients’ Healthcare- Diagnostic Transfusion Surgical Patients’
medical error
fall
error
associated
error
infections
Caregivers’ education
++2
and behavioral change
reviews (58,
interventions
64)
and testing
errors
suicide
errors
+ 2 reviews
(65, 69)
Digital and electronic
++1
review (5)
+ 1 review
(70)
Education and
++2
professional skills
reviews
(58, 59)
+1
review
(60)
Use of electronic
++2
+ + 12
systems
reviews
reviews (4,
(3, 4) + 22, 24–31,
2
56, 57)
reviews
+ 13
(1, 2)
reviews (5,
34, 35, 44–
53)
Environment/equipment
++ 1
cleaning
review (63)
Identification of
++ 1
patients (labeling and
review (72)
barcoding)
+1 review
(73)
++ eﬀective in reduction / significant reduction, + some evidence of reduction.
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Interventions based on medical error types
Overall medical error This group of interventions was not restricted to a specific medical error type. It
included four interventions groups (i.e., use of electronic systems, patient-centered intervention,
process interventions, and inter-professional education). In total, ten reviews focused on overall medical
errors (28–37) and included 257 primary studies (Table 1). Five reviews focused on the use of electron‐
ic systems to reduce overall medical error levels using health information systems, computerized
provider order entry systems combined with clinical decision support systems, diagnostic and clinical
decision-making aids, error-resistant systems, computer-enabled discharge communication, personal
digital assistants, human simulation training) (28–32). Four reviews presented the process interventions
such as failure mode and eﬀects analysis, proactive technique, systematic safety processes, teamwork
and communication training interventions, and reactive systematic safety processes in reducing risks,
medical errors and adverse events (32–34, 37). One study referred to a patient-centered intervention,
i.e., documentation through patient involvement and feedback on the medical file (35). Reeves et al.
focused on interprofessional education (36) (Supplementary Table 1).
Reviews confirmed that using electronic systems could reduce (28, 29) or eﬀectively and significantly
(30, 31) reduce medical errors. For example, Charles et al. (29) stated that computerized provider order
entry reduces medical error and adverse drug events. The eﬀect would be more when combined with
clinical decision support systems to alert healthcare providers of medical errors (29). Studies that fo‐
cused on other intervention groups [i.e., process interventions (32–34, 37), patient-centered interven‐
tion (35), and inter-professional education (36)] presented some evidence of their potential to reduce
medical errors (Table 2). For example, using process interventions minimizes risks and improves ser‐
vice quality (33). In contrast, interprofessional education could reduce medical errors and enhance be‐
havior culture in the emergency department (36).
Medication error This intervention group related to medication errors and specific subcategories (pre‐
scribing, dispensing, administering, transcription and dose errors). These interventions fell into five
groups: use of electronic systems, pharmacists and clinical pharmacist involvement in the treatment
process, process interventions, leadership or managerial manners, and strategies and smart pumps im‐
pact. Overall, 49 reviews focused on interventions to reduce medication errors. This was the most
prominent intervention category, including 1,380 primary studies (Table 1). Twentyfive reviews fo‐
cused on using electronic systems (14, 16, 31, 32, 38–58). Twelve reviews focused on pharmacists and
clinical pharmacist involvement in the treatment process (13, 17, 32, 41, 59–66). Five reviews presented
leadership or managerial manners interventions (12, 56, 67–69). The remaining 12 reviews stated
process interventions (9, 12, 32, 34, 67, 70–76), and two reviews focused on smart pumps impact (32,
77) (Table 2).
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Similarly to overall medical error interventions, reviews focusing on electronic systems provided evi‐
dence that they could reduce (14, 16, 32, 38–48) or eﬀectively and significantly (31, 49–58) reduce
medication errors. For example, the most significant results were noted for computerized provider order
entry in 96% error interception and 90% reduction of medication errors (41, 44). There was evidence
that leadership or managerial manners intervention could eﬀectively and significantly reduce medica‐
tion errors (12, 56, 67–69). For example, redesign of diabetes prescribing charts incorporating prescrib‐
ing guidelines, diabetes prescription error management pathway, and mandatory e-learning reduced
insulin prescription errors from 65 to 2% (67) (Table 2, Supplementary Table 1). Reviews on pharma‐
cists and clinical pharmacist involvement in the treatment process presented evidence of some to a very
eﬀective and significant reduction on medical errors. For example, pharmacists’ participation in medical
treatment leads to a 43% reduction in prescribing errors and a 27% reduction in overall medication er‐
rors (63, 64). Most reviews on process interventions had also shown that such intervention could eﬀec‐
tively and significantly reduce medication errors (9, 12, 34, 67, 70–74), with only a few (32, 75, 76, 78)
presenting only some evidence of medication error reduction. For example, double-checking reduce
medication error from 2.98 to 2.12 per 1,000 medication administered and dispensing error from 9.8 to
6 (73).
Patients’ fall This group of interventions focused on interventions that could reduce patients’ falls by
using four diﬀerent categories of interventions (professional skills and education, methods/tools evalu‐
ating patients’ fall risk, process and patient care programs, organizational and workplace culture). In
total, six reviews (10, 26, 27, 32, 79, 80) focused on fall prevention and included 14 primary studies.
Three reviews focused on using education and professional skills interventions (10, 27, 79). Two re‐
views presented using methods and tools evaluating patients’ fall risk (27, 32). Cumbler et al. reported
process and patient care programs as beneficial interventions (27). One study focused on hourly round‐
ing programs (80), and Braithwaite et al. presented organizational and workplace culture interventions
(26) (Table 2).
Based on the results of reviews, education and professional skills interventions eﬀectively reduced or
led to a significant reduction in patients’ falls (10, 27, 80), while another review showed some evidence
of a reduction in patients’ falls (79). For example, there were patients’ fall diﬀerences in intervention
groups vs. control groups through patient-centered interventions (180 in intervention group vs. 319 in
control group) (79). There was evidence that methods/tools evaluating patients’ fall risk intervention
could eﬀectively and significantly reduce medical errors (27), and other reviews showed that could re‐
duce patients’ falls (32). For example, using the Morse fall scale decreased falls (27). Two remaining
studies focused on eﬀectively and significantly reducing patients’ falls (27, 80), and the other had some
evidence of reduction (26). For example, staﬀ education, care planning, patient training in rehabilitation
and nutritionist support lead to a reduction in falls from 16.28 to 6.29 per 1,000 patient days (27) (
Table 2, Supplementary Table 1).
Healthcare-associated infections
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Twelve reviews and 382 primary studies focused on five groups of interventions that could reduce
healthcare-associated infections (caregivers’ educational and behavioral change interventions, process
interventions, managerial and organizational interventions, using medication interventions and environ‐
ment/equipment cleaning) (Table 1). Four reviews focused on the caregivers’ education and behavioral
changes (10, 81–83). Three reviews focused on process interventions (65, 72, 84). Four reviews pre‐
sented the managerial and organizational interventions (26, 69, 81, 83). Three reviews reported medica‐
tion interventions (65, 85, 86). Schabrun et al. focused on equipment cleaning (87) (Table 2).
Caregivers’ education and behavioral change eﬀectively reduced healthcare-associated infections (10,
81), and the other two reviews showed some evidence of a reduction in healthcare-associated infections
(82, 83). For example, hand-hygiene campaigns reduced nosocomial infection rates (median eﬀect
49%) (81). Boyd et al. presented an eﬀective or significant reduction in healthcare-associated infections
(72), and two reviews showed that these interventions could reduce healthcare-associated infections
(65, 84). For example, the Keystone intensive care unit intervention for central line-associated blood‐
stream infections and chlorhexidine for vascular catheter site care economically reduced healthcare-as‐
sociated infections (65). One review stated that managerial and organizational interventions are signifi‐
cant or eﬀective in reducing healthcare-associated infections (81), while three studies have some evi‐
dence on reducing healthcare-associated infections (26, 69, 83). For example, antibiotic stewardship,
antibiotic restriction, guidelines, education, and performance feedback showed a significant decrease
ranging from 13 to 82% (81). One review of medication interventions reported a significant decline
(28%) in surgical site infection using a chlorhexidine impregnated dressing that applied to the surgical
site (86). Another review demonstrated an eﬀective reduction (82.1%) in colony-forming units after
cleaning pieces of equipment with alcohol (87).
Diagnostic error
Three studies that included 68 primary studies focused on three intervention categories (digital and
electronic interventions, patient identification and checking and quality improvement methodologies)
that aﬀect diagnostic errors (2, 32, 88) (Table 1). Two studies presented the use of digital and electronic
interventions (2, 32). One study focused on the use of patient identification (2). Amaratunga et al. fo‐
cused on quality improvement methodologies (88). One review focused on digital and electronic inter‐
ventions showed a significant eﬀect of interventions to reduce diagnostic error. The other one presented
some evidence of diagnostic error reduction (2, 32). For example, clinical decision support systems and
a web-based diagnostic reminder system significantly reduced diagnostic errors (32). Zhou et al. (2)
presented some evidence of a reduction in diagnostic error using patient identification. For example, the
patient identification check, obtaining informed consent, verifying the correct side and site, and a final
check by the radiologist decreased the incidence rate of diagnostic error from 0.03% (9 of 32,982) to
0.005% (2). Another review reported some evidence of a reduction in diagnostic error within radiology
by lean and Six Sigma approaches as quality improvement methodologies (88).
