Infusion Medication Error Reduction by Two-Person Verification: A Quality Improvement InitiativeRajeev Subramanyam, MD, MS, Mohamed Mahmoud, MD, David Buck, MD, Anna Varughese, MD, MPH

Departments of Anesthesiology and Pediatrics, Cincinnati

Children’s Hospital Medical Center, University of Cincinnati

College of Medicine, Cincinnati, Ohio

Dr Subramanyam designed the improvement

project, collected and analyzed the data, and

drafted and revised the manuscript; Dr Mahmoud

assisted with improvement ideas in radiology and

revised the manuscript; Dr Buck assisted with

the PDSA cycles and revised the manuscript;

Dr Varughese assisted with designing the project

and improvement ideas and revised the manuscript;

and all authors approved the fi nal manuscript as

submitted.

DOI: 10.1542/peds.2015-4413

Accepted for publication Jun 2, 2016

Address correspondence to Rajeev Subramanyam,

MD, MS, Department of Anesthesia, Cincinnati

Children’s Hospital Medical Center, University of

Cincinnati School of Medicine, 3333 Burnet Ave,

Cincinnati, OH 45229. E-mail: rajeev.subramanyam@

cchmc.org

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online,

1098-4275).

Copyright © 2016 by the American Academy of

Pediatrics

FINANCIAL DISCLOSURE: The authors have

indicated they have no fi nancial relationships

relevant to this article to disclose.

FUNDING: No external funding.

POTENTIAL CONFLICT OF INTEREST: The authors

have indicated they have no potential confl icts of

interest to disclose.

The anesthesia radiology imaging

service at Cincinnati Children’s

Hospital Medical Center (CCHMC)

is a typical brief procedure,

multilocation area. There were 2

infusion pump programming errors

(resulting in no patient harm)

in our radiology imaging service

area related to incorrect entry of

patient weight or drug dosage on

the infusion pump. These errors

were an impetus for this quality

improvement (QI) project. Many

high-risk infusion medications

(eg, propofol, dexmedetomidine)

are used for sedation, and errors

in programming and operation

can be catastrophic. 1 Common

reasons for intravenous medication

infusion errors are incorrectly

programming weight or drug

dosage, programming the wrong

medication, tampering with infusion

pumps by unauthorized users,

and overriding alerts without

recognizing an error.

abstractOBJECTIVE: Errors made in the administration of intravenous medication

can lead to catastrophic harm. The frequency of hospital settings in which

medication pumps are being used are increasing. We sought to improve

medication safety by implementing a 2-person verification system before

medication administration.

METHODS: Our quality improvement initiative took place in an anesthesia

radiology imaging service at a tertiary pediatric hospital. Key drivers

included frequent educational meetings with clinicians, written reminders,

display of visual reminders, constant feedback in the clinical areas that

carried out the processes, and sharing of knowledge on displayed run

charts. A multidisciplinary team conducted a series of tests of changes to

address the interventions. Data were collected and entered into a database

by an independent and impartial data collector. Data were analyzed via run

charts and statistical process control methods.

RESULTS: The team ran 24 plan–do–study–act ramps. The rate of 2-person

verification of infusion pump programming increased from 0% to 90% and

was sustained. Overall, 4 errors were rectified before the medication was

administered to the patient. There was no delay in case starts (>90% before

and during the project). This project played a key role, as part of a larger

initiative within the department of anesthesia, in reducing medication

errors.

CONCLUSIONS: A brief 2-person verification approach can reduce medication

errors due to inaccurate infusion pump programming. This improvement

was achieved with the use of plan–do–study–act cycles. The impact can be

significant and will promote a hospital safety culture.

