Chapter 37. Medication Administration Safety

Ronda G. Hughes, Mary A. Blegen 

Background

The Institute of Medicine’s (IOM) first Quality Chasm report, To Err Is Human: Building a 

Safer Health System,

1

 stated that medication-related errors (a subset of medical error) were a 

significant cause of morbidity and mortality; they accounted “for one out of every 131 outpatient 

deaths, and one out of 854 inpatient deaths”1 (p. 27). Medication errors were estimated to 

account for more than 7,000 deaths annually.1 Building on this work and previous IOM reports, 

the IOM put forth a report in 2007 on medication safety, Preventing Medication Errors.

2

 This 

report emphasized the importance of severely reducing medication errors, improving 

communication with patients, continually monitoring for errors, providing clinicians with 

decision-support and information tools, and improving and standardizing medication labeling 

and drug-related information. 

With the growing reliance on medication therapy as the primary intervention for most 

illnesses, patients receiving medication interventions are exposed to potential harm as well as 

benefits. Benefits are effective management of the illness/disease, slowed progression of the 

disease, and improved patient outcomes with few if any errors. Harm from medications can arise 

from unintended consequences as well as medication error (wrong medication, wrong time, 

wrong dose, etc.). With inadequate nursing education about patient safety and quality, excessive 

workloads, staffing inadequacies, fatigue, illegible provider handwriting, flawed dispensing 

systems, and problems with the labeling of drugs, nurses are continually challenged to ensure 

that their patients receive the right medication at the right time. The purpose of this chapter is to 

review the research regarding medication safety in relation to nursing care. We will show that 

while we have an adequate and consistent knowledge base of medication error reporting and 

distribution across phases of the medication process, the knowledge base to inform interventions 

is very weak. 

Defining Medication Errors

Shared definitions of several key terms are important to understanding this chapter. Drugs are 

defined as “a substance intended for use in the diagnosis, cure, mitigation, treatment or 

prevention of disease; a substance (other than food) intended to affect the structure or any 

function of the body; and a substance intended for use as a component of a medicine but not a 

device or a component, part or accessory of a device.”3 Medications include, but are not limited 

to, any product considered a drug by the Food and Drug Administration (FDA).3

 Given the 

number and variety of definitions for medication errors, the IOM has recommended that 

international definitions be adopted for medication error, adverse drug events, and near misses.2

1 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

Medication Errors 

One commonly used definition for a medication error is: 

Any preventable event that may cause or lead to inappropriate medication use or 

patient harm while the medication is in the control of the health care professional, 

patient, or consumer. Such events may be related to professional practice, health 

care products, procedures, and systems, including prescribing; order 

communication; product labeling, packaging, and nomenclature; compounding; 

dispensing; distribution; administration; education; monitoring; and use.4 

Some of the factors associated with medication errors include the following: 

• Medications with similar names or similar packaging 

• Medications that are not commonly used or prescribed 

• Commonly used medications to which many patients are allergic (e.g., antibiotics, 

opiates, and nonsteroidal anti-inflammatory drugs) 

• Medications that require testing to ensure proper (i.e., nontoxic) therapeutic levels are 

maintained (e.g., lithium, warfarin, theophylline, and digoxin) 

Look-alike/sound-alike medication names can result in medication errors. Misreading 

medication names that look similar is a common mistake. These look-alike medication names 

may also sound alike and can lead to errors associated with verbal prescriptions. The Joint 

Commission publishes a list of look-alike/sound-alike drugs that are considered the most 

problematic medication names across settings. (This list is available at www.jointcommission. 

org/NR/rdonlyres/C92AAB3F-A9BD-431C-8628-11DD2D1D53CC/0/lasa.pdf.) 

Medication errors occur in all settings5

 and may or may not cause an adverse drug event 

(ADE). Medications with complex dosing regimens and those given in specialty areas (e.g., 

intensive care units, emergency departments, and diagnostic and interventional areas) are 

associated with increased risk of ADEs.6 Phillips and colleagues7 found that deaths (the most 

severe ADE) associated with medication errors involved central nervous system agents, 

antineoplastics, and cardiovascular drugs. Most of the common types of errors resulting in 

patient death involved the wrong dose (40.9 percent), the wrong drug (16 percent), and the 

wrong route of administration (9.5 percent). The causes of these deaths were categorized as oral 

and written miscommunication, name confusion (e.g., names that look or sound alike), similar or 

misleading container labeling, performance or knowledge deficits, and inappropriate packaging 

or device design. 

