Interventions to reduce medication administration errors among nurses in a health care setting

Topic:  Interventions to reduce medication administration errors among nurses in a health care setting

Population– nurses taking care of patients in a health care setting 

intervention— safety interventions 

comparison– none 

Outcome– reduce medication errors 

INDIVIDUAL TOPIC SEARCH STRATEGY (ITSS) GUIDELINES

PURPOSE

· The purpose of this initial paper is to briefly describe your search strategies when identifying two articles that pertain to an evidence-based practice topic of interest.

Course Outcomes

This assignment enables the student to meet the following course outcomes.

· CO

1

: Examine the sources of knowledge that contribute to professional nursing practice. (PO #7)

· CO 2: Apply research principles to the interpretation of the content of published research studies. (POs #4 and #8)

REQUIREMENTS/PREPARING THE PAPER

· Each student will sign-up for a group to formulate an evidence-based practice topic of interest

· Each group will formulate research question using PICO format.

· Each group member will search, retrieve, and receive approval for
1 PRIMARY DATA ARTICLE
to answer the group Research Question.

· Paper should include a Title and Reference pages.

· Page Length: 3-4 pages Excluding Title and Reference pages

· The paper will include the following:

· Clinical Question

· Describe problem

· Significance of problem in terms of outcomes or statistics

· Your PICOT question

· Purpose of your paper

· Level of Evidence

· Type of question asked

· Best evidence found to answer question

· Search Strategy

· Search terms

· Databases used: Chamberlain Database

· Refinement decisions made

· Identification of most relevant article

· Format

·

Correct grammar and spelling

· Use of headings for each section

· Use of APA format (7th edition)

· Required to write the paper based on
PAPER FORMAT

1

· Refers to Grading Rubric in page 3

Clinical Question

Research Question

· Accurately and clearly states your research question using PICO format

Overview of the Problem

·

What statistics document this is a problem?

(facts and figures)

Significance of the Problem

· What health outcomes result from this problem. Why should people be concerned about this problem?

Purpose of Paper

· Describe the purpose of topic search strategy (ITSS) paper

Search Strategy

Search Terms

· List all terms used to search for your article (i.e. breast cancer, screening, mammography, intervention, assessment, influencing factors….etc.)

Library Databases

· List Chamberlain library database used (i.e. EBSCO, Medline, OVID, PubMed….etc.)

·

Google search engine is NOT the library database

Availability of Articles

· How many research articles were available to answer your research question?

· Provide numbers of articles, NOT just saying “plenty, sufficient, many…etc.

Refinement Decisions

· What decision(s) have changed from your original search strategies? (i.e. peer-review, within last

5

years, primary data article, full-text….etc.)

· What was your rationale for your decision to change from original search strategies?

Final Article

· Describe decisions you made to specifically select 1 PRIMARY DATA ARTICLE as relevant for answering your Research Question

Level of Evidence

Addresses Topic/Relevance to PICO

· Describe how article addresses the topic, purpose and key points

Evidence Level Pyramid

· Identify and describe the level of evidence based on Evidence Level/Hierarchy Pyramid

· Refers to Handout (Quick Guide to Designs in an Evidence Hierarchy)

Study Type

· Identify study type of article: Quantitative, Qualitative, or Mixed-Method Study

Grading Rubric & Description for Individual Topic Search Strategy

10

10

10

10

10

5

5

10

10

10

5

5

5

10

10

5

Clinical Question (45)

Research Question (PICO)

15

Accurately and clearly states your Research Question as formulated and stated in PICO format

Purpose of Paper

10

Describe the purpose of your ITSS paper

Overview of Problem

What statistics document this is a problem?

Significance of Problem

What health outcomes result from your problem?

Search Strategy (65)

Search Terms

List terms used to search for your articles (breast cancer, screening, mammography, intervention, factors..etc)

Library Databases

List Chamberlain library database you used (i.e. EBSCO, Medline, OVID, PubMed) Google search engine is NOT the library database

Availability of Articles

5

How many research articles were available to answer your research question? Provide numbers

Refinement Decisions

As you did your search, what decisions did you make in refinement to get your required articles down to a reasonable number for review?

What was your rationale for your decision to change?

How many research articles were available to answer your research question after your refinement process?

Final Article

Describe decisions you made to specifically select ONE PRIMARY DATA ARTICLE as relevant for answering your Research Question

Submit a hard copy of selected article.

Level of Evidence (20)

Relevance to PICO Evidence Level Pyramid Study Type

Describe how the article addresses the topic (i.e. therapy, prognosis, risk factors, assessments, or meanings….etc)

Identify and describe the Level of Evidence based on level of evidence pyramid (see handout)

Identify the study type based on the study design: Quantitative, Qualitative, Descriptive, Mixed-Method Study

Format

Use of required Headings and Subheading for each category

APA Format (7th ed. ) references, citations

Correct grammar and spelling

Paper length (3-4 pages)

Topic: Interventions to reduce medication administration errors among nurses in a health care setting

Population– nurses taking care of patients in a health care setting

intervention— safety interventions

comparison– none

Outcome– reduce medication errors

JANUARY 2018, VOL. 45 NO. 1 ONCOLOGY NURSING FORUM E1ONF.ONS.ORG

Impact of a Barcode
Medication Administration

System on Patient Safety
Marta Macias, RN, PhD, Francisco A. Bernabeu-Andreu, PhD, Ignacio Arribas, MD, PhD,

Fatima Navarro, MD, and Gema Baldominos, PhD

T he process of medication administra-tion is the last stage during which a barrier can be erected to prevent an error from reaching the patient. The study and implementation of strate-
gies for error prevention are considered to be prior-
ities by health organizations. Studies of medication
administration errors (MAEs) report an incidence
of about 7%–20%, and 8% when wrong-time errors,
or errors related to the medication administration
schedule, are excluded (Berdot et al., 2012; Keers, Wil-
liams, Cooke, & Ashcroft, 2013).

