TITLE: Electronically Generated Medication Administration and Electronic Medication
Administration Records for the Prevention of Medication Transcription Errors:
Review of Clinical Effectiveness and Safety
DATE:
08 December 2016
CONTEXT AND POLICY ISSUES
In the hospital setting, medication errors represent and significant proportion of all medical
errors.1 These errors can lead to adverse drug events and can increase length of stay in
hospitals.2 Errors can occur at prescription, transcription, dispensation, and administration. 3
Human error is an important factor in all stages of potential medication errors and thus
information technology (IT) solutions are often sought in order to mitigate the risk of human
error.4 Transcription errors can occur when patient files and medication orders are being
updated from week to week and may be particularly susceptible to error due to healthcare
provider fatigue (e.g. files being updated at the end of a shift). Electronic health records,
computerized order entry systems, bar-code medication administration (BCMA) systems, and
electronic medication administration records (eMARs) are IT solutions that are often considered
in order to reduce such error.2,4
Electronically generated medication administration records (MARs), where the physician’s
medication order is entered into the pharmacy system and the administration record is printed
out and put into the patient file as opposed to updating by hand, and eMARs, whereby elements
of the prescribing and administration process includes bar code scans and digital
documentation, may be helpful in reducing transcription and administration errors. The current
review seeks to examine the clinical effectiveness of electronically generated MARs and eMARs
in preventing medication transcription errors in the acute care setting.
RESEARCH QUESTIONS
1. What is the clinical effectiveness of the use of electronically generated medication
administration records to prevent medication transcription errors in the acute care setting?
Disclaimer: The Rapid Response Service is an information service for those involved in planning and providing health care in
Canada. Rapid responses are based on a limited literature search and are not comprehensive, systematic review s. The intent is to
provide a list of sources of the best evidence on the topic that the Canadian Agency for Drugs and Technologies in Health (CADTH)
could identify using all reasonable efforts within the time allow ed. Rapid responses should be considered along w ith other ty pes of
information and health care considerations. The information included in this response is not intended to replace professional medical
advice, nor should it be construed as a recommendation for or against the use of a particular health technology. Readers are also
cautioned that a lack of good quality evidence does not necessarily mean a lack of effectiveness particularly in the case of new and
emerging health technologies, for w hich little information can be found, but w hich may in future prove to be effective. While CADTH
has taken care in the preparation of the report to ensure that its contents are accurate, complete and up to date, CADTH does not
make any guarantee to that effect. CADTH is not liable for any loss or damages resulting from use of the information in the report.
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2. What is the clinical effectiveness of the use of electronic medication administration records
to prevent medication transcription errors in the acute care setting?
KEY FINDINGS
No studies examining the use of electronically generated medication administration records
were identified and thus no conclusions can be made. Limited conclusions could be drawn
regarding the effect of electronic medication administration records on the reduction of
transcription errors. Based on the results of two cohort studies, the introduction of eMARs may
reduce the overall rates of medication errors and may not displace errors, however the effect
eMARs on transcription errors was not well reported. Further research may be warranted if the
goal of introducing eMARs is to reduce transcription errors regardless of whether overall error
rates are affected.
METHODS
Literature Search Methods
A limited literature search was conducted on key resources including PubMed, The Cochrane
Library, ECRI, University of York Centre for Reviews and Dissemination (CRD) databases,
Canadian and major international health technology agencies, as well as a focused Internet
search. No filters were applied to limit the retrieval by study type. Where possible, retrieval was
limited to the human population. The search was also limited to English language documents
published between January 1, 2011 and November 9, 2016.
Rapid Response reports are organized so that the evidence for each research question is
presented separately.
Selection Criteria and Methods
One reviewer screened citations and selected studies. In the first level of screening, titles and
abstracts were reviewed and potentially relevant articles were retrieved and assessed for
inclusion. The final selection of full-text articles was based on the inclusion criteria presented in
Table 1.
Population
Intervention
Comparator
Outcomes
Table 1: Selection Criteria
Inpatients (any age, any condition) in the acute care setting
Q1 - Electronically Generated Medication Administration Records
Q2- Electronic Medication Administration Record
Hand transcription of medication administration records
No active comparator
Q1 and Q2:
Effectiveness in preventing transcription errors
Prevention of medication errors
Patient safety
Occurrence of other errors Patient harm
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Study Designs
Health Technology Assessment, Systematic Reviews, Meta-Analyses,
Randomized Controlled Trials, Non-Randomized Studies
Exclusion Criteria
Articles were excluded if they did not meet the selection criteria outlined in Table 1, they were
duplicate publications, or were published prior to 2011.