Adverse Drug Events and Adverse Drug Reactions 

Adverse drug events are defined as injuries that result from medication use, although the 

causality of this relationship may not be proven.8 Some ADEs are caused by preventable errors. 

ADEs that are not preventable are often the result of adverse drug reactions (ADRs), which are 

defined as “any response to a drug which is noxious and unintended and which occurs at doses 

normally used for prophylaxis, diagnosis or therapy of disease, or the modification of 

physiological function, given that this noxious response is not due to medication error.”9

Potential ADEs or near misses/close calls are medication errors that do not cause any harm to the 

patient because they are intercepted before they reach the patient or because the patient is able to 

physiologically absorb the error without any harm. 

2 
Medication Administration Safety

An adverse drug reaction is defined as “an undesirable response associated with use of a drug 

that either compromises therapeutic efficacy, enhances toxicity, or both.”10 ADRs can be 

manifested as diarrhea or constipation, rash, headache, or other nonspecific symptoms. One of 

the challenges presented by ADRs is that prescribers may attribute the adverse effects to the 

patient’s underlying condition and fail to recognize the patient’s age or number of medications as 

a contributing factor.11 According to Bates and colleagues,12 more attention needs to be directed 

to ADEs—including both ADRs and preventable ADEs—which range in severity from 

insignificant to fatal. 

Black Box Warnings and High-Alert Medications 

In 1995, the FDA established the black box warning (BBW) system to alert prescribers to 

drugs with increased risks for patients. These warnings are intended to be the strongest labeling 

requirement for drugs or drug products that can have serious adverse reactions or potential safety 

hazards, especially those that may result in death or serious injury.13 While the FDA does not 

issue a comprehensive list of drugs with BBWs,14 some of the BBW drugs are celecoxib 

(Celebrex), warfarin, rosiglitazone (Avandia), methylphenidate (Ritalin), estrogen-containing 

contraceptives, and most antidepressants.15 One study funded by the Agency for Healthcare 

Research and Quality found 40 percent of patients were taking a medication with a BBW and 

that many of those patients did not receive the recommended laboratory monitoring. The authors 

concluded that BBWs did not prevent the inappropriate use of high-risk medications.16

Medication errors can be considered a sentinel event when they are associated with high-alert 

medications. According to the Institute for Safe Medication Practices (ISMP), “High-alert 

medications are those likely to cause significant harm when used in error.” The top five highalert medications are “insulin, opiates and narcotics, injectable potassium chloride (or phosphate) 

concentrate, intravenous anticoagulants (heparin), and sodium chloride solutions above 0.9 

percent”17 (p. 339). ISMP’s list of high-alert medications is available at: www.ismp.org/tools/ 

highalertmedications.pdf. 

The Prevalence and Impact of Medication Errors 

In the Harvard Medical Practice Study, Leape and colleagues18, 19 examined more than 

30,000 hospital discharges selected at random from 51 hospitals in the State of New York in 

1984. The researchers found that 3.7 percent of hospitalizations involved adverse events that 

prolonged hospital stay or were manifested as a new disability at the time of discharge. About 

one in four of these adverse events were judged to be attributable to negligence, and 58 percent 

were judged to be preventable. 

It is difficult to reduce or eliminate medication errors when information on their prevalence is 

absent, inaccurate, or contradictory. Bates20 put forth the notion that for every medication error 

that harms a patient, there are 100, mostly undetected, errors that do not. Most medication errors 

cause no patient harm or remain undetected by the clinician.20, 21 The low rate of detected errors 

makes assessing the effectiveness of strategies to prevent medication errors challenging. 

Rates of medication errors vary, depending on the detection method used. For example, 

among hospitalized patients, studies have shown that errors may be occurring as frequently as 

one per patient per day.5, 22 In pediatric intensive care unit (ICU) studies, reported medication 

error rates have ranged from 5.723 and 14.6 per 100 orders24 to as high as 26 per 100 orders.25 

3 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

The impact of medication errors on morbidity and mortality were assessed in a case-control 

analysis of ADEs in hospitalized patients during a 3-year period.26 The investigators found 

significant increases in (a) the cost of hospitalization from increased length of stay, ranging from 

$677 to $9,022; (b) patient mortality (odds ratio = 1.88 with a 95% confidence interval); and (c) 

postdischarge disability. The impact was less in male patients, younger patients, and patients 

with less severe illnesses and in certain diagnosis-related groups. 