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Transfusion and testing errors
Two reviews included 26 primary studies focused on the identification of patients (labeling and barcod‐
ing) intervention (11, 89) (Table 1). The results of Snyder et al.’s review was eﬀective in reducing trans‐
fusion and testing errors (89), and another review showed some evidence on reducing transfusion and
testing errors (11) (Table 2). For example, labeling significantly reduces testing errors, so the most ef‐
fective intervention in reducing transfusion and testing errors was barcoding systems, which reduced
2.26 errors to 0.17 errors per 10,000 specimens (89).
Surgical errors
Four reviews included 38 primary studies focused on two intervention groups to reduce surgical errors
(use of checklists and counting instruments and material and use of radio-frequency identification tech‐
nology) (15, 65, 72, 90) (Table 1). Three reviews reported using checklists and counting materials inter‐
ventions (65, 72, 90). Another review focused on radio-frequency identification technology (15) (
Table 2). Two reviews showed an eﬀective reduction in surgical errors (72, 90) while, Etchells et al.’s
review had some evidence related to reducing surgical errors (65). For example, using checklists (or
similar interventions) could reduce equipment errors in the operating room by 48.6% (90). One review
showed some evidence to reduce retained surgical instrument errors, reduce the risk of counting errors,
and improve workflow using radio-frequency identification technology (15) (Table 2).
Patients’ suicide
Two reviews included 112 primary studies focused on reducing patients’ suicide (91, 92) (Table 1). One
review focused on reducing absconding and engagement with patient’s family intervention (91). Doup‐
nik et al., focused on process and patient care interventions and contact interventions (92) (Table 2).
Bowers et al. reported measures to reduce absconding and engagement with patient’s family interven‐
tion, showed some evidence to reduce absconding without locking the door and engage with patients’
family problems to reduce patients’ suicide (91). Another review focused on process, and patient care
interventions and contact interventions showed significant reduction (pooled odds ratio, 0.69) in pa‐
tients’ suicide by using 11 interventions (i.e., telephone, postcard, letters, coordination between the
mental health care team, and follow up mental health care team) (92) (Supplementary Table 1, Table 2).
Discussion
We systematically reviewed systematic reviews for interventions to reduce medical errors in hospitals.
Studies related to preventing medication errors included approximately 35 interventions. We identified
21 groups of interventions falling into seven broader categories of medical errors. The least studied cat‐
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egory of medical errors was related to patients’ suicide and surgical errors. Our findings showed that
among 101 presented interventions, the use of electronic systems intervention group, was included in
most of the reviews (27 reviews). This group included interventions that reduce medication and overall
medical errors. Most interventions were related to the processing group (30 interventions). Also, this
group had three types of errors (overall medical error, medication error, and healthcare-associated in‐
fections). The most eﬀective interventions were related to medication errors among medical error types
(27 reviews) and electronic systems among intervention groups (12 reviews).
Patient safety has several requirements such as safe infrastructure, technologies and medical devices,
patient and staﬀ education, information, professional participation in patient safety programs, and en‐
suring that all individuals receive secure health services, regardless of where they are delivered. This
was reiterated in the resolution on “Global action on patient safety” in May 2019 (WHA72.6) (93). In
particular, the resolution requests the World Health Organization’s Director-General to formulate a
global patient safety action plan in consultation with the Member States, regional economic integration
organizations and all relevant stakeholders, including in the private sector. As stated in the resolution,
to achieve the highest level of patient safety and to be able to reduce medical error and adverse events,
one needs to recognize patient safety as a health priority in health sector policies and programs, collab‐
orate with other member states along with the improvement of national policies, programs, guidelines,
strategies and tools.
There are several ways, policies and procedures to identify medical errors. Diﬀerences in error identifi‐
cation methods aﬀect the incidence of errors and error reduction interventions. These methods include
voluntary reporting, direct observation, patient and family reporting, and retrospective and prospective
methods (cohort and cross sectional studies) and related techniques (e.g., failure mode, eﬀects analysis,
and root cause analysis) (94–99).
The most eﬀective interventions related to patient satisfaction referred to managerial and process inter‐
ventions that show patients do not have enough knowledge about medical issues. Process and adminis‐
trative interventions increase their satisfaction as a perceived issue (70, 80). Eﬀective interventions to
reduce costs and increase eﬃciency were related to using electronic systems and processes and manage‐
rial or leadership strategies (9, 12, 54, 70). For example, electronic distribution drug systems decreased
by €44,295 in a month (9). Eﬀective interventions related to reducing death referred to the use of elec‐
tronic systems and process interventions (16, 70). For example, commercial computerized provider or‐
der entry led to a 12% reduction in intensive care units mortality rates (16). Eﬀective interventions for
increasing health care quality were referred to as checklists and counting materials, environment/equip‐
ment cleaning, use of electronic systems, and process interventions (9, 54, 87, 90). Eﬀective interven‐
tions related to patient safety were associated with the use of electronic systems, process, education and
professional skills, methods/tools evaluating patients’ fall risk, and process and patient care interven‐
tions groups (9, 27, 34, 51, 53, 58).
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As we highlighted in our study findings, use of electronic systems has a wide eﬀect on reduction of
medical errors and related deaths, eﬃciency and eﬀectiveness of services, and improvement of patient
safety. Of course, when using electronic systems, like any other method, one must pay attention to its
specific limitations and considerations. For example, implementation of computerized prescription or‐
der entry can lead to wrong drug selection from drop-down menus (49). Nonetheless, computerized
prescription order entry systems are more eﬀective to detect medical errors when they are bundled with
clinical decision support systems, which has the potential to prevent errors of medication forms nearly
completely (29, 100). Simulation systems prevent iatrogenic risk related to medication errors, if the
program is well designed (14).
Our review has several limitations. One is that medical errors cover a very wide range of topics that
cannot be addressed in one review article. For example, topics that were left outside the scope of this
paper include error identification policies, procedures and methods, disclosure approaches, and inci‐
dence of medical errors. Another limitation is that we focused on the interventions in the hospital set‐
tings. Due to the high number of papers related to the eﬀect of interventions on medical error, we re‐
stricted our analysis to documents that reported the positive impact of the intervention on medical error
reduction. Also, our study was limited to systematic reviews that had diﬀerent focus; hence, metaanalyses were not possible.
Conclusion
Prevention of medical errors is vital in reducing patient’s harm and improving overall patient outcomes.
A review of the combined evidence of 73 systematic reviews found that a wide range of interventions
could be used to prevent and decrease of incidence of medical errors. Process and managerial interven‐
tions, and use of electronic systems had a critical role in medical error reduction.
Data availability statement
The original contributions presented in the study are included in the article/Supplementary material,
further inquiries can be directed to the corresponding author/s.
Author contributions
EA-E and LD conceived the basic and original idea, outlined the study, literature review, data acquisi‐
tion, data analysis, interpretation of data, and drafted the article. VS contributed to data acquisition,
data analysis, interpretation of data, and drafting and revising of manuscript. All authors participated in
the final design, revision of the manuscript, and have read and approved the manuscript.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
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Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial rela‐
tionships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those
of their aﬃliated organizations, or those of the publisher, the editors and the reviewers. Any product
that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed
or endorsed by the publisher.
Acknowledgments
This study forms Ph.D. research project of the primary author supported by the Tabriz University of
Medical Sciences, Tabriz, Iran.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/arti‐
cles/10.3389/fmed.2022.875426/full#supplementary-material
Click here for additional data file.(14K, docx)
Click here for additional data file.(68K, docx)
References
1. Donaldson MS, Corrigan JM, Kohn LT. To Err is Human: Building a Safer Health System. Vol. 6. Washington, DC: National
Academies Press; (2000). [PubMed] [Google Scholar]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
Page 14 of 23
Interventions to reduce the incidence of medical error and its financ… health care systems: A systematic review of systematic reviews – PMC
2/15/24, 10:51 AM
2. Zhou Y, Boyd L, Lawson C. Errors in medical imaging and radiography practice: a systematic review. J Med Imag Radiat Sci.
