








































Anesthesia eJournal
Volume 3 Issue 2 2015

AEJ

Educated Hand Publishing LLC 
“The Science Behind the Art”  

 Anesthesia eJournal - Online
ISSN 2333-2611

Medication errors are an important public health problem with high human and financial costs. Medication errors in 
anesthesia can result in patient morbidity or mortality and should be preventable.  Evidence in the literature supports 
increasing computer access to reduce the number of medication errors. The purpose of this study was to determine if 
medication errors could be reduced in one university hospital through a clinical intervention of increasing computer 
access in the post-anesthesia care unit. A quantitative retrospective chart review was conducted. A statistical test of two 
independent proportions was used to examine the occurrence of schedule II (fentanyl) and IV (midazolam) controlled 
substance documentation errors before and after increasing computer access in the post-anesthesia care unit. Access 
to computers appeared to be associated with a reduction of medication errors from 2.3% to 1.5%. The compliance rate 
increased from 97.6% to 98.5%. The reduction in the error percentage was significant (z = 2.045, p = 0.04). Our findings 
provide objective evidence for the support of continuous process improvement to reduce medication errors in anesthesia.

KEYWORDS: medication errors; patient safety; anesthesia documentation; medication documentation; electronic 
anesthesia record

Abstract

Reducing Intravenous Narcotic Documentation Errors on the Electronic Anesthesia 
Record: A Quality Improvement Project
John M. Borza DNP, MBA, CRNA
Judith A. Kaufmann Dr.PH, FNP-BC
Thomas W. Cline Ph.D., MBA

Affiliation:
University of Pittsburgh Medical Center, Pittsburgh, PA, USA. Dr Borza is Clinical Director Nurse Anesthesia. Email: borzajm@upmc.edu

Funding/Conflict of Interest Disclosure: 
None, IRB -University of Pittsburgh, Quality Improvement Review Committee, QI Review Number 0001579

INTRODUCTION
Medication errors are important public health problems with high human and financial costs. Medication errors can result in patient 

morbidity or mortality and should be preventable. A medication error is defined as a failure in the treatment process that leads to, 
or has the potential, to lead to harm to the patient.1 Yet the literature indicates that medication errors exist and must be addressed.2 
In anesthesia, medication errors are particularly problematic and are one of the most prevalent contributors to iatrogenic harm.3 The 
Institute of Medicine (IOM) report To Err is Human identified patient safety as a significant problem and suggested that efforts to 
improve patient safety must focus on systems rather than providers.5,6 Medication errors are an appropriate area on which to focus 
efforts for improving patient safety.6 A substantial need exists for evaluation of interventions to reduce errors. 



BACKGROUND AND SIGNIFICANCE 
Medication errors in the practice of anesthesia have long 

afflicted the specialty.7 The first documented medication error 
related to the administration of anesthesia was in 1848. A 
15-year-old girl, Hannah Greener of the United Kingdom, died 
after receiving a chloroform anesthetic for a minor procedure.8 
From the time of that earliest report, medication errors during 
the administration of anesthesia have persisted. Cooper and 
Nossaman7 observed that even though it is common knowledge 
that medication errors occur in anesthesia, there are few published 
studies on medication errors. Cooper and Nossaman’s7 systematic 
review contained only 14 articles, 3 of which were symposium 
reviews on medication errors. Only 5 articles using surveys 
specifically addressed medication errors during the administration 
of anesthesia. Despite the reports on medication errors and 
adverse events, few of the studies within the systematic review 
specifically addressed the rate of medication errors in anesthesia 
practice until 2001. Bowdle9 reviewed nearly 6000 closed or 
settled anesthesia malpractice claims and found 205 medication 
errors. Medication errors resulted in 24% mortality and 34% 
morbidity with an estimated annual cost of $2.8 million for a 
700-bed hospital. In 2011, Hanna and Levine3 reported that 1 
error occurs for every 133 anesthetics. Flynn et al10 reported that 
there are 300 near misses for every error reported. The national 
cost of all hospital medication errors is estimated to exceed $3.5 
billion dollars annually,11 and up to 7000 patients die each year as 
a result of medication errors.3 