Critical Appraisal of Individual Studies
The included cohort studies were critically appraised using the SIGN-50 methodology checklist
for cohort studies.5 Summary scores were not calculated for the included studies; rather, a
review of the strengths and limitations of each included study were described.
SUMMARY OF EVIDENCE
Quantity of Research Available
A total of 549 citations were identified in the literature search. Following screening of titles and
abstracts, 537 citations were excluded and 12 potentially relevant reports from the electronic
search were retrieved for full-text review. No potentially relevant publications were retrieved
from the grey literature search. Of these potentially relevant articles, 10 publications were
excluded for various reasons, while two publications met the inclusion criteria and were included
in this report. Appendix 1 shows the PRISMA flowchart of the study selection.
Summary of Study Characteristics
Further detail regarding study characteristics is included in Appendix 2, Table A1.
Study Design
Both of the included studies were non-randomized, prospective, pre/post cohort studies.3,6
Country of Origin
The two included studies were conducted in hospitals in the United States. 3,6
Patient Population
Both studies randomly observed nurses who administered doses of medication on the units
being studied.3,6
A single-centre study by McComas et al., involving 38 nurses, examined 156 cases (78 preintervention, 78 post-intervention) of medication administration to patients in a medical-oncology
unit as well as hospital-wide rates of medication error.3 Data were collected over the course of
12 months. The observations were made by the principle investigator.
A multi-centre study by Seibert et al., examined medication administration to patients in three
matched care units (medical-surgical, telemetry, and rehabilitation) in each of two non-teaching
community hospitals plus a medical-surgical intensive care unit (ICU) in one of the hospitals,
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and an emergency department, an inpatient oncology unit, and an outpatient oncology unit in
another hospital.6 Study observations were made by certified medical observers who were not
involved in patient care and did not interfere with nursing activities. If an error that could cause
harm was noticed by the study pharmacists, they corrected the error as discretely as possible.
Data were collected over the course of 12 months.
Interventions and Comparators
McComas et al., examined outcomes before and after the introduction of eMAR. 3 The system
used provided digital verification that the correct patient received the correct medication (correct
dose, time, and route of administration) and was recorded at the bedside. Prior to the
introduction of the system, nurses participated in a four hour educational session.
Seibert et al., examined outcomes before and after the introduction of bar-code assisted
medication administration (BCMA) plus eMAR.6 The hospital used the Meditech Magic BCMAeMAR system that included medication cards and in-room monitors with wireless scanners to
digitally record the medication administered to each patient. Medications, patient bracelets, and
paper orders all had machine readable bar codes.
Outcomes
McComas et al., examined medication efficiency as a primary outcome and medication errors
as a secondary outcome.3 In this report, medication efficiency is not discussed in detail, as it is
beyond the scope of this review. Medication errors comprised of prescription, transcription,
dispensation, and administration errors (measured separately and combined as overall error
rates). Injuries caused by medication errors were also reported. Investigators calculated
descriptive statistics (frequencies, percentages, standard error of the mean, and mean) and
performed t-tests and Pearson bivariate correlations in order to analyze the data.
Seibert et al., examined medication administration accuracy rates (calculated by dividing the
difference between opportunity for error and number of errors by 100X the opportunity for error)
as a primary outcome. They defined medication errors as “any discrepancy between a
prescriber’s interpretable medication order and what was administered to a patient (p. 211)”. 6
They further divided errors into target errors (i.e., errors that should have been caught by the
bar code system), opportunity for errors (doses that were ordered), total number of opportunities
for error (i.e., number of doses given plus those omitted) and total errors (i.e., errors that were
observed – included missed doses, administration of an unauthorized medication, a wrong
dose, incorrect route of administration, and incorrect timing of dose). They distinguished
between other errors and “wrong-time errors” by defining the latter as the administration of the
correct drug at the correct dose more than 60 minutes before or after the scheduled time. Chisquare (with Yates correction) statistics were calculated and the level of significance was set at
0.05.