Without an infrastructure to capture and assess all medication errors and near misses, the real 

number is not known. These rates could be expected to be higher once patient safety 

organizations begin to collect nationwide errors and health care clinicians become more 

comfortable and skilled in recognizing and reporting all medication errors. The concern raised in 

To Err Is Human1

 about the potential prevalence and impact of ADEs—2 out of every 100 

hospitalized patients—was just the beginning of our understanding of the potential magnitude of 

the rates of medication errors. The concern continues, as is seen in the most recent IOM report, 

Preventing Medication Errors,2

 which states that “a hospital patient is subject to at least one 

medication error per day, with considerable variation in error rates across facilities” (pp. 1–2). 

Yet, despite numerous research findings, we cannot estimate the actual rates because they vary 

by site, organization, and clinician; because not all medication errors are detected; and because 

not all detected errors are reported. 

Error-Prone Processes 

There are five stages of the medication process: (a) ordering/prescribing, (b) transcribing and 

verifying, (c) dispensing and delivering, (d) administering, and (e) monitoring and reporting.2

Monitoring and reporting is a newly identified stage about which there is little research. Some of 

the most noted and early work on medication safety found hospitalized patients suffer 

preventable injury or even death as a result of ADEs associated with errors made during the 

prescribing, dispensing, and administering of medications to patients,12, 27–29 although the rates of 

error in the stages of the medication process vary. A few studies have indicated that one of every 

three medication errors could be attributed to either a lack of knowledge about the medication or 

a lack of knowledge about the patient.30

Prescribing/ordering. Of the five stages, ordering/prescribing most often initiates a series of 

errors resulting in a patient receiving the wrong dose or wrong medication. In this stage, the 

wrong drug, dose, or route can be ordered, as can drugs to which the patient has known allergies. 

Workload, knowledge about the prescribed drug, and attitude of the prescriber—especially if 

there is a low perceived importance of prescribing compared with other responsibilities—are 

significantly associated with ADEs.31, 32 Furthermore, if nurses or pharmacists question a 

prescriber about an order, they can be confronted with aggressive behavior, which may inhibit 

future questioning and seeking clarification.33 The proportion of medication errors attributable to 

the ordering/prescribing stage range from 79 percent29 to 3 percent.34 Examples of the types of 

errors committed in this stage include illegible and/or incomplete orders, orders for 

contraindicated medications, and inappropriate doses. Similar results have been found in 

mandatory adverse event reporting systems. An analysis of 108 reports associated with 

significant harm or death reported to the State of New York noted that, when the error occurred 

during the prescribing stage, written prescriptions accounted for 74 percent of the errors, and 

verbal orders accounted for 15 percent.6

 

While the preponderance of the research focuses on physician prescribing, there is a brief 

discussion about the role of advanced practice nurses in prescribing to ensure safety. One 

4 
Medication Administration Safety

investigation of the occurrence of ADRs in outpatient veterans found no difference in ADR 

events between physicians and nurse practitioners.11 Prescribers may make changes in 

medication therapy (e.g., change the dosage or discontinue the medication) in response to ADRs 

(e.g., constipation, rash) or other indications communicated to them by nurses or patients. 

Transcribing, dispensing, and delivering. In some settings, medication orders are 

transcribed, dispensed, and then delivered for nurse administration. In certain circumstances and 

settings, both nurses and pharmacists are involved in transcribing, verifying, dispensing, and 

delivering medications. Yet errors of these two stages (transcribing and verifying, dispensing and 

delivering) have been predominately studied for pharmacists. Pharmacists can have an important 

role in intercepting and preventing prescribing/ordering errors.35 One study found that while 

dispensing errors were 14 percent of the total ADEs, pharmacists intercepted 70 percent of all 

physician ordering errors.27 Pharmacy dispensing errors have been found to range from 4 percent 

to 42 percent of errors.36 Examples of errors that can be initiated at the transcribing, dispensing, 

and delivering stages include failure to transcribe the order, incorrectly filling the order, and 

failure to deliver the correct medication for the correct patient. 