On the basis of earlier reports on anesthesia errors, the Robert 
Wood Johnson Foundation reinforced the conclusion that a key 
to reducing patient risk is to shift the focus from individuals, 
who will always make some errors, to systems, which can be 
redesigned to help prevent errors.7 The IOM report (2006), the 
Joint Commission (2008), and the Anesthesia Patient Safety 
Foundation (2010) recommended changes in work processes to 
reduce medication errors.7 

Medication documentation errors occur despite knowledgeable 
and competent anesthesia providers. The problem of medication 
administration in anesthesia is of particular concern because of 
the potent agents administered. For the present study, a baseline 
evaluation of medication errors was undertaken. In an analysis 
of 2 months of electronic anesthesia records compared with 
pharmacy controlled substance sheets of schedule II (fentanyl) 
and IV (midazolam) medications at a university medical center, 
63 intravenous narcotic medication errors were identified 
among 2495 anesthetic cases. Three types of medication 
documentation errors were identified. The least common 
medication documentation error, with an error rate of 7.6 per 
1000, was that the anesthesia provider did not sign the pharmacy 
controlled substance sheet. The second most common error, with 
an error rate of 6.4 per 1000, was that the anesthesia provider 
miscounted on the pharmacy narcotic sheet, but the correct 
medication dosage was administered to the patient. In most 
cases found in the data, with an error rate of 15.3 per 1000, the 
patient was administered the medication, but the medication was 
not recorded on the electronic anesthesia record. There was no 
reported harm to patients, but medication errors place the patient 

at risk. Intravenous narcotic medication documentation errors on 
the electronic anesthesia record may result in patient morbidity 
or mortality. Inaccurate or incomplete documentation can lead 
to over-medication or under-medication, resulting in potential 
harm.

Cause analysis revealed several factors that contributed to the 
documentation errors. These factors encompassed technology, 
policies and regulations, system processes, and accountability. 
There was a lack of computer access in patient care areas, a lack 
of real-time decision support, a lack of anesthesia providers who 
adhered to documentation policy, an inefficient electronic record 
conversion process that did not include all patient care areas, a 
lack of a clear documentation process that included a process 
to detect documentation errors, and a lack of counseling after 
identification of a documentation error. 
PURPOSE OF STUDY

Based on the above baseline evaluation of anesthesia-related 
medication errors, the primary aim of this quality improvement 
project was to achieve 100% accuracy in documenting intravenous 
schedule II and IV controlled substances on the electronic 
anesthesia record within the facility. This quality improvement 
project will enable the university medical center to meet US Drug 
Enforcement Agency requirements and comply with university 
medical center policies.
REVIEW OF THE LITERATURE

In preparation for the planning of this research translation 
study, a comprehensive evaluation of the literature for medication 
errors, medication reconciliation, and quality improvement design 
was performed. No inclusion or exclusion criteria were utilized 
because of the limited number of articles published on medication 
errors in anesthesia. Databases utilized for the search were 
PubMed and CINAHL. Search terms entered into PubMed were 
(“medication reconciliation methods” AND “anesthesia”), causes 
of reconciliation errors, anesthesia AND safety AND decrease 
morbidity, medication reconciliation, PDSA, and documentation 
errors on the anesthesia record. The search term entered into 
CINAHL was “develop a medication reconciliation process.” The 
search strategy identified 806 citations. After title and abstract 
review, 13 articles were considered relevant. By hand searching the 
reference lists of relevant articles and by use of the Google search 
engine, 14 additional articles were found to be relevant. A total of 
27 articles were pertinent to the study (Figure 1). 

Figure 1. Results of the Literature Search: Evidence Base for 
the Intervention.