Summary of Critical Appraisal
The two included studies had similar strengths.3,6 Both of the studies had clearly focused
questions, clearly defined outcomes and reliable exposure assessment.
A primary limitation of both studies is the presence of an observer when the medication
administration systems were being used and doses were being administered. It is unclear
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whether the presence of the trained observers had an effect on the intervention and behaviour
of nurses.
In the single-center McComas study,3 while nurses performing medication administration were
randomly observed, the total number of cases observed was reported, not the total number of
opportunities for medication error, which may represent an inaccurate estimate. It was unclear
whether or not the study was adequately powered to detect meaningful differences.
The multi-centre Seibert study6 included a sample size that was sufficiently powered to detect
meaningful differences (based on an a priori calculation), randomly observed the nurses
administering doses, and observed various units within the hospital and therefore observed a
wide range of patient types and medication types. They also presented the number of
opportunities for error alongside the administration accuracy rates. However, authors did not
discuss the limitations of their own methodology or study. There was no acknowledgement of
factors such as the effect of an observer on behaviour or the limitations of a cohort design.
While both studies 3,6 randomly observed the nurses administering doses, the cohort design may
limit the ability to make causal conclusions regarding the interventions being studied. Factors
such as educational initiatives, increased profile of reducing errors, or other hospital or cultural
factors could have influenced the rates of medication administration errors in ways that were not
accounted for.
Further detail regarding critical appraisal is included in Appendix 3, Table A2.
Summary of Findings
What is the clinical effectiveness of the use of electronically generated medication
administration records to prevent medication transcription errors in the acute care setting?
No relevant studies were identified regarding the use of electronically generated MARs to
prevent medication transcription errors in the acute care setting.
What is the clinical effectiveness of the use of electronic medication administration records to
prevent medication transcription errors in the acute care setting?
With respect to overall medication error rates, the results of the single-centre McComas study3
showed a statistically significant decrease from 11.0 errors per month before the introduction of
eMAR to 5.3 per month following the introduction of eMAR (P = 0.034).3 Injuries caused by
medication error decreased from 0.67 per month to 0.33 per month after the introduction of
eMAR (P value not reported). The separate effect sizes of error rates for prescription,
transcription, dispensing, and administration error rates were not provided and were only
reported in graph-form. Based on visual interpretation of the graph presented in the publication,
prescription, transcription, and dispensing errors decreased by at least or more than half
between the pre- and post-eMAR periods. Administration error rates, which were the highest of
the error rate types both before and after eMAR, also decreased, but by proportionally less than
the others.
Overall accuracy rates of medication administration rates of the multi-centre Seibert study6 were
reported by hospital and by hospital unit. There was a statistically significant increase in overall
accuracy rate following the introduction of BCMA-eMAR for the first hospital both when wrong-
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time errors were included (89% vs. 90%; P = 0.002) and excluded (92% vs. 96%; P <0.001).
For the second hospital, there was no significant difference following the introduction of BCMAeMAR when wrong-time errors were included (89% vs 91%; P = NR) but was significantly
increased when they were not included (93% vs. 96%; P = 0.015). Patient harm was not
reported. Authors did report that new medication errors were not reported. Rates for the
different units in each hospital are presented in Appendix 4, Table A3.
Limitations
The small number of studies and the lack of Canadian studies are both limitations to the
generalizability and applicability of this review to the Canadian context. While a variety of units
within hospitals were examined in the studies, because of the limited number of studies, it is
unclear if the results are valid in other hospitals or types of hospitals.
The lack of reporting specific effect sizes and information regarding transcription errors as a part
of medical errors and of eMAR separate from BCMA further limits the ability to draw
conclusions.