The type of medication is important when eval-
uating the characteristics of errors; health strategies
and policies are focused on medications defined as
high risk (Saedder, Brock, Nielsen, Bonnerup, & Lisby,
2014). Antineoplastic agents are considered to be high-
risk medications because of their narrow therapeutic
range and high toxicity (ASHP Council on Professional
Affairs, 2002). In a study analyzing the causes of death
because of medication errors, antineoplastic medi-
cations were found to be the most common agents
involved (McCarthy, Tuiskula, Driscoll, & Davis, 2017).
The incidence of MAEs in chemotherapy administration
ranges from 0.04% (Ford, Killebrew, Fugitt, Jacobsen,
& Prystas, 2006) to 18.8% (Walsh et al., 2009). The
incidence of MAEs in the outpatient setting range from
0.68% (León Villar, Aranda García, Tobaruela Soto, &
Iranzo Fernández, 2008) to 7.1% (Walsh et al., 2009) in
the adult population. The outpatient oncology setting
is considered to be a priority when reinforcing patient
safety (Goldspiel, DeChristoforo, & Hoffman, 2015;
León Villar et al., 2008).

Barcode medication administration (BCMA) is rec-
ommended for the prevention of MAEs (Lefkowitz,
Cheiken, & Barnhart, 1991; Neuenschwander et al.,
2003) because it allows nurses to verify the five rights
of medication administration (i.e., patient, drug, time,
route, and dose). Observational studies on BCMA tech-
nology reported a decrease in the incidence of MAEs,

OBJECTIVES: To determine the impact of barcode
medication administration (BCMA) on the incidence

of medication administration errors among patients

in an onco-hematology day hospital and to identify

the characteristics of medication errors in that

setting.

SAMPLE & SETTING: 715 patients treated in the
onco-hematology day unit at the Príncipe de Asturias

University Hospital in Madrid, Spain.

METHODS & VARIABLES: A between-groups,
pre-/postintervention study was conducted.

Administration errors observed in patients with solid

tumors (intervention group) were compared with

those in patients with hematologic cancer (control

group) before and after the introduction of BCMA.

Error incidence, type, and severity were assessed, as

was length of stay for treatment.

RESULTS: Use of a BCMA system reduced the
incidence and severity of errors in medication

administration in the onco-hematology day hospital.

IMPLICATIONS FOR NURSING: BCMA is a useful
technology to check the five rights of medication

administration in the onco-hematology day hospital

and could help nurses increase the time spent on

direct patient care activities.

KEYWORDS outpatient care; medication errors;
barcode medication administration

ONF, 45(1), E1–E13.
DOI 10.1188/18.ONF.E1-E13

E2 ONCOLOGY NURSING FORUM JANUARY 2018, VOL. 45 NO. 1 ONF.ONS.ORG

ranging from 23% (Helmons, Wargel, & Daniels, 2009)
to 56% (DeYoung, Vanderkooi, & Barletta, 2009).
When wrong-time errors were excluded, the percent-
age of errors ranged from 41% (Poon et al., 2010) to 81%
(Bonkowski et al., 2013). Little evidence exists regard-
ing the impact of this intervention on the severity of
errors (Hassink, Jansen, & Helmons, 2012). An import-
ant aspect to consider is the effect that BCMA devices
have on the time nurses need to administer medica-
tion; to date, no study has observed any variations in
time (Franklin, O’Grady, Donyai, Jacklin, & Barber,
2007; Tsai, Sun, & Taur, 2010).

In addition, little evidence exists related to the fre-
quency and type of MAEs in oncology, particularly in
the outpatient setting (Strudwick et al., 2017); assess-
ment of the use of information and communication
technology in this area to improve patient safety is
also limited. In the case of BCMA systems, the advan-
tages achieved in other populations and clinical units
have been applied to the oncology setting (Bubalo
et al., 2014). The diversity of criteria used to define
medication errors and error types, the disparity of
the methods used to detect them, and the variety of
settings justify the need for this study (Hassink et al.,

TABLE 1. Types of Medication Administration Errors in the Onco-Hematology Day Hospital

New Classification Observations and Changes Made

Wrong medication: Dispensation/administration of a
medication different than the prescribed

The subcategory “wrong prescription” was not included.
No definition of transcription is provided.

Omission of a dose or medication: Not administering
a prescribed dose (patients refusing medication were
excluded)

The current authors only considered medication or dose
omissions.

Wrong dose (higher, lower, extra)

No observations

Wrong date The current authors renamed the category “wrong time of
administration” to “wrong date.”

Wrong pharmacy dose No observations

Wrong preparation/handling/packaging/labeling No observations

Wrong administration technique No observations

Wrong route No observations

Wrong infusion rate No changes were made in this category. The infusion rate
was checked for each drug with the drug sheet and the
hospital’s protocols. The current authors considered a rate
of 20% plus or minus of the advised infusion rate to be
correct.

Wrong patient No observations

Insufficient drug monitoring: Absence of clinical review The “absence of analytical controls” subcategory was
excluded.