(2015) 46:435–41. 10.1016/j.jmir.2015.09.002 [PubMed] [CrossRef] [Google Scholar]
3. Heideveld-Chevalking A, Calsbeek H, Griﬃoen I, Damen J, Meijerink W, Wolﬀ A. Development and validation of a Selfassessment Instrument for Perioperative Patient Safety (SIPPS). BJS open. (2018) 2:381–91. 10.1002/bjs5.82 [PMC free article]
[PubMed] [CrossRef] [Google Scholar]
4. Andel C, Davidow SL, Hollander M, Moreno DA. The economics of health care quality and medical errors. J Health Care
Finance. (2012) 39:39. [PubMed] [Google Scholar]
5. Patient safety, Data and statisics: WHO Regional oﬃce for Europe . (2021). Available online at:
https://www.euro.who.int/en/health-topics/Health-systems/patient-safety/data-and-statistics (accessed January 29, 2021).
6. Patient safety, Overview (2021). Available online at: https://www.who.int/health-topics/patient-safety#tab=tab_1 (accessed
January 29, 2021).
7. Sreeramoju P. Preventing healthcare-associated infections: Beyond best practice. Am J Med Sci. (2013) 345:239–44.
10.1097/MAJ.0b013e31824435e6 [PubMed] [CrossRef] [Google Scholar]
8. Scott RD. The direct medical costs of healthcare-associated infections in US hospitals and the benefits of prevention. (2009).
[Google Scholar]
9. Ahtiainen HK, Kallio MM, Airaksinen M, Holmström AR. Safety, time and cost evaluation of automated and semi-automated
drug distribution systems in hospitals: a systematic review. Eur J Hospital Pharmacy. (2019). 10.1136/ejhpharm-2018-001791
[PMC free article] [PubMed] [CrossRef] [Google Scholar]
10. Coelho P. Relationship between nurse certification and clinical patient outcomes: a systematic literature review. J Nurs Care
Qual. (2019). 10.1097/NCQ.0000000000000397 [PubMed] [CrossRef] [Google Scholar]
11. Cottrell S, Watson D, Eyre TA, Brunskill SJ, Dorée C, Murphy MF. Interventions to reduce wrong blood in tube errors in
transfusion: A systematic review. Transfus Med Rev. (2013) 27:197–205. 10.1016/j.tmrv.2013.08.003 [PubMed] [CrossRef]
[Google Scholar]
12. Mikrani R, Naveed M, Mikrani A, Yasmeen S, Akabar M, Xiaohui Z. The impact of clinical pharmacy services in Nepal in
the context of current health policy: a systematic review. J Public Health. (2019). 10.1007/s10389-019-01042-y [CrossRef]
[Google Scholar]
13. Noormandi A, Karimzadeh I, Mirjalili M, Khalili H. Clinical and economic impacts of clinical pharmacists’ interventions in
Iran: a systematic review. DARU, J Pharmaceutical Sci. (2019) 27:361–78. 10.1007/s40199-019-00245-8 [PMC free article]
[PubMed] [CrossRef] [Google Scholar]
14. Sarfati L, Ranchon F, Vantard N, Schwiertz V, Larbre V, Parat S, et al.. Human-simulation-based learning to prevent
medication error: A systematic review. J Eval Clin Pract. (2019) 25:11–20. 10.1111/jep.12883 [PubMed] [CrossRef] [Google
Scholar]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
Page 15 of 23
Interventions to reduce the incidence of medical error and its financ… health care systems: A systematic review of systematic reviews – PMC
2/15/24, 10:51 AM
15. Schnock KO, Biggs B, Fladger A, Bates DW, Rozenblum R. Evaluating the impact of radio frequency identification retained
surgical instruments tracking on patient safety: literature review. J Patient Saf. (2017). 10.1097/PTS.0000000000000365
[PubMed] [CrossRef] [Google Scholar]
16. Prgomet M, Li L, Niazkhani Z, Georgiou A, Westbrook JI. Impact of commercial computerized provider order entry (CPOE)
and clinical decision support systems (CDSSs) on medication errors, length of stay, and mortality in intensive care units: A
systematic review and meta-analysis. J Am Med Inform Assoc. (2017) 24:413–22. 10.1093/jamia/ocw145 [PMC free article]
[PubMed] [CrossRef] [Google Scholar]
17. Cohen V, Jellinek SP, Hatch A, Motov S. Eﬀect of clinical pharmacists on care in the emergency department: A systematic
review. Am J Health-Syst Pharmacy. (2009) 66:1353–61. 10.2146/ajhp080304 [PubMed] [CrossRef] [Google Scholar]
18. Lucas AJ. Improving medication safety in a neonatal intensive care unit. Am J Health-Syst Pharm. (2004) 61:33–7.
10.1093/ajhp/61.1.33 [PubMed] [CrossRef] [Google Scholar]
19. Lee SE, Quinn BL. Incorporating medication administration safety in undergraduate nursing education: a literature review.
Nurse Educ Today. (2019) 72:77–83. 10.1016/j.nedt.2018.11.004 [PubMed] [CrossRef] [Google Scholar]
20. Owoc J, Manczak M, Tombarkiewicz M, Robert Olszewski R. Association between physician burnout and self-perceived
error: Meta-analysis. Eur J Prev Cardiol. (2019) 26:S57. 10.1177/2047487319860048 [CrossRef] [Google Scholar]
21. Mehtsun WT, Ibrahim AM, Diener-West M, Pronovost PJ, Makary MA. Surgical never events in the United States. Surgery.
(2013) 153:465–72. 10.1016/j.surg.2012.10.005 [PubMed] [CrossRef] [Google Scholar]
22. Omar I, Graham Y, Singhal R, Wilson M, Madhok B, Mahawar KK. Identification of common themes from never events data
published by NHS England. World J Surg. (2021) 45:697–704. 10.1007/s00268-020-05867-7 [PubMed] [CrossRef] [Google
Scholar]
23. Kim CW, Myung SJ, Eo EK, Chang Y. Improving disclosure of medical error through educational program as a first step
toward patient safety. BMC Med Educ. (2017) 17:1–6. 10.1186/s12909-017-0880-9 [PMC free article] [PubMed] [CrossRef]
[Google Scholar]
24. Wallis J, Fletcher D, Bentley A, Ludders J. Medical errors cause harm in veterinary hospitals. Front Veter Sci. (2019) 6:12.
10.3389/fvets.2019.00012 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
25. Benimana C, Small M, Rulisa S. Preventability of maternal near miss and mortality in Rwanda: a case series from the
University Teaching Hospital of Kigali (CHUK). PLoS ONE. (2018) 13:e0195711. 10.1371/journal.pone.0195711 [PMC free
article] [PubMed] [CrossRef] [Google Scholar]
26. Braithwaite J, Herkes J, Ludlow K, Testa L, Lamprell G. Association between organisational and workplace cultures, and
patient outcomes: Systematic review. BMJ Open. (2017) 7:e017708. 10.1136/bmjopen-2017-017708 [PMC free article]
[PubMed] [CrossRef] [Google Scholar]
27. Cumbler EU, Simpson JR, Rosenthal LD, Likosky DJ. Inpatient falls: defining the problem and identifying possible solutions.
Part I: An Evidence-Based Review. The Neurohospitalist. (2013) 3:135–43. 10.1177/1941874412470665 [PMC free article]
[PubMed] [CrossRef] [Google Scholar]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
Page 16 of 23
Interventions to reduce the incidence of medical error and its financ… health care systems: A systematic review of systematic reviews – PMC
2/15/24, 10:51 AM
28. Ahmadian L, Salehi Nejad S, Khajouei R. Evaluation methods used on health information systems (HISs) in Iran and the
eﬀects of HISs on Iranian healthcare: A systematic review. Int J Med Inform. (2015) 84:444–53. 10.1016/j.ijmedinf.2015.02.002
[PubMed] [CrossRef] [Google Scholar]
29. Charles K, Cannon M, Hall R, Coustasse A. Can utilizing a computerized provider order entry (CPOE) system prevent
hospital medical errors and adverse drug events? Perspect Health Inf Manage. (2014) 11:1b. [PMC free article] [PubMed]
[Google Scholar]
30. Motamedi SM, Posadas-Calleja J, Straus S, Bates DW, Lorenzetti DL, Baylis B, et al.. The eﬃcacy of computer-enabled
discharge communication interventions: A systematic review. BMJ Quality and Safety. (2011) 20:403–15.
10.1136/bmjqs.2009.034587 [PubMed] [CrossRef] [Google Scholar]
31. Prgomet M, Georgiou A, Westbrook JI. The Impact of Mobile Handheld Technology on Hospital Physicians’ Work Practices
and Patient Care: A Systematic Review. J Am Med Inform Assoc. (2009) 16:792–801. 10.1197/jamia.M3215 [PMC free article]
[PubMed] [CrossRef] [Google Scholar]
32. Dückers M, Faber M, Cruijsberg J, Grol R, Schoonhoven L, Wensing M. Safety and risk management interventions in
hospitals: A systematic review of the literature. Medical Care Research and Review. (2009) 66:90S–119S.