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Volume 3 Issue 2 2015



The level and the quality of the accepted articles were judged 
by using the Johns Hopkins Evidence Level and Quality Rating 
Scale.12 Rating scales present a structured way to differentiate 
evidence of varying strengths and quality. Strong evidence of 
high quality more likely represents best practice than evidence of 
lower strength and less quality. Level I of the 5 levels used in the 
rating schemes indicates evidence obtained from an experimental 
study, randomized controlled trial (RCT), or systematic review of 
RCTs, with or without meta-analysis. Level II indicates evidence 
obtained from a quasi-experimental study or systematic review 
of a combination of RCTs and quasi-experimental studies, or 
quasi-experimental studies only, with or without meta-analysis. 
Level III indicates evidence from a quantitative nonexperimental 
study; systematic review of a combination of RCTs, quasi-
experimental, and nonexperimental studies, or nonexperimental 
studies only with or without meta-analysis; or qualitative study 
or systematic review of qualitative studies, with or without a 
meta-synthesis. Level IV indicates expert opinion of respected 
authorities and/or nationally recognized expert committees or 
consensus panels based on scientific evidence. Level V, being 
the lowest level, indicates experiential and nonresearch evidence. 
Quality is based on a scale from A to C with A being the highest 
and C being the lowest. Evidence with a quality rating of A is 
consistent; has generalizable results, a sufficient sample size for 
the study design, and adequate control; has definitive conclusions; 
and has consistent recommendations based on comprehensive 
literature review that includes thorough reference to scientific 
evidence. Evidence with a quality rating of B has reasonably 
consistent results, a sufficient sample size for study design, some 
control, fairly definitive conclusions, and reasonably consistent 
recommendations based on fairly comprehensive literature review 
that includes some reference to scientific evidence. Evidence with 
a quality rating of C has inconsistent results, insufficient sample 
size for the study design, and a lack of conclusions.12 Of the 
relevant articles identified, 1 ranked at level I, 2 at level II, 9 at 
level III, 11 at level IV, and 4 at level V. All varied from A to C in 
quality (Figure 2). 

Figure 2. Johns Hopkins Evidence Level and Quality Rating 
Scale.

The consistent findings from these articles, guidelines, and best 
practices suggested that individual and system factors contribute 
to medication errors. In health care, accountability for medication 
errors is commonly attributed to the individual, and the “five 
rights” in medication administration is commonly used as the 
benchmark for individual performance. The “person” approach 

seeks to attribute causes to the individual, whereas the “systems” 
approach attributes that human error is to be expected. It is 
suggested that when system barriers are not effective, errors will 
occur.13  Information technology is recommended to overcome 
such system barriers. Information technology can improve 
anesthesia patient safety by minimizing medication errors and 
adverse events.14  Implementing a multimodal system that 
includes real-time charting was proven to be effective in reducing 
medication errors in a prospective randomized open label clinical 
trial.4 It is also recommended that technology be implemented at 
every anesthesia location.2,7 

There were a number of limitations to the review of the 
literature. These limitations were that the definition of a 
medication error is debatable,6 the studies performed were at 
single health care facilities,15 staff were resistant to change,11 
errors were reported on a voluntary basis,7 and studies were not 
blinded.4

THEORETICAL MODELS
Two theoretical models were used to develop this quality 

improvement project: the Diffusion of Innovation theory of 
Rogers16 and the translation framework Plan-Do-Study-Act 
(PDSA) Cycle. Rogers’ Diffusion of Innovation was selected 
because it outlines a process for change, which starts with an 
initial few and grows until critical mass is achieved. The PDSA 
Cycle is the accepted format used when implanting a new process 
improvement in the work setting. 