CONCLUSIONS AND IMPLICATIONS FOR DECISION OR POLICY MAKING
No relevant studies were identified regarding the use of electronically generated MARs to
prevent medication transcription errors in the acute care setting. Based on the results of two
non-randomized cohort studies, the use of eMAR may lead to reductions in overall rates of
medication administration errors.3,6 Medication transcription errors were included in overall error
rates in both of the included studies, however, despite a reduction in transcription errors, the
effect size was not reported in one of the studies 3 and the second did not specifically report
transcription error rates, however they did conclude that error rates decreased and errors were
not displaced.6 Therefore, no firm conclusions can be made regarding the effect of the
introduction of eMAR on the reduction of transcription errors. Additionally, as one of the studies
included both eMAR and BCMA, it is unclear what the impact of eMAR alone was. As
information technologies may be introduced together (such as eMAR with BCMA), and some
eMAR systems include bar code technology, this may not be an issue. One study concluded
that eMAR did not lead to new errors or the displacement of medication administration errors. 6
Further research regarding the impact of eMAR on transcription errors may be warranted if the
goal of introducing eMAR is to reduce transcription errors regardless of whether overall error
rates are affected. As no information regarding electronically generated MARs was identified, if
there is interest in introducing the technology, further research regarding how this type of record
may have an impact on transcription errors is warranted.
PREPARED BY:
Canadian Agency for Drugs and Technologies in Health
Tel: 1-866-898-8439
www.cadth.ca
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REFERENCES
1.
Gorbach C, Blanton L, Lukawski BA, Varkey AC, Pitman EP, Garey KW. Frequency of and
risk factors for medication errors by pharmacists during order verification in a tertiary care
medical center. Am J Health Syst Pharm. 2015 Sep 1;72(17):1471-4.
2.
Berdot S, Roudot M, Schramm C, Katsahian S, Durieux P, Sabatier B. Interventions to
reduce nurses' medication administration errors in inpatient settings: a systematic review
and meta-analysis. Int J Nurs Stud. 2016 Jan;53:342-50.
3.
McComas J, Riingen M, Chae KS. Impact of an electronic medication administration
record on medication administration efficiency and errors. Comput Inform Nurs. 2014
Dec;32(12):589-95.
4.
Stultz JS, Nahata MC. Preventability of voluntarily reported or trigger tool-identified
medication errors in a pediatric institution by information technology: a retrospective cohort
study. Drug Saf. 2015 Jul;38(7):661-70.
5.
Methodology checklist 3: cohort studies [Internet]. Edinburgh (UK): Scottish Intercollegiate
Guidelines Network (SIGN); 2011 Mar. [cited 2016 Dec 1]. Available from:
http://www.sign.ac.uk/methodology/checklists.html
6.
Seibert HH, Maddox RR, Flynn EA, Williams CK. Effect of barcode technology with
electronic medication administration record on medication accuracy rates. Am J Health
Syst Pharm. 2014 Feb 1;71(3):209-18.
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APPENDIX 1: Selection of Included Studies
549 citations identified from
electronic literature search and
screened
537 citations excluded
12 potentially relevant articles
retrieved for scrutiny (full text, if
available)
0 potentially relevant
reports retrieved from
other sources (grey
literature, hand
search)
12 potentially relevant reports
10 reports excluded:
-irrelevant intervention (6)
-irrelevant outcomes (1)
-irrelevant study type (2)
-published in language other than
English (1)
2 reports included in review
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APPENDIX 2: Characteristics of Included Publications
Table A1: Characteristics of Included Clinical Studies
First Author,
Publication
Year,
Country,
Study Name
McComas,
3
2014, USA
Seibert, 2014,
6
USA
Study Design;
Study
Objectives
Patient
Characteristics
Interventio
n(s)
Comparator(
s)
Prospective
Cohort
(pre/post); to
determine the
impact of the
implementation
of eMAR on
medication
administration
efficiency and
medication
errors.
Prospective
cohort
(pre/post); to
determine the
effect of the
combination of
barcodeassisted
medication
administration
(BCMA) and
eMAR on
medication
administration
errors.
156 cases (78 pre,
78 post) of
medication
administration
activities in the
medical oncology
unit.
introduction
of eMAR
pre-eMAR
Medical errors were
examined hospitalwide
3 matched patient
care units in each of
two community, nonteaching hospitals
(medical surgical,
telemetry,
rehabilitation), plus a
medical-surgical
ICU, an emergency
department, an
inpatient oncology
unit, and an
outpatient oncology
unit in one hospital.
BCMA plus
eMAR
pre-BCMA
plus eMAR;
voluntary
reporting of
errors during
that period
Clinical Outcomes
Primary outcome:
medication
administration
efficiency
Secondary:
medication errors
(prescription,
transcription,
dispensation, and
administration
errors)
Rate of medication
administration
a
errors.