QUALITY REPORTPEDIATRICS Volume 138 , number 6 , December 2016 :e 20154413

To cite: Subramanyam R, Mahmoud M, Buck D,

et al. Infusion Medication Error Reduction by

Two-Person Verifi cation: A Quality Improvement

Initiative. Pediatrics. 2016;138(6):e20154413

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SUBRAMANYAM et al

More than 56 000 adverse events,

710 deaths, and 87 recalls associated

with the use of infusion devices

alone were reported to US Food and

Drug Administration in the 5-year

span from 2005 to 2009. 2 Children

are at higher risk for medication

errors than adult patients because

of the need for precise weight-

based dosing. Most intravenous

medication errors occur when

drugs are administered that require

multiple-step preparation. 3 Although

technological advances have greatly

improved patient safety through

the use of smart pumps, the risk of

intravenous medication infusion

errors related to programming has

not been eliminated. 4, 5 A variety of

approaches to reduce these errors

have been described1; finding

safe ways to prevent intravenous

medication infusion errors remains a

priority. 6

Two-person verification is a process

in which the work of the first person

is checked independently by another

person. 7 Independent checking is

crucial in reducing any bias that

may occur when the second checker

sees what he or she expects to see,

regardless of any errors. 7 Two-

person verification has successfully

reduced wrong-patient or wrong-

study radiology events in a pediatric

hospital 8 and has been proposed

to reduce medication errors. 9 We

organized a multidisciplinary

taskforce consisting of

anesthesiologists, certified registered

nurse anesthetists (CRNAs), and

radiology registered nurses (RNs)

to reduce these errors. Our overall

objective was for ≥90% of the infusion

pump programming to be verified by

2 people before being administered to

the patient in the anesthesia radiology

imaging division.

METHODS

Ethical Considerations

This project was considered a local QI

project. There was no direct contact

with patients or families, and it was

considered non–human subject

research. Data were obtained from a

data collection form created for this

project and were deidentified. The

data were stored on a password-

protected computer.

Standards for Quality Improvement

Reporting Excellence (SQUIRE)

guidelines were followed in the

preparation of this manuscript. 10

Setting

The project was conducted at

CCHMC, an urban tertiary academic

care center with round-the-clock

anesthesia service availability to

provide anesthesia or sedation for

radiologic imaging (∼5000 cases per

year). The Department of Anesthesia

consists of 60 anesthesiologists,

40 CRNAs, and 29 anesthesia

imaging RNs. The setting for this

study consisted of 4 MRI scanners,

2 computed tomography scanners,

1 nuclear scanner, and 1 auditory

brainstem response testing unit.

The Department of Anesthesia

provides anesthesia for children

undergoing radiologic imaging by

a standardized method. Anesthesia

is induced with sevoflurane in a

mixture of oxygen and nitrous

oxide, and an intravenous line is

placed. An infusion of propofol or

dexmedetomidine is started, based

on the clinical indication, to achieve

motion control.

QI Team

The QI team consisted of 3

anesthesiologists, 2 radiology

imaging nurses, 3 CRNAs, and 1

administrative assistant. More than

half of the team have had previous

formal QI training. A QI consultant

and the hospital QI leaders provided

input during the project.

Planning the Intervention

The QI project was conducted

between August 2014 and February

2015. The impetus for this project

was 2 infusion pump programming

errors (resulting in no patient harm)

that occurred in our hospital before

August 2014.

Data were collected via standardized

questionnaires developed by the

QI team to ascertain whether an

infusion pump was used and whether

an error was found and rectified.

The answers were collected as

binary responses. An independent

administrative assistant who was

blinded to the QI project collected

the data forms and entered them

into the database. No patient-

related health information data

were collected. An “error” occurred

when an infusion pump was used for

that particular patient and an error

with programming was found and

rectified (answered “yes” to both

questions). Pilot data were collected

for a period of 4 weeks in August

2014. Elective, urgent, and emergent

cases were included in the project

if they entailed the use of infusion

medications.

The method used in the project

started with small tests of change or

plan–do–study–act (PDSA) cycles. 11

The QI team initially used 2 QI

methods: first, process mapping

( Fig 1) to lay out the whole process of

administering infusion medications

and, second, failure modes and

effects analysis (FMEA) ( Fig 2) to

identify the failures that occurred in

the process. FMEA helped clarify the

lack of process that could potentially

result in a medication error.

The team identified operational

factors or key drivers and their

associated interventions ( Fig 3)

based on the pilot data and from

the FMEA. The team set a goal

of increasing compliance with

2-person verification from 0% to

90%. A national benchmark was not

available for this goal. Because this

is an important safety issue, we had

the goal to achieve at least level 1

reliability, where there is 80% to

90% success (1 or 2 failures out of

10). 12 The PDSA cycle began with 1

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PEDIATRICS Volume 138 , number 6 , December 2016

imaging location and then spread to

other imaging locations.