Deteriorated medication (including expired drug, incorrect
preservation)

No observations

Wrong order of administration of antineoplastic
treatment

New category proposed by the current study’s research
group

Other types (not included in the rest of the categories) No observations

Note. The Ruiz-Jarabo 2000 work group classifies 18 types of error. The categories “wrong storage,” “wrong length of admin-
istration,” “not applicable,” and “patients’ noncompliance” were not considered. The rest of the categories were included.
Note. Based on information from Grupo Ruiz-Jarabo 2000 (2008).

JANUARY 2018, VOL. 45 NO. 1 ONCOLOGY NURSING FORUM E3ONF.ONS.ORG

2012). The aim of this study was to assess the impact
of BCMA on the incidence of MAEs, types of errors,
patient risk, and time spent administering medication
to onco-hematology patients in the day hospital.

Methods
An MAE (Keers et al., 2013) was defined as noncon-
cordance between the medication administration
performed and any of the following options: doctor’s
prescription, official administration instructions
according to the protocol of the center, or the admin-
istration instructions from the manufacturer. Also
taken into account were nonconcordance errors
between the doctor’s prescription and the dispen-
sation or transcription of the medication by the
pharmacy department.

In this study, the current authors used the adapted
version of the classification of type of medication
errors as defined by the Ruiz-Jarabo 2000 work
group (Grupo Ruiz-Jarabo 2000, 2008) (see Table 1).
Of the 14 types of error proposed, 7 could be influ-
enced by the BCMA system: wrong medication, dose
or medication omission, incorrect dose, wrong date
of treatment, wrong route of administration, wrong
patient, and wrong order of medication administra-
tion. The potential severity of each error was assessed
on a scale from 1 (no severity) to 5 (catastrophic).
The degree of severity resulting from the errors
was assessed according to the index of the National
Coordinating Council for Medication Error Reporting
and Prevention. The length of stay for treatment was
also measured.

Setting and Sample
A pre-/postintervention study was conducted in the
onco-hematology day unit of the Príncipe de Asturias
University Hospital from January 2011 to May 2012.
Twenty patients were admitted to the day hospi-
tal. BCMA and computerized physician order entry
(CPOE) were implemented for the intervention
group, made up of patients with solid tumors.

MAEs observed in patients with solid tumors
(intervention group, N = 627) were compared with
those observed in patients with hematologic cancer
(control group, N = 88). About 30,000 medication
administrations are performed annually in this ward.
Sixty-three patients were excluded from the study for
various reasons: (a) adverse drug reaction leading to
the interruption of therapy administration (interven-
tion, n = 7; control, n = 1); (b) incomplete observer
records of the drug’s administration because of lack
of time (intervention, n = 17; control, n = 8); and (c)

technical issues during BCMA implementation in the
intervention group (n = 30).

Training was given to an interprofessional team
of professionals from the quality, pharmacy, infor-
mation, and technology departments, as well as from
the biomedical research foundation and the day
unit. Nurses received two training sessions on the
management of the BCMA system, which was then
implemented in phases. Systematic assessment of
the implementation was performed throughout the
process.

This study was approved by the Príncipe de Asturias
University Hospital’s ethics committee in clinical
research. Informed consent was obtained from the
nurses who were involved in the study because of their
medication preparation and administration duties.
Patients were assigned correlative numbers, and the
anonymized patient data were included in a database.

Data Collection Procedure
The observation technique described by Barker, Flynn,
and Pepper (2002) and by Dean and Barber (2001)
was used to detect MAEs. To avoid nurses modify-
ing their actions because they were being observed
during the BCMA process, they were told that the
observer was there to monitor the performance of
the medication distribution system. Observations
were carried out during the Monday to Friday nurs-
ing shift (from 8 am to 7:30 pm) starting one month
before the introduction of the BCMA system and
ending one month afterward. According to the power
analysis conducted, a sample size of 1,994 observa-
tions (997 in the preimplementation period and 997
in the postimplementation period) would be required
to detect a difference in the MAE rate of 4.2% with
80% power and 95% confidence interval (CI). The
preintervention phase was conducted 10 months
before implementation of the BCMA system, and
postintervention observations took place 6 months
after BCMA implementation.

Study observers were selected and trained during
a workshop; the group of observers consisted of four
pharmacy students, six pharmacists, and one nurse.
To prepare for the observation, the observers studied
the standard operating procedures and the applica-
ble drug administration procedures of the setting.
Observers were trained to detect and classify errors.
For this reason, a written observational protocol was
established. Each observer carried out pilot observa-
tions that were supervised by one of the researchers for
one week to become familiar with the BCMA system.
Pilot observations were discussed with the research

E4 ONCOLOGY NURSING FORUM JANUARY 2018, VOL. 45 NO. 1 ONF.ONS.ORG

team, and pilot data were discarded. In practice, the
observer accompanied the nurse who administered
the medication using the BCMA system and observed
the administration of each dose of medication to the
patient. The observer was instructed to record each

of the nurse’s actions while administering medica-
tion to patients. These observation records were then
compared with the prescribed medication and with
available medication protocols in the ward to identify
MAEs. If the observer became aware of a potentially

TABLE 2. Characteristics of Medication Administration Before and After Implementing the BCMA System

Solid Tumor (Intervention) Hematology (Control)