(Nurses who
administered at least
one medication to
adult patients in one
of the selected units
during the study
period observation
times were randomly
observed)
AB = Alberta; BCMA = bar-code-assisted medication administration; eMAR = electronic medication administration record; ICU =
intensive care unit; MAO = medication administration omission
a
Authors defined this as: “any discrepancy between a prescriber’s interpretable medication order and w hat was administered to a
patient. Drug administration more than 60 minutes before or after the scheduled time w as considered a w rong-time error”
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APPENDIX 3: Critical Appraisal of Included Publications
Table A2: Summary of Critical Appraisal of the Included Cohort Studies Using the Sign 50 tool 5
Sign 50 Item
First Author, Year
McComas 3
Seibert6
The study addresses an appropriate and clearly focused question
y
y
The two groups being studied are selected from source populations that
c/s
c/s
are comparable in all respects other than the factor under investigation.
The study indicates how many of the people asked to take part did so in
n
n
each of the groups being studied.
The likelihood that some eligible subjects might have the outcome at the
n
n
time of enrolment is assessed and taken into account in the analysis?
What percentage of individuals or clusters recruited into each arm of the
n/a
n/a
study dropped out before the study was completed?
Comparison is made between full participants and those lost to follow -up,
n/a
n/a
by exposure status.
The outcomes are clearly defined
y
y
The assessment of outcome is made blind to exposure status
n
n
Where blinding was not possible, there is some recognition that
n
n
knowledge of exposure status could have influenced the assessment of
outcome.
The measure of assessment of exposure is reliable.
y
y
Evidence from other sources is used to demonstrate that the method of
n/a
n/a
outcome assessment is valid and reliable.
Exposure level or prognostic factor is assessed more than once
y
y
The main potential confounders are identified and taken into account
y
n
adequately in the design and analysis
Confidence intervals are provided
n
n
Taking into account clinical considerations, your evaluation of the
.
The authors do not discuss the limitations of
methodology used, and the statistical power of the study, do you think
There is no indication of the number of
their studies.
there is clear evidence of an association between exposure and outcome? medication administration occurrences –
while there was random observation of
Direct observation could have influenced the
medication administration from the day
actions of the staff.
and night shift, it is unclear if this was a
The fact that multiple types of units that deal
significant portion of the number of
with many types of medications were
observations. The presence of the
observed increases the generalizability of the
observer could have influenced
study.
administration behaviour. This was a
single-centre and single-unit study,
Sample size was calculated.
which may limit generalizability for the
efficiency results. The medication error
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Table A2: Summary of Critical Appraisal of the Included Cohort Studies Using the Sign 50 tool 5
Sign 50 Item
First Author, Year
McComas 3
Seibert6
results were hospital-wide, thus the
single-centre lack of generalizability
applies but it may be slightly more
generalizable than the efficiency results
due to being hospital-wide.
Full results for the type of medication
administration errors are reported in
graphical form only, and P values are
not reported.
Summarize the author’s conclusions. Add any comments on your own
After adjusting for confounders, eMAR
There were significant decreases in
assessment of the study, and the extent to which it answers your question neither increased nor decreased
medication administration errors (increases in
and mention any areas of uncertainty raised above. This section is very
medication administration efficiency.
medication accuracy) following the
important and will appear on the evidence table.
After the implementation of eMAR there
introduction of BCMA-eMAR when compared
was a ‘marked’ decrease in the monthly with voluntary reporting. BCMA-eMAR did not
number of medication error events (over introduce a new type of error and the
multiple categories of errors) and of
frequency of errors that were preventable by
medication error injuries.
the technology decreased significantly.
BCMA = bar code medication administration c/s = can’t say; eMAR = electronic administration record; n/a = not applicable; no = no; y = yes
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APPENDIX 4: Main Study Findings and Author’s Conclusions
Table A3: Summary of Findings of Included Studies
Main Study Findings
Author’s Conclusions
McComas, 20153
Total time (mean; SD) for medication
 After adjustment for confounding variables
administration (including preparation,
(such as using multiple machines,
administration, documentation, and
distractions, and interruptions), eMAR did
distractions/interruptions):
not result in increased or decreased
 pre-eMAR: 11.3 ± 8.4 minutes
medication administration efficiency.