10.1177/1077558709345870 [PubMed] [CrossRef] [Google Scholar]
33. Asgari Dastjerdi H, Khorasani E, Yarmohammadian MH, Ahmadzade MS. Evaluating the application of failure mode and
eﬀects analysis technique in hospital wards: a systematic review. J Injury Violence Res. (2017) 9:51. 10.5249/jivr.v9i1.794 [PMC
free article] [PubMed] [CrossRef] [Google Scholar]
34. Damiani G, Pinnarelli L, Scopelliti L, Sommella L, Ricciardi W. A review on the impact of systematic safety processes for the
control of error in medicine. Med Sci Monitor. (2009) 15:RA157–RA66. [PubMed] [Google Scholar]
35. Vermeir P, Degroote S, Vandijck D, Van Tiggelen H, Peleman R, Verhaeghe R, et al.. The patient perspective on the eﬀects of
medical record accessibility: a systematic review. Acta Clinica Belgica: Int J Clin Laboratory Med. (2017) 72:186–94.
10.1080/17843286.2016.1275375 [PubMed] [CrossRef] [Google Scholar]
36. Reeves S, Perrier L, Goldman J, Freeth D, Zwarenstein M. Interprofessional education: Eﬀects on professional practice and
healthcare outcomes (update). Cochrane Datab System Rev. (2013) 2013:CD002213. 10.1002/14651858.CD002213.pub3 [PMC
free article] [PubMed] [CrossRef] [Google Scholar]
37. Alsabri M, Boudi Z, Lauque D, Roger DD, Whelan JS, Östlundh L, et al.. Impact of teamwork and communication training
interventions on safety culture and patient safety in emergency departments: a systematic review. J Patient Saf. (2020).
10.1097/PTS.0000000000000782 [PubMed] [CrossRef] [Google Scholar]
38. Eslami S, de Keizer NF, Abu-Hanna A. The impact of computerized physician medication order entry in hospitalized
patients–a systematic review. Int J Med Inform. (2008) 77:365–76. 10.1016/j.ijmedinf.2007.10.001 [PubMed] [CrossRef]
[Google Scholar]
39. Khajouei R, JasperS MWM. The impact of CPOE medication systems’ design aspects on usability, workflow and medication
orders a systematic review. Methods Inf Med. (2010) 49:3–19. 10.3414/ME0630 [PubMed] [CrossRef] [Google Scholar]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
Page 17 of 23
Interventions to reduce the incidence of medical error and its financ… health care systems: A systematic review of systematic reviews – PMC
2/15/24, 10:51 AM
40. Ammenwerth E, Schnell-Inderst P, Machan C, Siebert U. The eﬀect of electronic prescribing on medication errors and
adverse drug events: a systematic review. J Am Med Inform Assoc. (2008) 15:585–600. 10.1197/jamia.M2667 [PMC free article]
[PubMed] [CrossRef] [Google Scholar]
41. Acheampong F, Anto BP, Koﬀuor GA. Medication safety strategies in hospitals – A systematic review. Int J Risk Safety Med.
(2014) 26:117–31. 10.3233/JRS-140623 [PubMed] [CrossRef] [Google Scholar]
42. Kaushal R, Shojania KG, Bates DW. Eﬀects of computerized physician order entry and clinical decision support systems on
medication safety: A systematic review. Arch Intern Med. (2003) 163:1409–16. 10.1001/archinte.163.12.1409 [PubMed]
[CrossRef] [Google Scholar]
43. Manias E, Kusljic S, Wu A. Interventions to reduce medication errors in adult medical and surgical settings: a systematic
review. Ther Adv Drug Saf. (2020) 11:2042098620968309. 10.1177/2042098620968309 [PMC free article] [PubMed]
[CrossRef] [Google Scholar]
44. Shitu Z, Aung MMT, Kamauzaman THT, Bhagat V, Rahman AFA. Medication error in hospitals and eﬀective intervention
strategies: A systematic review. Res J Pharm Technol. (2019) 12:4669–77. 10.5958/0974-360X.2019.00804.7 [CrossRef]
[Google Scholar]
45. Keers RN, Williams SD, Cooke J, Walsh T, Ashcroft DM. Impact of interventions designed to reduce medication
administration errors in hospitals: A systematic review. Drug Safety. (2014) 37:317–32. 10.1007/s40264-014-0152-0 [PubMed]
[CrossRef] [Google Scholar]
46. Jia P, Zhang L, Chen J, Zhao P, Zhang M. The eﬀects of clinical decision support systems on medication safety: An overview.
PLoS ONE. (2016) 11:e0167683. 10.1371/journal.pone.0167683 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
47. Pawloski PA, Brooks GA, Nielsen ME, Olson-Bullis BA. A systematic review of clinical decision support systems for clinical
oncology practice. JNCCN J National Comprehensive Cancer Network. (2019) 17:331–8. 10.6004/jnccn.2018.7104 [PMC free
article] [PubMed] [CrossRef] [Google Scholar]
48. Bouaud J, Lamy JB, Section Editors for the IYSoDS . A medical informatics perspective on clinical decision support systems.
Findings from the yearbook 2013 section on decision support. Yearbook of Med Inform. (2013) 8:128–31. 10.1055/s-00381638844 [PubMed] [CrossRef] [Google Scholar]
49. Velez-Diaz-Pallares M, Perez-Menendez-Conde C, Bermejo-Vicedo T. Systematic review of computerized prescriber order
entry and clinical decision support. Am J Health Syst Pharm. (2018) 75:1909–21. 10.2146/ajhp170870 [PubMed] [CrossRef]
[Google Scholar]
50. Nuckols TK, Smith-Spangler C, Morton SC, Asch SM, Patel VM, Anderson LJ, et al.. The eﬀectiveness of computerized
order entry at reducing preventable adverse drug events and medication errors in hospital settings: A systematic review and metaanalysis. System Rev. (2014) 3:56. 10.1186/2046-4053-3-56 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
51. Ahmed Z, Garfield S, Jani Y, Jheeta S, Franklin BD. Impact of electronic prescribing on patient safety in hospitals:
Implications for the UK. Clin Pharmacist. (2016) 8:1–11. 10.1211/CP.2016.20201013 [CrossRef] [Google Scholar]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
Page 18 of 23
Interventions to reduce the incidence of medical error and its financ… health care systems: A systematic review of systematic reviews – PMC
2/15/24, 10:51 AM
52. Roumeliotis N, Sniderman J, Adams-Webber T, Addo N, Anand V, Rochon P, et al.. Eﬀect of Electronic Prescribing
Strategies on Medication Error and Harm in Hospital: a Systematic Review and Meta-analysis. J Gen Intern Med. (2019)
34:2210–23. 10.1007/s11606-019-05236-8 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
53. Ojeleye O, Avery A, Gupta V, Boyd M. The evidence for the eﬀectiveness of safety alerts in electronic patient medication
record systems at the point of pharmacy order entry: A systematic review. BMC Med Inform Decis Making. (2013) 13:1–10.
10.1186/1472-6947-13-69 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
54. Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, et al.. Systematic review: Impact of health information
technology on quality, eﬃciency, and costs of medical care. Ann Intern Med. (2006) 144:742–52. 10.7326/0003-4819-144-10200605160-00125 [PubMed] [CrossRef] [Google Scholar]
55. Devin J, Cleary BJ, Cullinan S. The impact of health information technology on prescribing errors in hospitals: a systematic
review and behaviour change technique analysis. Syst Rev. (2020) 9:275. 10.1186/s13643-020-01510-7 [PMC free article]
[PubMed] [CrossRef] [Google Scholar]
56. Yang C, Yang L, Xiang X, Tang Y, Wang H, Bobai N, et al.. Interventions assessment of prescription automatic screening
system in chinese hospitals: a systematic review. Drug Inf J. (2012) 46:669–76. 10.1177/0092861512454417 [CrossRef] [Google
Scholar]
57. Schedlbauer A, Prasad V, Mulvaney C, Phansalkar S, Stanton W, Bates DW, et al.. What evidence supports the use of
computerized alerts and prompts to improve clinicians’ prescribing behavior? J Am Med Inform Assoc. (2009) 16:531–8.
10.1197/jamia.M2910 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
58. Alanazi A, Alomar M, Aldosari H, Shahrani A, Aldosari B. The eﬀect of electronic medication administration records on the
culture of patient safety: a literature review. Studies Health Technol Inform. (2018) 251:223–6. 10.3233/978-1-61499-880-8-223
[PubMed] [CrossRef] [Google Scholar]
59. Poh EW, McArthur A, Stephenson M, Roughead EE. Eﬀects of pharmacist prescribing on patient outcomes in the hospital
setting: A systematic review. JBI Datab System Rev Implement Reports. (2018) 16:1823–73. 10.11124/JBISRIR-2017-003697
[PubMed] [CrossRef] [Google Scholar]
60. Bethishou L, Herzik K, Fang N, Abdo C, Tomaszewski DM. The impact of the pharmacist on continuity of care during
transitions of care: A systematic review. J Am Pharm Assoc. (2020) 60:163–77.e2. 10.1016/j.japh.2019.06.020 [PubMed]
[CrossRef] [Google Scholar]
61. Mekonnen AB, McLachlan AJ, Brien JAE. Pharmacy-led medication reconciliation programmes at hospital transitions: A
systematic review and meta-analysis. J Clin Pharm Ther. (2016) 41:128–44. 10.1111/jcpt.12364 [PubMed] [CrossRef] [Google
Scholar]
62. Chiewchantanakit D, Meakchai A, Pituchaturont N, Dilokthornsakul P, Dhippayom T. The eﬀectiveness of medication
reconciliation to prevent medication error: A systematic review and meta-analysis. Res Social Adm Pharm. (2020) 16:886–94.