Key Drivers and Interventions

Education

In this key driver, education was

targeted to the small percentage

of anesthesiologists and CRNAs

who regularly provided anesthesia

for radiologic imaging. The first

step to make this process work

was to provide education about

the importance of a safety check

to reduce patient medication

errors. Education about the use of

standardized pump programming

was provided to stakeholders

with a job aid (anesthesiologists,

CRNAs, RNs), and education

about anesthesia medications was

provided to RNs. The specific roles

of each person were clarified. A

data form was created, and the RN

who was involved in caring for the

patient completed the data form.

One challenge during this process

was resistance to a culture change

from old processes to the 2-person

verification process. This challenge

was discussed at departmental

meetings.

Visual Aids

The first visual aid was a sticker,

which was to be signed by 2 people to

confirm that the 2-person verification

was completed. Although considered

a significant advance, this process

met with a lot of resistance from the

staff because of space constraints in

the anesthesia workspace. Therefore,

this sticker was abandoned.

The second visual aid was developed

midway through the improvement

project, and acted as a reminder.

The visual reminder was placed in

locations where failures most often

occurred to remind the clinical staff

to complete the 2-person verification.

Stakeholder Buy-In

The initial resistance to culture

change was converted successfully

with buy-in from stakeholders.

The key driver diagram and the

weekly updated run charts were

continuously displayed in the work

area to achieve support, provide a

constant reminder of the project,

and share knowledge. Constant

reminders and a presentation of

the process during the monthly QI

meeting were also performed. During

the QI project, 4 programming errors

were detected and were rectified

before they could affect the patient.

These instances of error rectification

were a major impetus for stakeholder

buy-in.

e3

FIGURE 1Process mapping showing the process of programming the infusion pump from the start to the end. The 2-person verifi cation is incorporated in the red circle. RN, registered nurse.

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SUBRAMANYAM et al

Modifi cations to Electronic Medical Records and Procedural Timeout

The electronic medical record (EMR)

was modified to accurately document

2-person verification of the infusion

pump programming. The procedural

timeout is a routine check performed

before the procedure and start of

anesthesia or sedation. 13 The QI team

representatives worked to locally

add the 2-person verification process

for infusion pump programming to

the procedural timeout to ensure

sustainability.

Performance of the Verifi cation Process

The first person to perform the

verification process (anesthesiologist

or CRNA) fully programmed the

pump. Subsequently, the second

person (another anesthesiologist

or CRNA, RN) walked through

each step in the infusion pump

programming and cross-verified

the drug, with particular emphasis

placed on patient weight and drug

dosage programming. These steps

were taken before the medication

was administered to the patient and

before procedural timeout.

Study of Interventions

The QI team assessed how well the

interventions were implemented

and their impact on the goal after

the completion of the project. The

data collection was continued after

completion of the project to ensure

sustainability. After changes in the

EMR documentation process and

the procedural timeout, impact on

the radiology anesthesia service was

assessed. On a monthly basis, the

QI team reviewed the reports, and

the information was conveyed to

perioperative staff through regular

meetings and poster boards.

Methods of Evaluation and Analysis

The primary (process) measure

was the proportion of 2-person

verification of infusion pump

programming (goal ≥90%). The

secondary outcome measure was

the reduction in medication errors

related to administration of infusion

pump medications (goal = 0%).

Balancing measure refers to no

delays in first case starts in radiology

e4

FIGURE 2Failure mode and effects analysis.

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PEDIATRICS Volume 138 , number 6 , December 2016

(goal >90%). Case start was defined

as the time at which the anesthetic or

sedative medication administration

was started. In addition, a cross-

sectional analysis was done via

Survey Monkey to assess delays in

case starts.

The number of data forms available

each day was cross-verified with

the number of cases where infusion

medication was used that day by 1

of the 4 independent patient flow

coordinator RNs to ensure that no

data were overlooked. The number

of cases conducted per week was

monitored to ensure that the data

captured were representative of

the sample population. The process

measure directly collected the data

for the outcome measure (eg, if the

nurse completed the double-check

form, that form was used to check

whether the first person made an

infusion pump medication “potential”

error).