Medication administration. Nurses are primarily involved in the administration of 

medications across settings. Nurses can also be involved in both the dispensing and preparation 

of medications (in a similar role to pharmacists), such as crushing pills and drawing up a 

measured amount for injections. Early research on medication administration errors (MAEs) 

reported an error rate of 60 percent,34 mainly in the form of wrong time, wrong rate, or wrong 

dose. In other studies, approximately one out of every three ADEs were attributable to nurses 

administering medications to patients.21, 28 In a study of deaths caused by medication errors 

reported to the FDA from 1993 to 1998, injectable drugs were most often the problem;7

 the most 

common type of error was a drug overdose, and the second most common type of error was 

administering the wrong drug to a patient. The 583 causes of the 469 deaths were categorized as 

miscommunication, name confusion, similar or misleading labeling, human factors (e.g., 

knowledge or performance deficits), and inappropriate packaging or device design. The most 

common causes were human factors (65.2 percent), followed by miscommunication (15.8 

percent). 

Nurses are not the only ones to administer medications. Physicians, certified medication 

technicians, and patients and family members also administer medications. Part of the challenge 

in understanding the impact of nursing in medication administration is the need for research that 

clearly differentiates the administrators of medications. Several studies have reported medication 

administration errors that have included nonnurses.37, 38 Among many reasons for the prevalence 

of nurse involvement in medication errors is that nurses may spend as much as 40 percent of 

their time in medication administration.39 

A large-scale study by the U.S. National Council of State Boards of Nursing assessed 

whether there were any identifiable characteristics common to those nurses who committed 

medication administration errors. The most significant finding was that “the age, educational 

preparation and employment setting of RNs disciplined for medication administration errors are 

similar to those of the entire RN population”40 (p. 12). 

The “rights” of medication administration include right patient, right drug, right time, right 

route, and right dose. These rights are critical for nurses. A survey of patients discharged from 

the hospital found that about 20 percent were concerned about an error with their medications, 

and 15 percent of them were concerned about being harmed from mistakes by nurses compared 

to 10 percent who were concerned about mistakes by physicians.41 However, the complexity of 

5 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

the medication process has led to the formulation of the rights of nurses in the area of medication 

administration. The essential environmental conditions conducive to safe medication practices 

include (a) the right to complete and clearly written orders that clearly specify the drug, dose, 

route, and frequency; (b) the right to have the correct drug route and dose dispensed from 

pharmacies; (c) the right to have access to drug information; (d) the right to have policies on safe 

medication administration; (e) the right to administer medications safely and to identify problems 

in the system; and (f) the right to stop, think, and be vigilant when administering medications.42

Types of Medication Errors 

Leape and colleagues27 reported more than 15 types of medication errors: wrong dose, wrong 

choice, wrong drug, known allergy, missed dose, wrong time, wrong frequency, wrong 

technique, drug-drug interaction, wrong route, extra dose, failure to act on test, equipment 

failure, inadequate monitoring, preparation error, and other. Of the 130 errors for physicians, the 

majority were wrong dose, wrong choice of drug, and known allergy. Among the 126 nursing 

administration errors, the majority were associated with wrong dose, wrong technique, and 

wrong drug. Each type of error was found to occur at various stages, though some more often 

during the ordering and administration stages. 

Since the study by Leape and colleagues, research has captured some of the types of error 

identified by Leape and added yet others (e.g., omission due to late transcription,43 wrong 

administration technique,24, 44, 45 and infiltration/extravasation.46 Reporting incidences by type of 

error, rather than the stage it was associated with, leads to equivocal implications for nursing 

practice. The categorization approach used determines whether the implication can be targeted to 

stage, and therefore discipline, or to types of error. For example, 11 studies reported rates of 

types of medication errors using institution-specific and national databases, yet not specifying 

whether the error occurred during the prescribing, dispensing, or administration stage of the 

medication process or not clearly specifying administration errors associated with nurse 

administration. One of these studies analyzed deaths associated with medication errors, finding 

that the majority of deaths were related to overdose and wrong drug7

—again, not specified by 

stage. Yet among these, it may be possible to see that wrong dose, dose omission, wrong drug, 

and wrong time are the most frequent type of medication error. Even then, comparisons and 

practice implications are challenging due to the lack of standardization among the types of 

categories used in research. 

Working Conditions Can Facilitate Medication Errors 

Following the release of To Err Is Human,

1

 the focus on deaths caused by medication errors 

targeted system issues, such as high noise levels and excessive workloads,47 and system 

interventions, such as the need for computerized order entry, unit dose (e.g., single-dose 

packaging), and 24-hour pharmacy coverage.48 The IOM’s report, Crossing the Quality Chasm,

49

put forth the concept that poor designs set the workforce up to fail, regardless of how hard they 

try. Thus, if health care institutions want to ensure safer, higher-quality care, they will need to, 

among other things, redesign systems of care using information technology to support clinical 

and administrative processes. 