The Diffusion of Innovation Theory is often regarded as a 
valuable change model for guiding technological innovation 
when the innovation itself is modified and presented in ways that 
meet across all levels of adopters. It also stresses the importance 
of communication and peer networking within the adoption 
process.17 Diffusion of innovation refers to the process that occurs 
as people adopt new ideas. Bridging the evidence gap will not 
be achieved simply by informing clinicians about the evidence.18 

Rogers outlined this process of change and stressed that, in most 
cases, an initial few are open to the new idea and adopt its use. 
As these early innovators “spread the word,” more people become 
open to the idea and a critical mass is reached. Over time, the 
innovative idea diffuses among the staff until a saturation point 
is achieved. Rogers distinguished 5 categories of adopters of 
an innovation: innovators, early adopters, early majority, late 
majority, and laggards. Rogers estimated the percentages for each 
category, which take the shape of a normal bell curve (Figure 3).

Figure 3. Diffusion of Innovation Adopter Categories. Source: 
Kaminski, 2011.17

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Volume 3 Issue 2 2015



The PDSA cycle is used to develop and test rapid change 
for quality improvement. The main objective in PDSA quality 
improvement is to assess whether an intervention that changes 
a process produces an improvement outcome. The PDSA cycle 
uses the scientific method to answer, “How will we know that 
a change is an improvement?” The PDSA model advocates 
the formation of a hypothesis for improvement (Plan), a study 
protocol with collection of data (Do), analysis and interpretation 
of the results (Study), and the iteration for what to do next (Act) 
(Figure 4). For the present study, the “Plan” was to reduce the 
number of documentation errors of schedule II and IV controlled 
narcotic substances on the electronic anesthesia record. The “Do” 
was to increase access to computers in the post-anesthesia area. 
The “Study” was to statistically analyze the results, and the “Act” 
was to determine whether the cycle needed to be performed again 
with a modified intervention or whether a process change could 
proceed in practice.

Figure 4. Plan-Do-Study-Act Cycle.

METHODS
Study Design

The study design was a quantitative retrospective chart review 
to examine the occurrence of schedule II and IV controlled 
substance documentation errors before and after increasing 
computer access in the post-anesthesia care unit. 
POPULATION AND SETTING

The study received Institutional Review Board approval from 
the university and the university medical center. A retrospective 
chart review included all surgical patients undergoing anesthesia 
in the main operating suite from March 3, 2014, to April 2, 
2014. Charts for patients who had endoscopy procedures, off-site 
procedures, and procedures such as cardiac catheterizations in the 
special procedure unit were excluded. 
SAMPLE SIZE ESTIMATION

For this study we used the alpha significance level of 0.05, and 
the standard power of 80 percent, as well as a compliance rate of 
0.03 for the pre-intervention month and a zero for the post-
intervention month as one for 100% compliance. A final sample 
size of 320 was calculated for the pre-intervention month and the 
same sample size for the post-intervention month. 
INTERVENTION

The intervention was designed to increase access to computers 

in the post-anesthesia care unit at the bedside during the transfer 
of care process. There were dedicated computers for the anesthesia 
providers. If a computer was unavailable because another 
anesthesia provider was using the machine, the post-anesthesia 
care unit registered nurse provided access to the bedside 
computer. The anesthesia providers completed documentation 
and used their computer screen to provide a transfer of care to the 
post-anesthesia care unit registered nurse. 

The study was introduced at an operating suite meeting, which 
included the post-anesthesia care unit staff, anesthesia staff, and 
the operating suite staff as well as the operating suite leadership. 
After a slide presentation of the capstone project, a question and 
answer period was available to address concerns and questions.