Before BCMA After BCMA Before BCMA After BCMA

Characteristic n N % n N % n N % n N %

Medication administration

Total number of OEs 1,281 2,912 44 1,272 2,912 44 141 2,912 5 218 2,912 7
Supportive drug OEs 842 2,912 29 767 2,912 26 89 2,912 3 139 2,912 5
Antineoplastic OEs 439 2,912 15 505 2,912 17 52 2,912 2 79 2,912 3

Medication prescription

Manual 199 304 65 – – – 40 40 100 48 48 100
Electronic 105 304 35 323 323 100 –

– – – – –

Number of OEs by route

IV 1,157 1,281 90 1,205 1,272 95 – – – – – –
IV minibag (< 100 ml) 785 1,281 61 750 1,272 59 – – – – – – IV large volume (> 100 ml) 366 1,281 29 455 1,272 36 – – – – – –
IV bolus dose 6 1,281 1 – – – – – – – – –
Oral 110 1,281 9 52 1,272 4 – – – – – –
Subcutaneous 14 1,281 1 13 1,272 1 – – – – – –
Intrathecal – – – – – – – – – – – –
Intramuscular – – – 2 1,272 < 1 – – – – – –

Patientsa

Overall 304 715 43 323 715 45 40 715 6 48 715 7
Women 167 304 55 196 323 61 23 40 58 24 48 50

Solid Tumor (Intervention) Hematology (Control)
Before BCMA After BCMA Before BCMA After BCMA
Characteristic n N % n N % n N % n N %

Age (years)b

Younger than 25 – 298 – – 320 – 1 38 3 3 45 7
25–34 6 298 2 3 320 < 1 1 38 3 – 45 – 35–44 23 298 8 52 320 16 1 38 3 1 45 2 45–54 66 298 22 51 320 16 8 38 21 3 45 7 55–64 109 298 37 93 320 29 9 38 24 18 45 40 65 or older 94 298 32 121 320 38 18 38 47 20 45 44 a The median number of patients per day was 20.2 for the intervention group and 2.8 for the control group. b For the intervention group, the median age was 59.16 years (SD = 10.61, range = 32–84) before BCMA and 59.51 years (SD = 12.52, range = 30–87) after BCMA. For the control group, the median age was 60.87 years (SD = 13.29, range = 19–79) before BCMA and 62.16 years (SD = 15.25, range = 18–87) after BCMA. BCMA—barcode medication administration; OE—opportunity for error (the sum of observed administrations and omitted medications) Note. Because of rounding, percentages may not total 100.

JANUARY 2018, VOL. 45 NO. 1 ONCOLOGY NURSING FORUM E5ONF.ONS.ORG

serious error, the observer was instructed to intervene
for ethical reasons. These data were included in the
study if the serious error reached the patient.

Calibrated chronometers were used to measure
patients’ total length of stay in the onco-hematology
day unit and the time to administer each medication.
In both study periods, nursing staff included four
nurses with similar working conditions (number of
patients attended to and medications administered).
These four nurses attended to the two patient study
groups (intervention and control) in the same setting.
A maximum of three nurses were present during each
round of medication administration, and one nurse
was present from 4–7:30 pm.

To assess the degree of severity resulting from
errors, a panel of experts, which consisted of a doctor
specializing in oncology, a pharmacist, and a nurse,
was engaged. The actual degree of severity of the
MAEs was assessed with data obtained from medical
records. Information taken from the administration
instructions of the manufacturer and from UpToDate
were used to assess the potential severity of MAEs.
When no evidence was available, the authors relied on
the consensus criteria of the panel of experts.

Data Analysis
Information from the observations of the medication
administration process was entered into a comput-
erized database by one person. Absolute and relative
frequencies of the MAEs were calculated and com-
pared to determine the number of errors observed
before and after implementation of the BCMA
system. The chi-square test or the Fisher’s exact test
(as appropriate), odds ratio (OR), and relative error
reduction were used for this purpose. These analy-
ses were performed in the intervention and control
groups. When appropriate, 95% CIs were calculated
for further accuracy. For the comparison of quanti-
tative variables before and after the intervention, the
paired Student’s t test was used when the variable
followed a normal distribution, whereas the Mann–
Whitney U test or the Wilcoxon signed-rank test was
used when it did not. In all cases, a p value of less than
0.05 was considered to be statistically significant. The
power of the study reached 91%. Data analysis was
performed using IBM SPSS Statistics, version 20.0;
EpiData, version 4.1; and GraphPad Prism, version 7.0.

Results
A total of 2,912 medication administrations were
observed (including omissions) in 715 patients (627 in
the intervention group and 88 in the control group).

The number of observations of medication administra-
tions in the intervention group was similar before and
after the intervention (1,281 versus 1,272, respectively).
The number of observations was smaller in the control
group because of the reduced number of patients who
attended per day (141 before the intervention versus 218
after the intervention). Patients received a large number
of different medications, including antineoplastic
agents, drugs for comorbid illness, and medications
for supportive care and for complications related to
antineoplastic therapy. These were all observed and
included in the study. Medications have been sepa-
rated into two main groups: antineoplastic agents and
supportive drugs. In all study groups, supportive drugs
stood out as the most frequently used medications
compared to antineoplastic agents. Concerning the
route of administration, most medications were admin-
istered via IV. Table 2 shows the overall characteristics
of the medications observed and the characteristics of
the patients to whom they were administered.