We are at the beginning stage of assessing and understanding the potential association 

between working conditions/environment and medication errors. Early research in this area 

found a relationship between characteristics of the work environment for nurses and medication 

6 
Medication Administration Safety

errors.30, 50, 51 For example, Leape and colleagues27 found an association between the occurrence 

of medication errors and the inability to access information and failure to follow policies and 

guidelines. Also, research has found that health care clinicians should be aware of the repeated 

patterns of medication errors and near misses to provide insight on how to avoid future errors.52

The system approach to safety emphasizes the human condition of fallibility and anticipates 

that errors will occur, even in the best organizations with the best people working in them. This 

approach focuses on identifying predisposing factors within the working environment or systems 

that lead to errors.53 Reason’s53 model of accident causation describes three conditions that 

predicate an error: 

1. Latent conditions—Organizational processes, management decisions, and elements in the 

system, such as staffing shortages, turnover, and medication administration protocols. 

2. Error-producing conditions—Environmental, team, individual, or task factors that affect 

performance, such as distractions and interruptions (e.g., delivering and receiving food 

trays), transporting patients, and performing ancillary services (e.g., delivery of medical 

supplies, blood products).49

3. Active failures—errors involving slips (actions in which there are recognition or selection 

failures), lapses (failure of memory or attention), and mistakes (incorrect choice of 

objective, or choice of an incorrect path to achieve it), compared to violation, where rules 

of correct behavior are consciously ignored. 

Threats to medication safety include miscommunication among health care providers, drug 

information that is not accessible or up to date, confusing directions, poor technique, inadequate 

patient information, lack of drug knowledge, incomplete patient medication history, lack of 

redundant safety checks, lack of evidence-based protocols, and staff assuming roles for which 

they are not prepared. An additional risk is a hospital without 24-hour pharmacy coverage, 

especially when procedural barriers to offset the risk of accessing high-risk drugs are absent.6

Recognizing and Reporting Medication Administration Errors 

Error reporting strategies are critical to the implementation of effective system-level 

approaches to reduce medication errors and ADEs.54 However, the usefulness of many reporting 

strategies depends directly on the level of response.55 To be effective, medication error reporting 

needs to be ongoing and part of a continuous quality improvement process.56, 57

Previous research has found that when nurses voluntarily report medication administration 

errors, as few as 10 to 25 percent of errors are reported.28 As discussed in the chapter on error 

reporting, there were numerous surveys of hospital nurses’ perceptions of what constitutes an 

MAE, why these types of errors occur,58–61 and what the barriers to reporting are.58–72 The three 

most significant barriers to reporting were (a) a hierarchical hospital culture/structure where the 

nursing staff disagreed about the definition of reportable errors, (b) fear of the response and 

reaction of hospital management/administrators and peers to a reported error, and (c) the amount 

of time and effort involved in documenting and reporting an error. Together these studies 

indicate that the medication errors that are reported do not represent the actual incidence of 

medication errors. 

Without reporting, many errors may not be known. Based on a survey of nurses on barriers to 

reporting, Wakefield and colleagues62 suggested several strategies to increase the reporting of 

MAEs: agreement on the definition of error; supporting and simplifying reporting of errors; 

institutionalizing a culture that rewards and learns from error reporting (i.e., a culture of safety, 

where learning is encouraged and blaming discouraged); capitalizing on feedback reports to 

7 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

determine system factors contributing to error; and ensuring positive incentives for MAE 

reporting. 

Incident reports, retrospective chart reviews, and direct observation are methods that have 

been used to detect errors. Incident reports, which capture information on recognized errors, can 

vary by type of unit and management activities;73 they represent only a few of the actual 

medication errors, particularly when compared to a patient record review.74 Chart reviews have 

been found to be most useful in detecting errors in ordering/prescribing, but not 

administration.75, 76 Direct observation of administration with comparison to the medication 

administration record detects most administration errors; however, it cannot detect ordering 

errors and, in some systems, transcribing and dispensing errors. There were two studies that 

compared detection methods. One of these studies of medication administration in 36 hospitals 

and skilled nursing facilities found 373 errors made on 2,556 doses.77 The comparison of three 

detection methods found that chart review detected 7 percent of the observed errors, and incident 

reports detected only 1 percent. Direct observation was able to detect 80 percent of true 

administration errors, far more than detected through other means. A second study compared 

detection methods and found that more administration errors were detected by observation (a 