10.1016/j.sapharm.2019.10.004 [PubMed] [CrossRef] [Google Scholar]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
Page 19 of 23
Interventions to reduce the incidence of medical error and its financ… health care systems: A systematic review of systematic reviews – PMC
2/15/24, 10:51 AM
63. Wang T, Benedict N, Olsen KM, Luan R, Zhu X, Zhou N, et al.. Eﬀect of critical care pharmacist’s intervention on
medication errors: a systematic review and meta-analysis of observational studies. J Crit Care. (2015) 30:1101–6.
10.1016/j.jcrc.2015.06.018 [PubMed] [CrossRef] [Google Scholar]
64. Naseralallah LM, Hussain TA, Jaam M, Pawluk SA. Impact of pharmacist interventions on medication errors in hospitalized
pediatric patients: a systematic review and meta-analysis. Int J Clin Pharm. (2020) 42:979–94. 10.1007/s11096-020-01034-z
[PubMed] [CrossRef] [Google Scholar]
65. Etchells E, Koo M, Daneman N, McDonald A, Baker M, Matlow A, et al.. Comparative economic analyses of patient safety
improvement strategies in acute care: a systematic review. BMJ Quality Safety. (2012) 21:448–56. 10.1136/bmjqs-2011-000585
[PubMed] [CrossRef] [Google Scholar]
66. Gillani SW, Gulam SM, Thomas D, Gebreigziabher FB, Al-Salloum J, Assadi RA, et al.. Role and services of pharmacist in
the prevention of medication errors: a systematic review. Curr Drug Saf. (2020). 10.2174/1574886315666201002124713
[PubMed] [CrossRef] [Google Scholar]
67. Bain A, Hasan SS, Babar ZUD. Interventions to improve insulin prescribing practice for people with diabetes in hospital: a
systematic review. Diabetic Med. (2019) 36:948–60. 10.1111/dme.13982 [PubMed] [CrossRef] [Google Scholar]
68. Schroers G. Characteristics of interruptions during medication administration: An integrative review of direct observational
studies. J Clin Nurs. (2018) 27:3462–71. 10.1111/jocn.14587 [PubMed] [CrossRef] [Google Scholar]
69. Wong CA, Cummings GG, Ducharme L. The relationship between nursing leadership and patient outcomes: A systematic
review update. J Nurs Manag. (2013) 21:709–24. 10.1111/jonm.12116 [PubMed] [CrossRef] [Google Scholar]
70. Ashcraft S, Bordelon C, Fells S, George V, Thombley K, Shirey MR. Interprofessional Clinical Rounding: Eﬀects on
Processes and Outcomes of Care. J Healthcare Quality. (2017) 39:85–94. 10.1097/JHQ.0000000000000039 [PubMed]
[CrossRef] [Google Scholar]
71. Wimpenny P, Kirkpatrick P. Roles and systems for routine medication administration to prevent medication errors in hospitalbased, acute care settings: a systematic review. JBI Libr Syst Rev. (2010) 8:405–46. 10.11124/jbisrir-2010-123 [PubMed]
[CrossRef] [Google Scholar]
72. Boyd JM, Wu G, Stelfox HT. The impact of checklists on inpatient safety outcomes: A systematic review of randomized
controlled trials. J Hospital Med. (2017) 12:675–82. 10.12788/jhm.2788 [PubMed] [CrossRef] [Google Scholar]
73. Alsulami Z, Conroy S, Choonara I. Double checking the administration of medicines: What is the evidence? A systematic
review. Arch Dis Childhood. (2012) 97:833–7. 10.1136/archdischild-2011-301093 [PubMed] [CrossRef] [Google Scholar]
74. McDowell SE, Mt-Isa S, Ashby D, Ferner RE. Where errors occur in the preparation and administration of intravenous
medicines: A systematic review and Bayesian analysis. Quality Safety Health Care. (2010) 19:341–5. 10.1136/qshc.2008.029785
[PubMed] [CrossRef] [Google Scholar]
75. Jensen LS, Merry AF, Webster CS, Weller CS, Larsson L. Evidence-based strategies for preventing drug administration errors
during anaesthesia. Anaesthesia. (2004) 59:493–504. 10.1111/j.1365-2044.2004.03670.x [PubMed] [CrossRef] [Google Scholar]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
Page 20 of 23
Interventions to reduce the incidence of medical error and its financ… health care systems: A systematic review of systematic reviews – PMC
2/15/24, 10:51 AM
76. Ostini R, Roughead EE, Kirkpatrick CMJ, Monteith GR, Tett SE. Quality Use of Medicines – Medication safety issues in
naming; Look-alike, sound-alike medicine names. Int J Pharm Pract. (2012) 20:349–57. 10.1111/j.2042-7174.2012.00210.x
[PubMed] [CrossRef] [Google Scholar]
77. Ohashi K, Dalleur O, Dykes PC, Bates DW. Benefits and risks of using smart pumps to reduce medication error rates: a
systematic review. Drug Safety. (2014) 37:1011–20. 10.1007/s40264-014-0232-1 [PubMed] [CrossRef] [Google Scholar]
78. Lehnbom EC, Stewart MJ, Manias E, Westbrook JI. Impact of medication reconciliation and review on clinical outcomes.
Ann Pharmacotherapy. (2014) 48:1298–312. 10.1177/1060028014543485 [PubMed] [CrossRef] [Google Scholar]
79. Avanecean D, Calliste D, Contreras T, Lim Y, Fitzpatrick A. Eﬀectiveness of patient-centered interventions on falls in the
acute care setting compared to usual care: a systematic review. JBI Datab System Rev Implement Reports. (2017) 15:3006–48.
10.11124/JBISRIR-2016-003331 [PubMed] [CrossRef] [Google Scholar]
80. Mitchell MD, Lavenberg JG, Trotta RL, Umscheid CA. Hourly rounding to improve nursing responsiveness: a systematic
review. J Nursing Administration. (2014) 44:462–72. 10.1097/NNA.0000000000000101 [PMC free article] [PubMed]
[CrossRef] [Google Scholar]
81. Murni I, Duke T, Triasih R, Kinney S, Daley AJ, Soenarto Y. Prevention of nosocomial infections in developing countries, a
systematic review. Paediatr Int Child Health. (2013) 33:61–78. 10.1179/2046905513Y.0000000054 [PubMed] [CrossRef]
[Google Scholar]
82. Safdar N, Abad C. Educational interventions for prevention of healthcare-associated infection: A systematic review. Crit Care
Med. (2008) 36:933–40. 10.1097/CCM.0B013E318165FAF3 [PubMed] [CrossRef] [Google Scholar]
83. Aboelela SW, Stone PW, Larson EL. Eﬀectiveness of bundled behavioural interventions to control healthcare-associated
infections: a systematic review of the literature. J Hospital Infection. (2007) 66:101–8. 10.1016/j.jhin.2006.10.019 [PubMed]
[CrossRef] [Google Scholar]
84. Vonberg RP, Gastmeier P. Hospital-acquired infections related to contaminated substances. J Hospital Infection. (2007)
65:15–23. 10.1016/j.jhin.2006.09.018 [PubMed] [CrossRef] [Google Scholar]