Frequency and Type of Errors
The most relevant result from this study is that, when
attention is paid exclusively to the type of errors that
could be influenced by the intervention, the BCMA
system reduced the incidence of these errors by 85%
(see Table 3). Research shows that the most frequently
reported antineoplastic MAE is wrong dose, followed
by dose omission (Ford et al., 2006; Gandhi et al.,
2005; León Villar et al., 2008; Rinke, Shore, Morlock,
Hicks, & Miller, 2007; Serrano-Fabiá, Albert-Marí,
Almenar-Cubells, & Jiménez-Torres, 2010). However,
the most frequent error in the intervention group
during both periods was the rate of infusion. Among
other possible causes, the current authors observed
that infusion pumps were not systematically used for
either supportive drugs or photosensitive antineo-
plastic medications. This type of error, although not
sensitive to the intervention, set off a series of actions
for improvement in the current authors’ hospital. Few
studies have assessed this error (Dhamija, Kapoor, &
Juneja, 2014; Franklin et al., 2007). The second most
frequent error in this study was the order of admin-
istration; the current authors found one study that
also reports this error as frequent (Ulas et al., 2015).
The third most frequent error during both study peri-
ods in the current study was the wrong technique of
administration; nearly all the errors of this type were
associated with the administration of paclitaxel.

The incidence of MAEs during the study was 39%
(number of MAEs out of number of opportunities for
error; this refers to both study groups and all types of

E6 ONCOLOGY NURSING FORUM JANUARY 2018, VOL. 45 NO. 1 ONF.ONS.ORG

MAEs), and about 6% of medications accumulated more
than one error. The incidence of MAEs sensitive to the
BCMA system (or not able to be influenced by the BCMA
system) in the intervention group was 16%. Following
the intervention, a significant relative reduction of about
2% occurred. In the control group, a significant increase
was noted in the incidence of MAEs, from 18% before the
intervention to 39% after the intervention.

With the implementation of the BCMA system, the
authors observed a significant relative reduction in
the following types of error in the intervention group:
wrong medication, administration omission, wrong
dose, and wrong order of administration. An increase

in frequency of errors relating to technique of admin-
istration and rate of infusion was noted (see Table 4).
However, these are not influenced by the BCMA system.

Severity
The severity of MAEs was assessed in the intervention
group, with a focus on those sensitive to BCMA imple-
mentation, and from two perspectives: the potential
severity of the error and the actual consequences for
the patient. Regarding potential severity of errors, all
categories experienced a reduction in the number of
errors, except in the mild category, and showed sta-
tistically significant differences in moderate potential

TABLE 3. MAEs and Types of Errors Influenced by BCMA System in Patients With Solid Tumors (Intervention Group)

Before BCMA After BCMA Relative Change in ROE

Variable n N % n N % % 95% CI OR 95% CI p

Intervention group

MAEs 595 1,281 46 459 1,272 36 –22 [–23.4, –21.2] 1.54 [1.31, 1.8] < 0.001 Excluding infusion

rate errors
259 1,281 20 126 1,272 10 –51 [–54, –48.1] 2.3 [1.83, 2.9] < 0.001

Control group

MAEs 91 141 65 152 218 70 8 [4.6, 12.7] 0.79 [0.5, 1.24] 0.3
Excluding infusion

rate errors
41 141 29 77 218 35 21 [12.7, 33.3] 0.75 [0.47, 1.18] 0.22

Errors influenced
by BCMA

25 141 18 86 218 39 223 [178.6, 184.7] 0.33 [0.2, 0.55] 0.0012

Type of error influ-
enced by BCMA

Errors influenced
by BCMA

206 1,281 16 31 1,272 2 –85 [–88.6, –81.3] 0.13 [0.09, 0.19] < 0.001

Pharmacy tran-
scription errorsa

19 1,281 2 1 1,272 < 1 –93 [–99.7, –81.3] 0.05 [0.01, 0.39] < 0.001

Wrong medicationa 6 1,281 1 2 1,272 < 1 –60 [–88.2, –45.1] 0.33 [0.07, 1.66] 0.159 Medication

administration
omission a

14 1,281 1 1 1,272 < 1 –91 [–99.6, –76.3] 0.07 [0.01, 0.54] 0.008

Wrong dose
(higher)

7 1,281 1 – – – –100 – – – 0.008

Wrong dose
(lower)

8 1,281 1 – – – –100 – – – 0.004

Extra dose – – – – – – – – – – –
Wrong datea 2 1,281 < 1 – – – –100 – – – 0.16 Wrong routea 8 1,281 1 6 1,272 1 –17 [–37, –16.4] 0.75 [0.26, 2.18] 0.6 Wrong patienta – – – – – – – – – – – Wrong ordera 142 1,281 11 21 1,272 2 –86 [–89.2, –80.6] 0.13 [0.08, 0.21] < 0.001 a n refers to number of MAEs, whereas N is number of opportunities for error. BCMA—barcode medication administration; CI—confidence interval; MAE—medication administration error; OR—odds ratio; ROE—rate of error

JANUARY 2018, VOL. 45 NO. 1 ONCOLOGY NURSING FORUM E7ONF.ONS.ORG

severity (see Table 5). The no-severity category (55%)
was the most frequent in the period before BCMA
implementation, whereas the mild category (61%)
was the most frequent in the period after BCMA
implementation. No errors were rated in the highest
severity category after BCMA implementation.

Regarding the actual consequences for patients,
only four errors (2%) caused mild harm to the patient
in the period before BCMA implementation. Most
errors were classified into the “reached the patient
but caused no harm” category, which was the only one
to increase after the intervention. A nonsignificant
reduction of errors was observed in both categories in
which errors had an impact on patients, with no cases
observed after the intervention.