31.1 percent error rate) than were documented in the patients’ medical records (a 23.5 percent 

error rate).78 Therefore, no one method will do it all. When automated systems that use triggers 

are not in place, multiple approaches such as incident reports, observation, patient record 

reviews, and surveillance by pharmacist may be more successful.79

The wide variation in reported prevalence and etiology of medication errors is in part 

attributable to the lack of a national reporting system or systems that collect both errors and near 

misses. State-based and nationally focused efforts to better determine the incidence of 

medication errors are also available and expanding (Patient Safety and Quality Improvement Act 

of 2005). The FDA’s Adverse Event Reporting System (AERS), which is part of the FDAs’ 

MedWatch program (www.fda.gov/medwatch), U.S. Pharmacopeia’s (USP’s) MEDMARX®

database (www.medmarx.com), and the USP’s Medication Errors Reporting Program (MERP; 

www.ismp.org/orderforms/reporterrortoISMP.asp), in cooperation with the ISMP, collect 

voluntary reports on actual and potential medication errors, analyze the information, and publish 

information on their findings. 

Research reported to date clearly reveals that medication errors are a major threat to patient 

safety, and that these errors can be attributed to all involved disciplines and to all stages of the 

medication process. Unfortunately, the research also reveals that we have only weak knowledge 

of the actual incidence of errors. Our information about ADEs (those detected, reported, and 

treated) is better, but far from complete. With this knowledge of the strengths and limitations of 

the research, this chapter will consider the evidence regarding nurses’ medication administration. 

Research Evidence—Medication Administration by Nurses 

The research review targeted studies involving medication administration by nurses. This 

excluded several studies that assessed medication administration errors without differentiating 

whether the errors were associated with physicians, assistants, or nurses. None of these studies 

included interventions. 

8 
Medication Administration Safety

Rates and Types of Medication Administration Errors 

Thirteen studies explicitly reported types of MAEs associated with nurses. The incidence of 

MAEs was detected either formally through incident reports, chart reviews, or direct observation, 

or informally through anonymous surveys. Two studies conducted retrospective assessments, one 

using medical records43 and the other malpractice claims.80 Seven studies assessed self-reported 

MAEs from a nationally representative database44, 81–83 or self-reported errors using a nationally 

representative sample.84–86 None of these self-reported MAEs were verified. Eight studies 

assessed MAEs using direct observation of the medication administration process.24, 37, 78, 87–91 

The incidence of MAEs varied widely with the different research designs and samples. Using 

chart reviews, Grasso and colleagues43 found that 4.7 percent of doses were administered 

incorrectly. Direct observation studies placed the estimate of total incorrect doses between 19 

percent and 27 percent,87 and when an extra review was done to separate the errors into stages of 

the medication process, between 6 percent and 8 percent of doses were in error because of 

administration. The majority of types of MAEs reported were wrong dose, wrong rate, wrong 

time, and omission. All of the studies reviewed here reported wrong drug and dose, but varied 

across the other types of MAE categories (see Evidence Table 1); this was dependent upon the 

study methodology. 

Five studies evaluated self-reported MAEs, involving incident reports and informal reports.38, 

44, 81, 82 The most common types of reported errors were wrong dose, omission, and wrong time. 

Four of these studies38, 81–83 assessed a large secondary, nationally representative database 

containing MAEs reported to the MEDMARX database over five years.38, 81, 82, 44 found in the 

error reports submitted by nursing students that the majority of MAEs were associated with 

omission, wrong dose, wrong time, and extra dose. Of the reported contributing factors, 78 

percent were due to the inexperience of the nurse. The Beyea and Hicks81, 82 studies looked at 

errors associated with the operating room, same-day surgery, and postanesthesia; they found the 

majority of errors attributable to administration but did not classify them by error type. The other 

study reviewed 88 incident reports from a long-term care facility submitted during a 21-month 

period. It found that the majority of MAEs were associated with errors involving interpreting or 

updating the medication administration record, delayed dose, wrong dose, or wrong drug.92 A 

separate component of this study surveyed administrative and clinical nurses and found that they 

believed the majority of medication errors occurred at either the administration or dispensing 

stage. 

Two other studies assessed the type of MAEs reported by nurses in nationwide surveys.84, 85

While the majority (57 percent) of errors reported by critical care nurses involved MAEs, an 

additional 28 percent of reported errors involved near misses. Medication administration errors 

involving wrong time, omission, and wrong dose accounted for 77.3 percent of errors, while 

wrong drug and wrong patient accounted for 77.8 percent of near misses. The most frequent 

types of medication errors were wrong time (33.6 percent), wrong dose (24.1 percent), and 

wrong drug (17.2 percent), and the three most frequent types of near misses were wrong drug 

(29.3 percent), wrong dose (21.6 percent), and wrong patient (19.0 percent).85 Many of the 

reported MAEs in ICUs involved intravenous medications and fluids.84 In these surveys, the 

nurses who reported making errors described between two and five errors during a 14-day 

period. 