85. Flanders SA, Collard HR, Saint S. Nosocomial pneumonia: State of the science. Am J Infect Control. (2006) 34:84–93.
10.1016/j.ajic.2005.07.003 [PubMed] [CrossRef] [Google Scholar]
86. Savage JW, Anderson PA. An update on modifiable factors to reduce the risk of surgical site infections. Spine J. (2013)
13:1017–29. 10.1016/j.spinee.2013.03.051 [PubMed] [CrossRef] [Google Scholar]
87. Schabrun S, Chipchase L. Healthcare equipment as a source of nosocomial infection: a systematic review. J Hospital
Infection. (2006) 63:239–45. 10.1016/j.jhin.2005.10.013 [PubMed] [CrossRef] [Google Scholar]
88. Amaratunga T, Dobranowski J. Systematic review of the application of lean and six sigma quality improvement
methodologies in radiology. J Am College Radiol. (2016) 13:1088–95.e7. 10.1016/j.jacr.2016.02.033 [PubMed] [CrossRef]
[Google Scholar]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
Page 21 of 23
Interventions to reduce the incidence of medical error and its financ… health care systems: A systematic review of systematic reviews – PMC
2/15/24, 10:51 AM
89. Snyder SR, Favoretto AM, Derzon JH, Christenson RH, Kahn SE, Shaw CS, et al.. Eﬀectiveness of barcoding for reducing
patient specimen and laboratory testing identification errors: A Laboratory Medicine Best Practices systematic review and metaanalysis. Clin Biochem. (2012) 45:988–98. 10.1016/j.clinbiochem.2012.06.019 [PMC free article] [PubMed] [CrossRef] [Google
Scholar]
90. Weerakkody RA, Cheshire NJ, Riga C, Lear R, Hamady MS, Moorthy K, et al.. Surgical technology and operatingroom
safety failures: A systematic review of quantitative studies. BMJ Quality and Safety. (2013) 22:710–8. 10.1136/bmjqs-2012001778 [PubMed] [CrossRef] [Google Scholar]
91. Bowers L, Banda T, Nijman H. Suicide inside: A systematic review of inpatient suicides. J Nervous Mental Disease. (2010)
198:315–28. 10.1097/NMD.0b013e3181da47e2 [PubMed] [CrossRef] [Google Scholar]
92. Doupnik SK, Rudd B, Schmutte T, Worsley D, Bowden CF, McCarthy E, et al.. Association of suicide prevention
interventions with subsequent suicide attempts, linkage to follow-up care, and depression symptoms for acute care settings: a
systematic review and meta-analysis. JAMA Psychiatry. (2020) 77:1021–30. 10.1001/jamapsychiatry.2020.1586 [PMC free
article] [PubMed] [CrossRef] [Google Scholar]
93. Kim JM, Suarez-Cuervo C, Berger Z, Lee J, Gayleard J, Rosenberg C, et al.. Evaluation of patient and family engagement
strategies to improve medication safety. Patient. (2018) 11:193–206. 10.1007/s40271-017-0270-8 [PubMed] [CrossRef] [Google
Scholar]
94. Garrouste-Orgeas M, Philippart F, Bruel C, Max A, Lau N, Misset B. Overview of medical errors and adverse events. Ann
Intensive Care. (2012) 2:2. 10.1186/2110-5820-2-2 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
95. Khammarnia M, Ravangard R, Barfar E, Setoodehzadeh F. Medical Errors and Barriers to Reporting in Ten Hospitals in
Southern Iran. Malays J Med Sci. (2015) 22:57–63. 10.1155/2015/357140 [PMC free article] [PubMed] [CrossRef] [Google
Scholar]
96. Poorolajal J, Rezaie S, Aghighi N. Barriers to medical error reporting. Int J Preventive Med. (2015) 6:97. 10.4103/20087802.166680 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
97. Morrison M, Cope V, Murray M. The underreporting of medication errors: A retrospective and comparative root cause
analysis in an acute mental health unit over a 3-year period. Int J Ment Health Nurs. (2018) 27:1719–28. 10.1111/inm.12475
[PubMed] [CrossRef] [Google Scholar]
98. Senders J. FMEA and RCA: the mantras; of modern risk management. BMJ Qual Saf. (2004) 13:249–50.
10.1136/qshc.2004.010868 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
99. Tanaka M, Tanaka K, Takano T, Kato N, Watanabe M, Miyaoka H. Analysis of risk of medical errors using structuralequation modelling: a 6-month prospective cohort study. BMJ Quality Safety. (2012) 21:784–90. 10.1136/bmjqs-2010-048330
[PubMed] [CrossRef] [Google Scholar]
100. Vardi A, Efrati O, Levin I, Matok I, Rubinstein M, Paret G, et al.. Prevention of potential errors in resuscitation medications
orders by means of a computerised physician order entry in paediatric critical care. Resuscitation. (2007) 73:400–6.
10.1016/j.resuscitation.2006.10.016 [PubMed] [CrossRef] [Google Scholar]
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
Page 22 of 23
Interventions to reduce the incidence of medical error and its financ… health care systems: A systematic review of systematic reviews – PMC
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363709/
2/15/24, 10:51 AM
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Learn more: PMC Disclaimer | PMC Copyright Notice
Glob Qual Nurs Res. 2022 Jan-Dec; 9: 23333936221094857.
PMCID: PMC9243474
Published online 2022 Jun 28. doi: 10.1177/23333936221094857
PMID: 35782105
Language: English | Greek
Exploring Nurses’ Perceptions of Medication Error Risk Factors: Findings From a
Sequential Qualitative Study
Georgios Savva,1 Evridiki Papastavrou,2 Andreas Charalambous,2,3 Stavros Vryonides,2,4 and
Anastasios Merkouris2
Abstract
A focus group study was conducted to explore nurses’ perceptions of medication administration error
associated factors in two medical wards of a tertiary hospital. Nurses were invited to participate in fo‐
cus group discussions. Thematic analysis was employed and identified four themes: professional prac‐
tice environment related factors, person-related factors, drug-related factors, and processes and proce‐
dures. Staﬃng, interruptions, system failures, insuﬃcient leadership, and patient acuity were perceived
as risk factors for medication errors. The findings of this study complement the findings of an observa‐
tional study which investigated medication administration errors in the same setting. Although some
findings were similar, important risk factors were identified only through focus group discussions with
nurses. Nurses’ perceptions of factors influencing medication administration errors provide important
considerations in addressing factors that contribute to errors and for improving patient safety.
Keywords: medication errors, drug safety, nurses, medical wards, focus groups, thematic analysis,
Cyprus
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Introduction
Medication administration errors (MAEs) are common in hospital wards, despite the eﬀorts made to
prevent them and patients run the risk of suﬀering harm as a consequence (Giannetta et al., 2020;
Härkänen et al., 2019). Previous research suggests that MAEs (excluding prescription, or dispensing
errors) occur in 5% of non-intravenous and 35% of intravenous doses or up to 20% of all doses given
(Härkänen et al., 2019). Globally, the cost associated with all medication errors has been estimated by
the World Health Organization (WHO) at $42 billion USD annually (World Health Organization,
2017). In Europe, the annual cost of medication errors had been estimated between €4.5 billion and
€21.8 billion (European Medicines Agency, 2013).
Clinical nurses spend an important part of their time administering medicines to inpatients (Härkänen
et al., 2015; Michel et al., 2021). In fact, nurses spend approximately 27% of their time on medicationrelated activities depending on the ward type and on the type of health information technology em‐
ployed (Moore et al., 2020). Medication administration to inpatients is a complex process, and diﬀerent
healthcare professionals are involved. Individual (staﬀ) related factors (i.e., knowledge, experience),
patient characteristics (i.e., medical condition) and system related factors (i.e., workload, communica‐
tion failures) may influence the medication process (Härkänen et al., 2015; Härkänen, Luokkamäki et
al., 2020). Therefore, errors during the medication administration process can be attributed to diﬀerent
factors. Nurses, are, therefore, involved in a prone to error procedure (Giannetta et al., 2020; Härkänen
et al., 2015). Since nurses have an important role in this process, it is crucial to explore their percep‐
tions of MAE associated factors, in order to draft targeted plans to limit drug errors and improve patient
safety (Härkänen, Luokkamäki et al., 2020).
The United States National Coordinating Council for Medication Error Reporting and Prevention define
medication errors as “any preventable event that may cause or lead to inappropriate medication use or
patient harm while the medication is in the control of the health care professional, patient, or con‐
sumer” (National Coordinating Council for Medication Error Reporting and Prevention, 2021). Medica‐
tion errors can also be defined as “a deviation from the doctor’s order, a deviation from the manufactur‐
ers’ preparation/administration instructions, or deviations from the relevant organization’s guidelines or
policies” (Keers et al., 2013).
Regarding MAEs, several definitions have been used in previous research. The Nursing Interventions
Classification provides the following definition for medication administration: “preparing, giving and
evaluating eﬀectiveness of prescribed and non-prescribed medications” (Butcher et al., 2018). A MAE
can be defined as a medication error that occurs while administering a medication to a patient (Baraki
et al., 2018). MAEs represent a failure in one of the five “rights” of medication administration (right
patient, medication, time, dose, and route) or a failure in the documentation of drug administration
(Moore et al., 2020).
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Procedural errors are also common during the medication process. Procedural errors include omissions
and deviations from safe drug administration guidelines (Härkänen et al., 2015; Savva et al., 2022). In
particular, the omission of several procedural steps represents a great proportion of the errors detected
during the medication process (Henderson et al., 2021). For example, omitting to disinfect the hands
before drug administration or omitting to disinfect the site of injection, constitute errors of omission
that have the potential to cause harm to patients and prolonged hospitalization (Härkänen et al., 2019).