Data obtained were analyzed each

week in terms of proportions. The

primary and secondary outcomes

were represented with statistical

control charts and presented to the

QI team on a monthly basis. Median

was applied to assess the statistical

process control. These charts helped

display and analyze any variations

in the time series data. Special cause

variation was used to evaluate the

effectiveness of interventions. Special

cause variation was considered

to be present based on a shift (≥8

consecutive points), a trend (6

consecutive points), or alternating

points (14 consecutive data points). 14

Any special cause variation was

investigated to learn about the

reason for the change, and the charts

were annotated. The process was

regarded as having a change, and a

new baseline was created when the

special cause coincided temporally

with a plausible explanation.

RESULTS

A total of 24 PDSA ramps were

tested. The baseline data are shown

for 4 weeks. In the first few months

of testing the key interventions,

the run chart showed special cause

variations, specifically 8 consecutive

points above the centerline ( Fig 4).

The centerline remained consistently

above the goal of 90% during the rest

of the time period. The stakeholder

buy-in was remarkable, and there

was minimal variation with the

process. The 2-person verification

process was incorporated during the

procedural timeout during the time

annotated in the run chart ( Fig 3).

Fifteen months after the project

started, the centerline was still above

e5

FIGURE 3Key driver diagram for the improvement project presenting the overall project aim, key drivers, and interventions (ideas for change).

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SUBRAMANYAM et al

the goal, with minimal variation.

The EMR was modified to record

the 2-person verification. Given the

success, we were able to scale the

process to other anesthesia locations

of the hospital. The stakeholders

were eager to emulate this process in

other areas.

During the initial period of the

project, 4 programming errors

were identified and rectified before

medication administration ( Fig 5).

Two errors were due to incorrect

dosage or weight programming,

and the other 2 resulted from

programming the incorrect infusion

pump module. The “no delay in case

starts” rate was >90% before project

start, during the project, and after

project completion. In the cross-

sectional analysis performed via

Survey Monkey, 95% of stakeholders

indicated there was no delay in case

starts.

DISCUSSION

A standardized, team-based approach

to reduce the number of intravenous

medication infusion administration

errors in a high-turnover area

of the hospital where anesthesia

and sedation are administered

is described. Implementation of

2-person verification resulted in

>90% medication programming

being double-checked before

medication administration. This

change was sustained through human

factor–dependent processes, such as

reminders and procedural timeouts,

and human factor–independent

processes with inclusion in the

EMR. This standardized patient-

centered approach decreased the

number of medication errors by

early identification of programming

errors. This project played a key role,

as part of a larger initiative in the

department of anesthesia, to reduce

medication errors. Over the course

of 2 years, this initiative decreased

e6

FIGURE 4Run chart showing overall compliance with 2-person verifi cation. The solid red line represents the average number of infusion pumps that are 2-person verifi ed as a percentage of the number of infusion pump medications used per week. Special cause is shown by 2 shifts of the centerline based on 8 consecutive points above the centerline. The yellow boxes represent PDSA interventions at specifi c time intervals. (PDSA 1, job aids; PDSA 2, run chart display; PDSA 3, stickers; PDSA 4, written reminders; PDSA 5, presentation; and PDSA 6, changes to EMR.)

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PEDIATRICS Volume 138 , number 6 , December 2016

medication errors from a rate of

4 errors per month to 1 error per

month.

The US Pharmacopeia Medication

Errors Reporting Program showed

a significantly higher rate of

medication error resulting in

harm or death of 31% in pediatric

patients as compared with 13% in

adult patients. 15 The occurrence

of potential adverse drug events

(those not causing harm) is also 3

times higher in pediatric patients

as compared with adult patients. 16

Intravenous fluids are the most

common product implicated in

pediatric medication errors. 15 Errors

with high-hazard drugs can be

catastrophic. Although the infusion

pumps used to administer pediatric

medications are “smart pumps, ” they

are not completely error-free because

of their dependence on human

factors. 4 In our project, we found that

although there were hard limits in

the infusion pump drug library, there

were also soft limits that allowed

high override rates. Therefore, a

continuous QI process was important

to improve their safe use.4 An

infusion pump informatics analytics

system can be used to design a

smart pump drug library. 17 For a

system transitioning from a paper

ordering system to a computer-based

ordering, it is important to know

that this transition can introduce

new types of medication errors, and

the system should be designed to

recognize such errors. 18 Integration

of barcodes on a smart infusion

pumps and creation of closed-loop

systems will also reduce intravenous

medication infusion errors.