At the more advanced stage of incident reports, one study reviewed 68 malpractice cases 

involving MAEs in Sweden.80 Among the cases reviewed, the majority of MAEs made by nurses 

9 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

10 

involved wrong dose. When the nurses delegated the drug administration to subordinate staff, the 

majority of MAEs involved wrong drug or wrong concentration of a drug. Errors, which were 

reported to the immediate supervisor, were also reported to the physician in 65 percent of cases. 

The reported causes of MAEs were lack of administration protocols, failure to check orders, 

ineffective nurse supervision when delegating administration, and inadequate documentation. 

One study assessed medication errors using 31 medical records of patients discharged from a 

psychiatric hospital and found a total of 2,194 errors.43 Of these, 997 were classified as MAEs 

(4.7 percent of all doses, and 66 percent of all errors). Of these, 61.9 percent were due to 

scheduled doses not documented as administered, 29.1 percent as drugs administered without an 

order, 8 percent as missed doses because of late transcription, and 3 percent resulting from orders 

not being correctly entered in the pharmacy computer.
Table 1. Comparison of the Incidence of Medication Administration Errors by Type Categories 

11

Buckley 200724

n = 15 

Tang 200793

n = 72

Balas 200684

n = 127 

Kopp 200645

n = 132 

Wolf 200644

n = 1,305 

Prot 200578

n = 538 

Handler 200492

n = 88 

Colen 200388

n = 1,077 

Tissot 200391

n = 78 

Percentages (%)

Wrong patient - - 4.7 - 9.2 - 4.5 0 Wrong drug/unauthorized drug 

0 26.4 10.2 0 8.4 12 11.3 0.46 13 

Wrong dose 26.7 36.1 20.5 12 17.2 15 19.3 1.0 12 Wrong route 0 8.3 3.9 0 3.6 19 - 0.19 Wrong time/frequency 26.7 18.1 37.8 10 16.9 36 29.5 20.0 26 Wrong form 0 - - 0 0.4 8 - 0.09 Wrong administration technique 

20 - - 14 3.4 3 - 0.19 4 

Omission 0 - 22.0 48 19.0 5 - 3.3 16 Extra dose 26.7 - - 14 14.1 0 - - - Deteriorated drug - - - - - 2 - - - Drug past expiration date 

- - - - - - - - - 

Drug reaction/allergy 0 - - 0 - - - - - Infiltration/extravasation - - - - - - - - - Maintenance intravenous fluid/total parenteral nutrition 

0 - - 2 - - - - 

Wrong concentration - - - - - - - - - Wrong drug preparation 

- - - - 3.1 - - 0.09 4 

Wrong rate - - - - - - - - 19 
12

Wrong solution 

- - - - - - - 0 - 

Wrong storage - - - - - - - - - Other/Not specified - - 0.8 - - - 35.2 1.5 6 Note: “-” represents variable not included in analysis or not reported. 
Medication Administration Safety

The number of studies using direct observation of medication administration is increasing in 

response to the concern about the accuracy of other sources of data. Ten studies were found, only 

three of which were done in the United States. While we attempt to summarize across these 

studies, it is difficult to determine consistency across studies as each focused on different sets of 

errors (some only intravenous errors, some included gastrointestinal tube technique) and were 

conducted in different settings. In many of the non-U.S. studies, nurses dispensed drugs from 

ward stock and prepared many of the intravenous solutions for administration. 

Three observational studies were conducted in pediatric units—one in France,78 one in 

Switzerland,25 and one in the United States.24 Buckley24 reported 52 of the 263 doses (19 

percent) observed to be in error, but only 15 (6 percent) of those were in the administration stage. 

Those 15 were nearly evenly divided among wrong dose, wrong time, wrong technique, and 

extra dose categories. Prot78 reported nearly 50 percent more MAEs. Of the 1,719 observed 

doses, 467 (27 percent) were in error, including wrong time; excluding wrong-time errors, the 

error rate was 13 percent of doses. The categories with the most MAEs in Prot’s study were 

wrong time, wrong route (GI tube versus oral), wrong dose, unordered drug, wrong form, and 

omissions. Schneider and colleagues25 reported an overall 26.9 percent error rate with wrongtime errors, and an 18.2 percent rate excluding wrong-time errors. Common errors in addition to 

wrong time were wrong dose preparation and wrong administration technique. 