Length of Stay for Treatment Administration
When analyzing the impact of the intervention on
average length of stay for treatment, no statistically

significant differences were found. In the interven-
tion group, the average length of stay was 166 minutes
before the intervention and 160 minutes after the
intervention. In the control group, the average length
of stay was 167 minutes before the intervention and
155 minutes after the intervention.

Discussion
The implementation of a BCMA system for patients
with solid tumors was associated with an 85% relative
reduction of MAEs. No statistically significant differ-
ences were observed in the control group. The current
authors estimated that 3,200 potential MAEs per year
could be prevented in the studied setting. As Bubalo
et al. (2014) stated, these results are relevant because
of the lack of studies focusing on these types of treat-
ments. In their review of the impact of BCMA systems,
Leung et al. (2015) emphasized the limited knowledge
of these systems within the outpatient treatment

TABLE 4. MAEs in Patients With Solid Tumors Before and After BCMA

Before BCMA After BCMA Relative Change in ROE

Type of errora n % n % % 95% CI OR 95% CI p

Wrong medication 32 5 3 1 –89 [–96.4, –74.8] 8.64 [2.63, 28.4] < 0.001 Pharmacy dispensation 7 1 – – –100 – – – 0.02 Pharmacy transcription 19 3 1 < 1 –94 [–99.7, –75.7] 15.1 [2.01, 113.28] < 0.001 Administration 6 1 2 < 1 –60 [–85.7, –28.4] 2.75 [0.55, 13.68] < 0.47

Omission 15 3 2 < 1 –84 [–96.4, –62.1] 6.91 [1.34, 25.97] 0.006 Pharmacy transcription 1 < 1 1 < 1 100 [29.03, 50] – – 1 Pharmacy dispensation – – – – – – – – – Administration 14 2 1 < 1 –91 [–99.5, –69.3] 11.04 [1.45, 84.24] 0.003

Wrong dose 15 3 – – –100 – – – < 0.001 Higher 7 1 – – –100 – – – 0.02 Lower 8 1 – – –100 – – – 0.012 Extra – – – – – – – – –

Wrong date 2 < 1 – – –100 – – – 0.5 Wrong pharmaceutical form – – – – – – – – – Wrong preparation/handling/

packaging/labeling
8 1 4 1 –39 [–60.34, –15.9] – – 0.56

Wrong administration technique 53 9 91 20 123 [10.7, 141.4] 0.4 [0.27, 0.57] 0.001
Wrong route 8 1 6 1 – [–17.24, 7.22] – – 0.95
Wrong infusion rate 317 53 332 72 36 [33.2, 38.3] 0.44 [0.34, 0.57] < 0.001 Wrong patient – – – – – – – – – Wrong drug monitoring 2 < 1 – – –100 – – – 0.5 Deteriorated medication 1 < 1 – – –100 – – – – Wrong order 142 24 21 5 –81 [–86.1, –74.9] 6.54 [4.06, 10.53] < 0.001 a Number of errors out of total number of MAEs (N = 595 MAEs before BCMA; N = 459 MAES after BCMA) BCMA—barcode medication administration; CI—confidence interval; MAE—medication administration error; OE—opportunity for error; OR—odds ratio; ROE—rate of error

E8 ONCOLOGY NURSING FORUM JANUARY 2018, VOL. 45 NO. 1 ONF.ONS.ORG

setting. Only one study (Seibert, Maddox, Flynn, &
Williams, 2014) uses a methodology similar to the
present study. It too measured the impact of BCMA
in a day hospital; although the data on incidence of
MAEs are not comparable, Seibert et al. (2014) did not
observe a significant reduction of errors after BCMA
implementation. The authors stated that a manual
double-checking procedure was performed before the
BCMA system was implemented, which may justify
their findings (Seibert et al., 2014).

Most medications were administered via IV, which
limits potential comparisons with similar studies.
Only Helmons et al. (2009) clearly specified the
routes of administration, and in their study, the oral
route was the most frequently used.

In the current study, observations were mainly
performed by pharmacists; in other studies, observa-
tions were carried out by pharmacists (Bonkowski et
al., 2013; Franklin et al., 2007), nurses (Paoletti et al.,
2007; Poon et al., 2010; Skibinski, White, Lin, Dong,
& Wu, 2007), or a combination of both (Cochran &
Haynatzki, 2013; DeYoung et al., 2009; Seibert et al.,

2014). Future research should take into account the
profile and training of observers; an interprofessional
group of observers could improve the quality of the
data obtained.

No current gold standard has been established with
regard to the duration of the observation period. In the
current study, the observation period extended to more
than one month, with uninterrupted observations for 11
hours per day. In other studies, the observation period
varied from four hours (Serrano-Fabiá et al., 2010) to
seven months (Seibert et al., 2014).