Reliability of documentation and adherence to the intervention 
protocol was maximized by the support of anesthesia leadership, 
who observed the compliance of anesthesia providers using 
the dedicated computers. Anesthesia providers who chose not 
to participate were encouraged to do so, but participation for 
the purposes of this study period was not mandated. Although 
exact compliance rates were not obtained, a general consensus 
was that nearly all of the anesthesia providers participated on 
various shifts. Overall, the post-anesthesia care nurses observed a 
consistent use of the computers.
TIME PERIOD

The period for the study was from January 2013 through April 
2014. During the intervention period, 2 emails were sent to the 
anesthesia staff to motivate and reinforce engagement. 
MEASUREMENTS

The study compared narcotic medication documentation errors 
before and after the initiation of increased computer access in the 
post-anesthesia care unit. Data were collected by using a custom-
designed Microsoft Excel (Microsoft Corp, Redmond, WA) 
spreadsheet (Appendix I). Demographic variables were collected. 
The outcome variables were schedule II and IV controlled 
substance documentation errors. The data sources were the 
electronic anesthesia record, the pharmacy narcotic form, and the 
intraoperative note on the electronic anesthesia record. 

The data abstractors who reviewed and coded each chart had an 
important role with respect to data quality.19 Two data abstractors 
were trained to collect the data with one abstractor having no 
anesthesia background to reduce bias. Inter-rater reliability was 
achieved by using Cohen’s kappa. With the range of -1, which 
demonstrates perfect disagreement, to +1, which demonstrates 
perfect agreement, the study rated a score of +1 for reviewing 
1612 charts.19

DATA COLLECTION
All data were collected on paper and computers. All data were 

de-identified and protected in a locked office and on computers 
that were password protected. All participants and individuals 
associated with the quality improvement study adhered to the 
university medical center’s policies on confidential information, 
proper handling of protected health information outside of the 
medical center, and electronic mail and messaging. 

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Volume 3 Issue 2 2015



RESULTS
Pre- and post-intervention compliance rates and medication errors of schedule II and IV controlled substances were collected from 

January 2013 to April 2014. A total of 4107 anesthetic cases were included in the study. Additional demographic variables collected 
included assigned study identification number, surgical date, patient FIN number, gender, age, American Society of Anesthesiologists 
(ASA) physical status, types of error, surgical procedure, operating room number, medication variance, anesthesia providers, surgeon, 
circulating registered nurse, scrub technician, type of narcotic storage, and whether the event was in the AM or PM for future studies. 

Medication errors decreased from a combined January-February 2013 error rate of 23.6 per 1000 to an error rate of 14.9 per 1000 
in March 2014. The January error rate was 30.0 and the February error rate was 16.7 per 1000, respectively. The compliance rate in 
March increased to 98.5% from the combined rate of 97.6% for January-February. The January compliance rate was 97.0% and that 
for February was 98.3%. The error percentage rate decreased in March to 1.48% from 2.36% for January-February combined. The 
January error percentage rate was 3.0% and that for February was 1.67%. Comparing the medication error rate to the national average, 
real-time bedside computer access reduced the error rate from 3.15 times the national average in January-February combined to 1.98 
times the national average for the intervention month (March). The error rate for January represented 3.99 times the national average, 
whereas that for February was 2.23 times the national average (Table 1). 

Table 1. Medication Error Rate

March showed a significant reduction in error percentage compared with January 2013 (z= 2.69, p = 0.007). Thus, we can conclude 
that the proportion of errors in March is significantly lower than errors in January, at the 0.01 level of significance. March also showed 
a reduction in error percentage compared with February; however, the difference in the two proportions was not statistically significant 
(z = 0.38, p = 0.699). Comparing March with January and February combined showed a significant reduction in error percentage (z = 
2.04, p = 0.04; Table 2).Table 2. Significance of Medication Error Rates

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Volume 3 Issue 2 2015



DISCUSSION
Compared with a lack of computer access at the bedside in 

the post-anesthesia care unit, access to computers appeared to be 
associated with a reduction of medication errors from 2.3% to 
1.5%. The compliance rate increased from 97.6% to 98.5%. It is 
unknown why January 2013 had an error rate of 3% and February 
1.67% with compliance rates of 97% and 98.3%, respectively, 
while the same documentation process occurred. Owing to the 
disparity in errors between January and February 2013 with no 
known cause, the 2 months were combined for the purposes of 
this study, assuming that January could have been a month with 
less vigilance in documentation than February. Although it was 
shown that the intervention was associated with statistically 
significant (p=0.04) improvement in the error rate, the results 
were still below the national average of 0.752 error percentage 
and 99.2% compliance. The question arises of whether making 
participation in the study mandatory would have decreased the 
error rate and increased compliance more to meet or exceed the 
national averages.