For the purpose of this study, MAEs and procedural errors that could have been made during drug ad‐
ministration were considered. In particular, a MAE was defined as a deviation from the doctor’s order, a
deviation from the manufacturers’ preparation/administration instructions, or deviations from the rele‐
vant organization’s guidelines or policies (Keers et al., 2013).
Studies have reported the implementation of diﬀerent interventions to prevent errors, including techno‐
logical applications, staﬀ training, improved access to pharmacy services, and improvements in ward
systems (European Medicines Agency, 2013; Manias et al., 2020). However, errors are still commonly
detected in healthcare settings, particularly in hospitals (Härkänen et al., 2019). MAEs occur in up to
20% of all doses given, however, higher percentages have been reported, depending on the site and on
the definitions used (Härkänen et al., 2019; Keers et al., 2013).
The present study is part of a project to investigate medication administration safety in two medical
wards of a tertiary hospital in the Republic of Cyprus. Using an observational study on the same two
medical wards, we reported drug therapeutic class and patient attributes to be significantly associated
with the occurrence of errors (Savva et al., 2022). This was the first report examining medication errors
in Cyprus. The present study aimed to collect nurses’ perceptions of these error related factors. The ob‐
servation method is considered to be one of the most eﬃcient, valid and accurate methods for detecting
MAEs (Flynn et al., 2002). Nurses’ perceptions may reveal information lacking from the observational
study. The observational study found that nurses did not disinfect the site of injection before administer‐
ing an injectable drug, and did not disinfect their hands, but the reasons that led nurses to deviate from
basic safety guidelines could not be explained by the observational study. The present study aimed to
collect nurses’ perceptions of these error related factors and identify any diﬀerences between perceived
and observed MAE associated factors. The use of more than one method for collecting the data has
been shown to produce a clearer picture of the problem (Wisdom & Creswell, 2013). By extending our
research to include nurses’ perceptions, we hoped to extend our knowledge about the MAE problem
and stimulate the development of appropriate actions to reduce MAEs.
Methods
Design
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This is an exploratory qualitative study and part of a multiple method project. The theoretical approach
followed for the present study was based on the inductive method and thematic analysis, an independent
qualitative descriptive approach which is appropriate for identifying, analyzing and reporting patterns
(themes) within data (Braun & Clarke, 2006; Vaismoradi et al., 2013). Thematic analysis is considered
appropriate when trying to identify and understand individuals’ perceptions of a phenomenon (George
et al., 2021).
Two focus group discussions were organized to explore nurses’ perceptions regarding the factors con‐
tributing to MAEs in medical wards. Qualitative data deriving from focus group discussions allow an in
depth comprehension of participant’s perceptions on the discussion topic concerned, and have been
used extensively in previous research aimed to gain insights of participants’ perceptions (Escrivá Gracia
et al., 2019; Papastavrou & Andreou, 2012). The research team comprised three academics (EP, AM,
AC) who are university professors with substantial experience in academic research, one clinical nurse
(RN, PhD) with experience in drug administration and who was involved in the conduct of previous
research in nursing ethics and rationing (SV) and one pharmacist (BPharm, PhD), with experience in
drug administration and special interest in drug safety (GS). None of the researchers were working in or
had any kind of relationship with the hospital where the study was conducted. This is crucial as it en‐
sured that there was no undue pressure on the nurses to participate.
The focus group interviews aimed at exploring the perceptions of nurses involved in the medication
process in medical wards regarding the risk factors for errors and deviations from the basic medication
administration safety guidelines. In comparison with other methods, focus group discussions have sev‐
eral advantages (Freeman, 2006). The sense of freedom and security among participants and the dy‐
namic nature of a focus group discussion is motivating for participants and creates a suitable environ‐
ment to elicit the opinions of the group (McLaﬀerty, 2004; Wilkinson & Birmingham, 2003). Further‐
more, because “errors” is a sensitive issue that cannot easily be discussed freely, this method gives the
opportunity for participants to express their views in a safe environment (McLaﬀerty, 2004; Papas‐
tavrou et al., 2014). The study is reported in accordance with the Consolidated Criteria for Reporting
Qualitative Studies (COREQ) (Tong et al., 2007).
Participants and Setting
Nurses involved in the medication process in two medical wards of a tertiary hospital in the Republic of
Cyprus were invited to participate in the focus group discussions. The hospital provides healthcare ser‐
vices to more than 250,000 inhabitants. Each medical ward has 30 beds and a total of 25 nurses are em‐
ployed on each ward. An observational study was previously conducted in these two medical wards in
order to detect the MAEs and to explore the associated factors. In that study nurses were directly ob‐
served by two independent observers administering the medication to inpatients. For this study we
aimed to explore the perceptions of nurses who participated in the observational study, thus we invited
nurses from these two wards to participate in the focus group discussions.
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In order to achieve a comprehensive representation of the nurses involved in the medication process in
these medical wards, a purposive sampling approach was implemented. Eligible nurses were identified
and approached by the researchers, after consulting with the ward management, and a face-to-face de‐
tailed oral explanation about the study was provided, before they provided informed consent and agreed
to participate. Inclusion criteria for nurses’ participation were the involvement in the medication
process and currently working on one of the two medical wards. Nurses with managerial position were
excluded to ensure that staﬀ nurses could talk freely about their experiences without reprisal. Hetero‐
geneity was sought for work experience in order to obtain the perceptions of new and experienced nurs‐
es (McLaﬀerty, 2004; Papastavrou & Andreou, 2012). Therefore, nurses with a diﬀerence in years of
work experience and with higher degrees were recruited. Two focus groups were held, each with homo‐
geneity with respect to participants’ job rank in order to address any hesitancies about expressing their
views in the presence of senior colleagues (Papastavrou & Andreou, 2012).
In total, 12 nurses, that met the above criteria, agreed to be enrolled. None of the nurses revoked his/her
participation and two focus groups were conducted (Group A = 5 nurses, Group B = 7 nurses). All of
the participants were registered nurses while five of them had additionally a master’s degree. Eight of
them were female nurses and four were male nurses. Age ranged from 26 to 52 years and they were all
Cypriots. Work experience, including experience in the medication process, ranged from 2 to 18 years,
and they all worked on one of the two medical wards of the same tertiary hospital where recruitment
took place (five from the one ward and seven from the other).
Data collection
Focus group interviews were conducted from January to February 2020 in one of the hospital’s meeting
rooms. Participants were separated in two focus groups (Group A = 5 nurses, Group B = 7 nurses).
Group A interview lasted 75 minutes and Group B lasted 90 minutes. Focus groups were led by a mod‐
erator in the presence of an observer. The moderator (SV) guided the discussion based on a semi-struc‐
tured interview guide, while the observer (GS) took notes of the conversation as well as the non-verbal
signals. The moderator had previous experience of conducting focus group interviews. The moderator
and the observer were experienced in the medication process in clinical wards but had no relationship
with the medical wards or the participants. Participants were aware of the researchers professional
background and that the goal of the study was to promote drug administration safety. The focus group
discussion continued until no additional statements or views were expressed (McLaﬀerty, 2004; Papas‐
tavrou & Andreou, 2012). Two audio recording devices were used at each focus group to record the
conversation for later transcription and analysis. The observer helped to keep issues relevant to medica‐
tion error by notifying the moderator to steer conversations away from issues irrelevant to the aim of
the study. The observer informed the moderator if more details were needed to elaborate on a partici‐
pant’s comment, observed and took notes of participants’ reactions and behaviors relevant to the issues
raised during discussions. During discussions the observer and the moderator wrote observational notes
in order to record incidents, interactions and narratives that could help later during data coding and
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analysis. All data were strictly confidential. Only the researchers had access during the analysis of the
data and the data were always stored in a password-protected form. Data were transcribed in a way that
no links between subjects and responses could be made (e.g., by using codes instead of names).
Development of the Interview Guide
It was agreed by the research team to develop a semi-structured guide. The development of the inter‐
view guide was based on the findings of the observational study and on a literature review mapping the
most common causes of medication errors in clinical settings and created a conceptual basis for the in‐
terview (Kallio et al., 2016). Medication error risk factors, as described in literature, were embedded
into an initial set of questions and a preliminary semi-structured interview guide was drafted.
The observer and moderator, reviewed the preliminary version and formulated the questions in order to
be participant-oriented, non-leading, and clearly worded (Kallio et al., 2016; Papastavrou & Andreou,
2012). The interview guide introduced participants to the topic and included short, conversational,
open-ended, and one-dimensional questions (see Supplemental File). For example, nurses were asked
“What would you consider as an error or omission during the administration of medicines to inpa‐
tients?” and “In your opinion, what factors may be related to the occurrence of errors?”
Data Analysis
Data analysis included the transcription of the discussions, data coding and analysis based on the the‐
matic analysis method. Interviews were transcribed verbatim by the moderator in order to produce an
accurate record of everything said in each of the focus-group interviews (Wilkinson & Birmingham,
2003). Transcripts were organized and coded by two researchers separately (SV and GS). Additionally,
during data analysis, the researchers recorded their thoughts in unstructured memos, made independent‐
ly by each coder in notebooks in order to facilitate the grouping of codes based on content similarity.