Two-person verification is used

by high-reliability organizations

such as the nuclear industry, the

US Department of Defense, and

the airline industry. In health care,

2-person verification has been used

for a long time with blood component

transfusion and is mandated by the

Joint Commission to achieve patient

safety. In the radiology imaging

service, this 2-person verification

was deemed a value-based approach

because 2 anesthesia personnel

or 1 anesthesia staff person and

an imaging nurse care for every

patient. Because infusion pump

errors related to programming and

operation are common, 1 we deemed

2-person verification a reasonable

approach to ensure patient safety,

akin to reducing clerical errors with

transfusion.

e7

FIGURE 5Run chart showing the rate of medication errors detected and verifi ed before reaching the patient during the project. The solid red line represents the number of infusion pump programming errors as a percentage of the number of infusion pump medications used per week. The median does not exist for these data.

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SUBRAMANYAM et al

Although this project is done in the

setting of an anesthesia radiology

imaging service, the implications

of the project relate to all areas of a

hospital where infusion medications

are used. With the increasing use

of sedatives and other infusion

medications across the hospital,

reducing medication errors related

to infusion pump programming

is critical. The sustainability of

2-person verification was reviewed

and analyzed on a weekly basis. 19

The culture of change has been

sustained to date by incorporating

the process into the procedural

timeout. Procedural timeout is a

checklist created by World Health

Organization to address surgical and

procedural safety. 13 The checklist

helps with effective communication

and teamwork and helps health

care teams remember critical

information about the patient before

administering anesthesia. 20 The use

of a checklist is imperative for patient

safety, and the radiology anesthesia

service at CCHMC is 100% compliant

with the use of this surgical checklist.

Checklist compliance is monitored

by a radiology anesthesia nurse and

is overseen by the nursing clinical

director of radiology anesthesia

imaging. Therefore, incorporating

the 2-person verification as part of

the procedural timeout checklist also

enabled new staff to comply with the

verification process.

One limitation of this QI work is that

a few PDSA cycles were introduced

in a period of 6 months; it is hard

to discern which of those had the

highest impact. Different aspects of

our approach, including constant

communication and the display of

the outcome measure run chart

with reduction in medication errors,

had the greatest impact, given the

interaction with stakeholders.

Another limitation is the

nonavailability of QI infrastructure

at hospitals trying to replicate the QI

method.

CONCLUSIONS

Our QI project was successful in

implementing a 2-person verification

process to enable safe medication

administration by identifying a set of

key drivers and testing interventions.

Analysis-driven modifications to

the 2-person verification process

and reduction of medication errors,

which was refined via a model for

improvement, led to a safe culture

for intravenous medication infusion

administration at a large tertiary

children’s hospital. Education,

constant communication, impact

demonstration, and sustainability

were critical to the QI effort.

Pediatricians can follow this

method to acquire competence in

QI 21 and to apply this competence

in their own practices. The safety

impact is generalizable and can be

implemented in any busy location

of the hospital where critical

intravenous medication infusion is

used for emergency, urgent care,

or routine elective procedures. We

suggest that as a part of continuous

QI, health care facilities develop a

local policy to maintain and address

medication errors.

ACKNOWLEDGMENTS

We thank all the members of the QI

team: Lois Curtwright (radiology

anesthesia imaging, nursing clinical

director), John Holcomb, Kelly

Buczak, anesthesiologists, CRNAs,

radiology imaging nurses, and

radiology technicians.

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ABBREVIATIONS

CCHMC:  Cincinnati Children’s

Hospital Medical Center

CRNA:  certified registered nurse

anesthetist

EMR:  electronic medical record

FMEA:  failure modes and effects

analysis

PDSA:  plan–do–study–act

QI:  quality improvement

RN:  registered nurse

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PEDIATRICS Volume 138 , number 6 , December 2016

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originally published online November 9, 2016; Pediatrics Rajeev Subramanyam, Mohamed Mahmoud, David Buck and Anna Varughese

Improvement InitiativeInfusion Medication Error Reduction by Two-Person Verification: A Quality

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originally published online November 9, 2016; Pediatrics Rajeev Subramanyam, Mohamed Mahmoud, David Buck and Anna Varughese

Improvement InitiativeInfusion Medication Error Reduction by Two-Person Verification: A Quality

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