Although the use of control groups is highly rec-
ommended to avoid potential random errors (Hassink
et al., 2012), only one study has been conducted com-
paring an intervention group with a control group, as
the current study does; however, the context is not
the same (Paoletti et al., 2007). Paoletti et al. (2007)
observed an increase in the number of errors in the
control group after the intervention. In addition, in
a systematic review of 42 pre-/postintervention stud-
ies on patient safety, the authors found that none
included a control group to assess the effectiveness

TABLE 5. Severity of MAEs in Patients with Solid Tumors Influenced by BCMA

Before BCMA
(N = 206)a

After BCMA
(N = 31)a

Variable n % n % p

Severity description

A. Potential – – – – –
B. Did not reach the patient 19 9 3 10 0.8
C. Reached the patient but caused no harm 144 70 28 90 0.77
D. Reached the patient and required monitoring 2 1 – – 0.54
E. May have contributed to or resulted in temporary harm to the patient

and required intervention
2 1 – – 0.54

F. May have contributed to or resulted in temporary harm to the patient
and required initial or prolonged hospitalization

– – – – –

G. May have contributed to or resulted in permanent harm to the patient – – – – –
H. Required intervention necessary to sustain the patient’s life – – – – –
I. May have contributed to or resulted in death of the patient – – – – –
Not evaluated 39 19 – – –

Severity of potential description

No severity 113 55 12 39 0.33
Mild 48 23 19 61 0.003
Moderate 29 14 – – 0.038
Severe 16 8 – – 0.12
Life-threatening – – – – –
a N refers to total number of MAEs influenced by BCMA
BCMA—barcode medication administration; MAE—medication administration error

JANUARY 2018, VOL. 45 NO. 1 ONCOLOGY NURSING FORUM E9ONF.ONS.ORG

of the interventions (Acheampong, Anto, & Koffuor,
2014).

Incidence of Medication Administration Errors
Results from the current study show a reduction of
85% in the incidence of medication errors—a finding
that is in line with prior evidence, where a reduction
of as much as 80% of the errors is reported after
implementation of a BCMA system (Bonkowski et
al., 2013; Leung et al., 2015). However, the literature
regarding the impact of BCMA systems shows contra-
dictory results.

The incidence of all MAEs in this study was
higher than that observed in other studies with sim-
ilar methodology (Bonkowski et al., 2013; Cochran
& Haynatzki, 2013; Franklin et al., 2007; Hardmeier,
Tsourounis, Moore, Abbott, & Guglielmo, 2014;
Helmons et al., 2009; Morriss, Abramowitz, Carmen,
& Wallis, 2009; Paoletti et al., 2007; Poon et al., 2010;
Seibert et al., 2014; Skibinski et al., 2007) where the
incidence of MAEs ranged from 7%–25% in the period
before BCMA implementation and from 2%–21% in
the period after. When selecting errors sensitive to
the BCMA system in the intervention group, the inci-
dence was 16%. These differences can be explained
by the peculiarities of the study setting, the complex
management of the medications used, and the study
design. Among study variables, those related to the
type of error were decisive to compare different stud-
ies’ results. The frequency of administration error
(related to time) was assessed in many studies and
had a high incidence in comparison to other errors;
the current authors could not consider it because
each patient in this study received only one dose of
medication per treatment. The current study pro-
vides unprecedented evidence of the high error rate
in the incorrect medication infusion rate, which is a
relevant finding because this type of MAE was not
sensitive to BCMA implementation. Future research
should be aimed at the reduction of incorrect medica-
tion infusion rates, given the potential adverse effect
on patients’ safety. A validated classification system
for types of medication errors would be necessary to
compare results.

Types of Error in Medication Administration
The current authors’ findings on types of error are
noteworthy, given the current lack of research and
error assessment in the field of medication adminis-
tration. These results provide information on MAEs
in oncology treatments that are specific to the out-
patient setting. The types of error most frequently

analyzed in similar studies are wrong medication,
wrong dose, wrong route of administration, wrong
time, and dose omission. Wrong order of admin-
istration is a unique type of error associated with
antineoplastic treatments, which was included for the
first time in the current study.

Regarding the impact of BCMA on errors sensitive
to these systems, results from other studies are not
at all homogeneous. In some studies, administration
omission errors decreased the most after imple-
menting the BCMA system (Franklin et al., 2007;
Helmons et al., 2009). In other studies, the errors
that decreased most were administration route (Poon
et al., 2010; Skibinski et al., 2007), time to adminis-
ter the medication (DeYoung et al., 2009; Morriss,
Abramowitz, Nelson, et al., 2009; Poon et al., 2010),
and wrong dose (Bonkowski et al., 2013, 2014; Seibert
et al., 2014).

This study confirms that some errors are not
preventable with BCMA and CPOE, which is why ver-
ification on the part of professionals is irreplaceable.
In line with previous reports (Seibert et al., 2014),
the current authors were able to observe an increase
in wrong route of administration errors. The BCMA
system would require further technological develop-
ment to reduce the number of errors associated with
infusion pumps.

Severity of Errors
Results from the current study suggest that a BCMA
system is effective in reducing severe MAEs. Few stud-
ies have addressed the impact of BCMA systems on
the severity of MAEs (Franklin et al., 2007; Morriss,
Abramowitz, Nelson, et al., 2009; Poon et al., 2010),
and no study has assessed the influence of this in
antineoplastic administrations. Regarding potential
severity, the number of severe errors decreased. This
finding is consistent with results from previous stud-
ies, where most medication errors had little effect on

KNOWLEDGE TRANSLATION
ɐ Barcode medication administration (BCMA) is effective in reduc-

ing the incidence and severity of medication administration errors

in outpatients with cancer.

ɐ BCMA reduces the types of error relating to the five rights and
those relating to wrong order of administration, which is a

chemotherapy-specific medication error.

ɐ BCMA implementation does not increase the length of stay for
treatment of patients with cancer.

E10 ONCOLOGY NURSING FORUM JANUARY 2018, VOL. 45 NO. 1 ONF.ONS.ORG

patient health (Bates, 1999; Franklin et al., 2007; Poon
et al., 2010; Taxis, Dean, & Barber, 2002).