Our findings were also consistent with a previous study by 
Merry et al,4 which described a reduction in medication errors 
by using a multimodal approach, whereas the present study 
implemented a single intervention. Merry et al did not identify 
which intervention had the largest impact.

Previous studies that addressed medication errors in anesthesia 
were limited to voluntary surveys. Even though our study 
was voluntary, the medication errors were extracted from the 
electronic anesthesia record and pharmacy narcotic sheet, which 
maximized objectivity and the accuracy of the results.
LIMITATIONS

The study was implemented at a single university setting. One 
of the data abstractors was an anesthesia provider who could 
have been a source of bias. Anesthesia leadership designed and 
conducted the study, which may have been a source of bias. 
The anesthesia providers may have felt pressured to participate. 
Comparisons of study results with previous studies are limited 
owing to a lack of a clear definition of medication errors. Last, 
participation in the study was voluntary, which may have 
influenced the number of medication errors.
FUTURE RESEARCH

Our results suggest a need for improvement in the accuracy 
of medication recording in anesthesia. Our findings provide 
objective evidence for the support of continuous process 
improvement. There is a lack of computer access in patient care 
areas, a lack of real-time decision support, a lack of anesthesia 

providers who adhere to documentation policy, an inefficient 
electronic record conversion process that does not include all 
patient care areas, a lack of a clear documentation process that 
includes a process to detect documentation errors, and a lack of 
counseling after identification of a documentation error. Use of a 
multimodal approach in future interventions is warranted. 
IMPLICATIONS

Errors in medication administration are an ongoing source of 
concern in anesthesia and in health care in general.4 This study 
demonstrates that having computer access at the bedside reduces 
medication errors. No patients sustained increased morbidity or 
died as the result of medication errors during the time frame. The 
implications for practice are focused on patients, anesthesia staff, 
and systems. The first and foremost is improved patient safety 
and outcomes. Reducing medication errors maximizes safe care of 
the patient. Anesthesia providers must be provided with the tools 
needed to provide safe care and to document in real time. Policies 
and laws are in place to protect the patient and anesthesia staff 
from making errors. Increasing compliance in medication errors 
will meet university medical center medication policies and the 
laws of the US Drug Enforcement Agency.
CONCLUSION

Medication errors in the practice of anesthesia have long 
afflicted the specialty. Medication errors may result in patient 
morbidity or mortality and should be preventable. Given the 
adverse effects of medication errors, there is a substantial need 
for evaluation of interventions to reduce errors through process 
improvement. Cause analysis revealed a number of factors that 
contribute to documentation errors. Addressing one factor, 
the lack of computer access in patient care areas, by increasing 
computer access in the post-anesthesia care units did reduce the 
number of medication errors. 
ACKNOWLEDGEMENTS

Many thanks to the faculty of Robert Morris University, 
specifically, Judith Kaufmann, DrPH, FNP-BC. Their guidance 
and support throughout this study was instrumental. In addition, 
thank you to Dr. Daniel Sullivan, Dr. Mark Hudson, Dr. Jacques 
Chelly, and Ms. Janet Lindner for their mentorship and assistance 
throughout. Also, thank you to the anesthesia leadership and staff 
at the University of Pittsburgh Medical Center, Passavant for 
their support. And of course, many thanks to my wife, Katherine, 
daughter, Melissa, and son, Tyler, for their unwavering moral and 
emotional support of my academic pursuits; without them this 
journey would not have been possible.

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Volume 3 Issue 2 2015



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http://www.apsf.org/newsletters/html/2010/spring/01_conference.htm


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Volume 3 Issue 2 2015

Appendix I: Measurement Instrument