Data analysis was based on the inductive method and thematic analysis was employed. There are vari‐
ous techniques used for data analysis in the inductive method, however thematic analysis is among the
more common ones (Papastavrou et al., 2014; Ritchie & Lewis, 2004). Researchers identified topics
that emerged from the discussions, and then verified and expanded these topics through the data. The
process was repeated for finding any additional topics that could emerge from the transcribed discus‐
sions (Papastavrou & Andreou, 2012; Papastavrou et al., 2014; Ritchie & Lewis, 2004). Coding along
with the respective wording were grouped based on their content and similarity. Researchers repeatedly
performed this task until consensus was reached. Codes with similar content were grouped together
forming separate thematic categories. The objective of this eﬀort was the continuous analysis and syn‐
thesis of thematic categories into themes that were directly linked to the interview data. The researchers
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moved thereafter from independent analysis to team analysis. They compared their coding, memos, and
discussed and interpreted the content of several statements and reviewed the diﬀerences between their
coding until consensus was reached. Researchers did not use any specific software to manage the data.
Ethical Aspects
The study was approved by the National Ethics Committee (EEBK EΠ 2018.01.92) and by the research
committee of the Ministry of Health (0479/2018) of the Republic of Cyprus. The study was agreed by
the hospital administration and ward management. Participants’ names were replaced by a code (i.e.,
Nurse1, Nurse2 etc.) in order to maintain anonymity and all data gathered were kept confidential and
secure after data analysis was finalized. Prior to providing informed consent, all ward nurses were in‐
formed about the study. Participation was voluntary and it was made clear that participants would be
free to withdraw from the study at any point, if they wished to do so. Participants were assured of
anonymity, thus a link between the data and participants would not be possible. They were also in‐
formed that the data will be used only for the study purposes and for improving patient safety in the
wards.
Trustworthiness
In order to support the trustworthiness of the findings, the authors employed several techniques pro‐
posed by Lincoln and Guba (1985) during the conduct of the study. In particular, credibility was en‐
hanced through prolonged engagement with and persistent observation of the participants in both med‐
ical wards. In fact, the moderator and the observer spent extended time with nurses working in the
study setting, first during the observational study, which preceded the focus group study, and then be‐
fore the initiation of the focus groups discussions. Participants were aware of the researchers’ profes‐
sional background and experience. This helped establish a trusting relationship between researchers and
participants and in enhancing participants’ engagement. During the observation phase (in which the
focus group moderator and the observer participated) the researchers gained useful information about
participants’ behaviors during drug administration, which subsequently helped in recognizing and un‐
derstanding participants’ descriptions about medication error associated factors during the focus group
discussions, which also enhanced credibility. Furthermore, after each focus group discussion was final‐
ized, the observer and the moderator remained in the room with the participants, summarized what had
been said, in order to obtain additional information which could be relevant with the study topic. Trian‐
gulation was achieved by comparing data collected via notes and memos made by the observer and by
the moderator, from focus group discussions and from the experienced gained during the observational
study. Furthermore, an additional researcher assessed the datasets, the data analysis and the results of
the study, establishing investigators triangulation (Sandelowski, 1993).
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Exploring Nurses’ Perceptions of Medication Error Risk Factors: Findings From a Sequential Qualitative Study – PMC
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To ensure dependability and confirmability, the researchers maintained an audit trail of the process and
used notes, memos, observations and transcripts of the whole research process. Data coding and analy‐
sis was done independently by the moderator and the observer and then an additional researcher as‐
sessed data analysis and results. Furthermore, transferability was ensured by implementing a purposive
sampling approach to ensure that participants (i.e., clinical nurses) could provide rich descriptions of
their perceptions regarding the factors associated with MAEs and the views, perceptions, ideas, and
experiences of all nurses who participated in the study could be captured and reflected.
The researchers, prior to initiation of the study, discussed and clarified their understandings and views
regarding the research topic in order to identify and contest their personal views related to this topic.
Researchers discussed whether the derived themes were related to the participants’ narratives and accu‐
rately reflected the perceptions of the participants. Participants were not invited to provide feedback on
the findings. However, observations were drawn upon to support interpretations of the data.
Results
From the analysis of data collected from the two focus groups, initially 33 diﬀerent thematic categories
were derived from the codes. In the coding tree chart used during analysis of data, MAE related factors
that were rooted in the working environment were mapped under the theme “Professional practice envi‐
ronment and related factors.” Data that related nurse or patient factors were grouped under theme “Per‐
son related factors” for patient or nurse accordingly. Factors that were relevant to the drugs adminis‐
tered were grouped under theme “Drug related factors” and finally factors that were related to problem‐
atic procedures and latent conditions were captured under the theme “Processes and procedures.” Each
of these themes is described, beginning with the Professional practice environment and related factors
as the dominant theme.
Professional Practice Environment and Related Factors
Nurses pointed to issues related to their professional practice environment and working conditions that
contributed to MAEs. For instance, nurses explained that factors like inadequate staﬃng, the shift
(morning, evening and night shift), the work organization system, distractions/interruptions, the nature
of the ward, problematic communication, leadership and training, can be associated with errors.
Shift and staffing Shift and staﬃng were two important working environment factors that are associat‐
ed with MAEs and were stressed during discussions. Participants explained that during night shifts er‐
rors may occur due to physical and mental fatigue which have a negative impact on nurses’ perfor‐
mance. As one nurse stated: “At the end of the night shift, nurses are often more exhausted. This can
make them prone to errors. You get tired at night” (Nurse 3). In addition, they emphasized that, by
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243474/
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Exploring Nurses’ Perceptions of Medication Error Risk Factors: Findings From a Sequential Qualitative Study – PMC
2/15/24, 10:50 AM
comparison with the morning shifts, the night shift is usually understaﬀed, which can negatively aﬀect
the medication round. One nurse mentioned that the medication process can be significantly prolonged
in night shifts due to lower staﬃng levels:
For me there is a big problem in the administration of medicines at the night shift. It takes
much longer to finalize medication administration at the night shift. . .night shift is always
understaﬀed. Due to the very low staﬃng on the night shift, i.e. usually with 3 nurses only,
the medication round is carried out by one nurse only and this prolongs the whole process
(Nurse 6).
Low staﬃng levels were identified by the nurses as an important contributing factor to medication er‐
rors. They claimed that with low staﬃng levels (i.e., four or less nurses per shift) additional work is al‐
located to each nurse creating situations where they are more likely to omit tasks that shouldn’t be omit‐
ted in order to administer medications on time. Some tasks, like hand disinfection before medication
administration, were considered as less important and could be omitted to save time. Nurses reasoned
that by omitting these extra tasks they had time to provide other types of nursing care. Understaﬃng
was a common experience shared by the participants and consequently placed nurses in the diﬃcult
position of having to make these trade-oﬀs because as one nurse stated: “There is just not enough time”
(Nurse 5). The nurses suggested that if staﬃng levels were appropriate, there would be more time to
administer medications following accepted practices, thereby reducing the likelihood of procedural er‐
rors related to administering medications.
Work organization system The organization of work was viewed as an important factor influencing
medication errors. Nurses explained that there are two basic types of work allocation in the wards. One
is when a number of patients are assigned to a nurse, so that nurse has to provide all the care needed
solely for these patients only. Another type is when specific tasks are assigned to each nurse, resulting
in 1 or 2 nurses being responsible for administering all medicines to all inpatients. These types of work
allocations also varied between day and night shifts. Nurses expressed the view that these variations in
organizing nursing work and tasks related to medication administration influenced the likelihood for
MAEs. They explained, when tasks are allocated to nurses, a single nurse will have to carry out both;
preparation and administration of all medicines to all inpatients. This results in a rather prolonged med‐
ication round, meaning that for some patients the medication will not be administered at the right time.
Further, if this nurse who has the responsibility to administer all medicines to all inpatients, is exhaust‐
ed or interrupted or distracted during the process, this could negatively aﬀect his/hers concentration,
which increases the risk of an error being made during the medication administration process. As one
nurse described:
I believe that the risk of a dosage error is increased when tasks are allocated to nurses. In
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243474/
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Exploring Nurses’ Perceptions of Medication Error Risk Factors: Findings From a Sequential Qualitative Study – PMC
2/15/24, 10:50 AM
I believe that the risk of a dosage error is increased when tasks are allocated to nurses. In
these cases, usually one nurse will be administering the drugs to all inpatients, and this
could, for example, delay the administration of time critical drugs. Particularly when that
nurse is fatigued, as on night shifts, or when is interrupted or distracted by visitors or from
other ward staﬀ, errors can occur (Nurse 8).
Distractions and/or Interruptions. Distractions and interruptions were perceived as error associated fac‐
tors. The presence of family members and relatives in the ward during medication …

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