As in the current study, most authors classified
the consequences of MAEs as benign (Bonkowski
et al., 2013; Morriss, Abramowitz, Nelson, et al.,
2009; Walsh et al., 2009), possibly because of the
low incidence of errors classified as severe (Bates,
1999; Bates, Boyle, Vander Vliet, Schneider, & Leape,
1995; Sakowski, Newman, & Dozier, 2008). No MAEs
were classified in the most severe categories after
intervention. As medical records were reviewed to
retrospectively assess the severity of MAEs, addi-
tional variability and a certain degree of subjectivity
may have influenced the classification of MAEs in
the current study.

Length of Stay of Patients
The results show that the implementation of a BCMA
system does not increase the length of stay of patients.
This supports and reinforces the results from other
researchers who either report no changes (Helmons
et al., 2009; Poon et al., 2006) or report a decrease in
the length of stay (Dasgupta et al., 2011; Dwibedi et
al., 2011; Franklin et al., 2007; Huang & Lee, 2011; Tsai
et al., 2010).

Limitations
Several limitations have been identified in this
study. For instance, the results show the experience
of using BCMA systems in an onco-hematology day
hospital and cannot be generalized to other settings;
however, they do provide information that adds to
the few studies that explore the impact of BCMA
on MAEs in the context of an onco-hematology day
hospital. In addition, regardless of intervention,
extension of the CPOE and additional changes nec-
essary for implementing the BCMA system could
have affected the incidence of observed MAEs,
leading to improved patient safety. However, both
technologies must be implemented at the same
time (Hagland, 2004). Also, changes because of
the long interval between pre-/postintervention
data collection cannot be excluded, but the lack
of change in the control group does not seem
to support this hypothesis. This issue should be
addressed in future studies (Strudwick et al.,
2017). Another limitation is that the selected con-
trol group differed from the intervention group in
terms of prescription, number of patients per day,
and pathology. Nurses, too, may have modified
their actions because they knew they were being
observed, as in the Hawthorne effect. Although the

observers received specific training for the project,
the impact of education and experience cannot be
ruled out because inter-rater reliability measures
were not obtained. This could be improved in
future studies. Similarly, assessment of the actual
severity of MAEs was based on expert opinion. This
adds a degree of subjectivity, which contrasts with
the proper methods for gathering and interpreting
data from medical records. Great difficulty is inher-
ent in attempting to determine the effect of MAEs
on patients’ quality of life.

Implications for Nursing
The results of this study have relevant implications
for nursing practice. The BCMA system is a useful
technology to check the five rights of medication
administration in an onco-hematology day hospital.
Although some specific errors related to chemother-
apy could be directly addressed by implementation
of a BCMA system, others are nonspecific and may
also be prevented. Further research is required to
investigate other types of errors (e.g., infusion rate)
and their impact. This will help to raise awareness
of the relevance of such errors. The results from this
study suggest that a BCMA system can improve the
safety and quality of the chemotherapy administra-
tion process. The need for an interprofessional team
should be highlighted, with special attention paid to
the oncology nurses who play an important role in
the success of the implementation and maintenance
of a BCMA system. A consolidated culture of patient
safety may influence the implementation and main-
tenance of a BCMA system. In addition, the use of
new technologies, such as BCMA, could help nurses
increase the time they spend on other direct patient
care activities. Oncology nurses are at the forefront of
chemotherapy error-prevention activities and play a
key role in implementing safety measures.

Conclusion
The main contribution of this study is to present the
first available evidence that the incidence of MAEs in
patients in an onco-hematology day hospital can be
reduced with the implementation of a BCMA system.
The authors also show that a BCMA system reduces
the potential and actual severity of errors. A BCMA
system was effective in reducing the following errors:
order of administration, pharmacy department medi-
cation transcription, dose omissions, and dose errors.
In addition, BCMA technology needs to be improved
to minimize frequently detected errors and to assess
high potential errors, such as the infusion rate and

JANUARY 2018, VOL. 45 NO. 1 ONCOLOGY NURSING FORUM E11ONF.ONS.ORG

the technique of administration. This technological
development can lead to an improvement in patient
safety.

Marta Macías, RN, PhD, is a nurse and Francisco A. Bernabeu-
Andreu, PhD, is a quality manager, both in the quality department
at the Príncipe de Asturias University Hospital in Alcalá de Henares,

Madrid; Ignacio Arribas, MD, PhD, is a physician in the clinical
biochemistry department at the Ramón y Cajal University Hospital

in Madrid; and Fatima Navarro, MD, is a medical oncologist in
oncology service and Gema Baldominos, PhD, is a pharmacist in
the pharmacy department at the Príncipe de Asturias University

Hospital. Macias can be reached at mmacias.hupa@gmail.com,

with copy to ONFEditor@ons.org. (Submitted June 2017. Accepted

August 2, 2017.)

The authors gratefully acknowledge the oncology nurses who

participated in all phases of the study. They also thank staff from

the hospital’s pharmacy department for their assistance with study

observations.

This research was funded by the Ministry of Health of Spain for the

implementation of patient safety strategies (RD. 829/2010, 25th

June, BOE 09.07.10).

Macias, Bernabeu-Andreu, Arribas, and Baldominos contributed to

the conceptualization and design and the manuscript preparation.

Macias, Navarro, and Baldominos completed the data collection.

Macias and Arribas provided statistical support. All authors

provided the analysis.

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