 post-eMAR: 14.4 ± 10.2 minutes
 There was a statistically significant
reduction in medication errors following the
 mean difference: +3.1
implementation of eMAR.
 t = 2.080; P = 0.039
 Medication administration error rates were
Medication errors (mean):
the most frequent error rates both before
 hospital-wide medication error events:
and after eMAR introduction.
o pre-eMAR: 11.0/month
o Computerized order entry and baro post-eMAR: 5.3/month
code-assisted medication
o P = 0.034
administration were not part of the
 medication error-related injuries (mean):
protocol.
o pre-eMAR: 0.67/month
 Authors concluded that quality of care
o post-eMAR: 0.33/month
improved.
 Prescription, transcription, and dispensing
errors decreased by at least or more than
half between the pre- and post-eMAR
periods.a Administration error rates, which
were the highest of the error rate types
both before and after eMAR, also
decreased, but by proportionally less than
the others.a
Seibert, 20156
Hospital 1 – overall accuracy:
 Medication accuracy rates were
 pre-BCMA-eMAR: 89%
significantly improved following the
introduction of BCMA-eMAR.
 post-BCMA-eMAR: 90%
 New medication errors were not introduced
 P = 0.0015
 when wrong-time errors were excluded,  BCMA-eMAR and direct observation were
more effective in preventing errors than
pre-rate was 92% and post-BCMAvoluntary reporting.
eMAR rate was 96% (P = 0.000008)
Hospital 2 – overall accuracy:
 no significant change in overall
accuracy when wrong-time errors were
included (89% vs 91%)
 when wrong-time errors were excluded.
pre-BCMA-eMAR rate was 93%, postrate was 96%; P = 0.015
Hospital 1 – Units:
 Medical-Surgical
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




Table A3: Summary of Findings of Included Studies
Main Study Findings
Author’s Conclusions
o no significant change in
accuracy after introduction of
BCMA-eMAR when wrong-time
errors were included (88% vs.
93%) or excluded (93% vs.
96%)
Telemetry
o significant decrease in
medication accuracy rates after
introduction of BCMA-eMAR
when wrong time errors were
included: 94% vs. 88%; P =
0.04
o rates remained unchanged
when wrong-time errors were
excluded (94% vs. 94%)
Rehabilitation
o no significant change in
accuracy after introduction of
BCMA-eMAR when wrong-time
errors were included (86% vs.
85%)
o rates were significantly lower
when wrong-time errors were
excluded: 90% vs. 94%; P =
0.004
Inpatient oncology
o medication accuracy rates
increased from 89% to 94% (P
not significant)
o when wrong-time errors were
excluded, the results remained
not statistically significant
Outpatient oncology
o medication accuracy rates
remained unchanged
o when wrong-time errors were
excluded, the rates were 97%
pre- and 98% post-BCMAeMAR (P = 0.006)
Emergency department
o medication accuracy rates
increased from 86% to 95%
following BCMA-eMAR (P =
0.0015)
o when wrong-time errors were
excluded, the rates were 87%
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Table A3: Summary of Findings of Included Studies
Main Study Findings
Author’s Conclusions
and 99% (P = 0.000002)
Hospital 2 – Units:
 Medical-surgical
o no significant change in
accuracy after introduction of
BCMA-eMAR when wrong-time
errors were included (89% vs.
92%) or excluded (94% vs.
93%)
 Telemetry
o no significant change in
accuracy after introduction of
BCMA-eMAR when wrong-time
errors were included (89% vs.
89%)
o when wrong-time errors were
excluded, the rates were 93%
vs. 98%; P = 0.006
 Rehabilitation
o accuracy rates significantly
increased after the introduction
of BCMA-eMAR both when
wrong-time errors were
included (87% vs. 94%; P =
0.0005) and excluded (92% vs
97%; P = 0.002)
 ICU
o medication accuracy rates
decreased from 94% to 89%
following BCMA-eMAR when
wrong-time errors were
included (P = 0.004) and when
wrong-time errors were
excluded (96% to 88%; P =
0.003)
BCMA = eMAR = electronic medication administration record; ICU = intensive care unit
a
Results w ere presented in a bar-graph form; numerical error rates and P values w ere not reported. The authors do, how ever, report
that the rates are statistically significantly lower following the implementation of eMAR.
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