The incidence of intravenous drug errors was observed in three studies, one in England,89 one 

in Germany,90 and one in both countries.37 About 50 percent of the doses were determined to 

contain at least one error. Compared to other studies, this rate is surprisingly high, and it 

included preparation technique errors (selection of diluent/solvent) as well as administration 

errors (rate of bolus injection and infusion rate). Part of the explanation may come from 

institutional (type of pharmacy support available) and professional training factors. (German 

nurses are not trained to do intravenous medications.) 

Three studies focused on medication administration in ICUs in the United States,45 in 

France,91 and in the Netherlands.94 Kopp and colleagues45 looked at all medication errors and 

report that 27 percent of doses were in error; of these 32 percent could be attributed to the 

administration stage. Within the MAEs, most were omitted medications; the rest were evenly 

distributed among wrong dose, extra dose, and wrong technique. Few wrong-time errors were 

noted. Tissot91 and van den Bernt94 examined only administration stage errors and reported very 

different rates. Tissot reported 6.6 percent of the 2,009 observed doses were in error, most from 

wrong dose, wrong rate, and wrong preparation technique. Excluding wrong-time errors, van den 

Bernt reported a 33 percent error rate that included preparation errors with diluent/solvent issues, 

infusion-rate errors, and chemical incompatibility of intravenous drugs. It is likely that the 

differences in rates across these studies are due to the range of error types observed in each study 

as well as the varying responsibilities of nurses in the three countries. 

The most extensive observation study, by Barker and colleagues,87 conducted observations of 

medication administration in 36 randomly selected health care facilities (acute and long-term 

care) in two States in the United States. Of the 3,216 doses observed, 605 (19 percent) contained 

at least one error. Nearly half of those errors were wrong-time errors. Other common types of 

errors included omission, wrong dose, and unauthorized (unordered) drug. In a much smaller 

study conducted in the Netherlands, Colen, Neef, and Schuring88 found an MAE rate of 27 

percent, with most of these wrong-time errors. The rate of MAEs without wrong time was 

approximately 7 percent, and most of those were omissions. 

13 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

14 

Information from these research studies forms a consistent picture of the most common types 

of MAEs. These are wrong time, omissions, and wrong dose (including extra dose). Rates of 

error derived from direct observation studies ranged narrowly between 20 and 27 percent 

including wrong-time errors, and between 6 and 18 percent excluding wrong-time errors. The 

alarming exception to this was the nearly 50 percent error rate in observation of intravenous 

medication in ICUs in Europe. 
Evidence Table 1. Types of Reported and Observed Medication Administration Errors (MAEs) 

Source Safety Issue 

Related to Clinical Practice 

Design Type Study Design & Study 

Outcome Measure(s) 

Study Setting & Study Population 

Key Finding(s) 

Balas 200485 Type of MAEs Cross- sectional 

study 

Voluntary, self-reported recording of 14 days of shift work, sleep, and errors using a journal 

393 full-time registered nurses (RNs) in hospitals responded to the survey. 

37.8% of nurses reported medication made on average between 2 and 5 eReported top types of medication er(33.6%), wrong dose (24.1%), and wcompared to the top three types of nwrong drug (29.3%), wrong dose (21(19.0%). 

Balas 200684 Types of MAEs or near errors Cross- sectional 

study 

Voluntary, self-reported recording of 14 days of shift work, sleep, and errors using a journal 

502 RNs in critical care units throughout the United States 

Of the 224 errors and 350 near errormedications. Wrong time, omission, accounted for 77.3% of MAEs, and wand wrong patient accounted for 77.

Barker 200287 Types of MAEs Cross- sectional Observation of 3,216 doses administered by 

nurses in 36 randomly selected institutions 

12 accredited hospitals, 12 nonaccredited hospitals, and 12 nursing homes 

19% of doses were in error including excluding wrong time. The most freqtime were omissions and wrong dosinstitutions. 

Buckley 200724 Types of MAEs Prospective cohort study Direct observation over 6 months of medication 

process, determining actual and potential errors. Observers would intervene if error was considered harmful to patient. 

In a 16-bed pediatric medical/surgical ICU at a tertiary care academic medical center 

263 doses observed and 19% were doses were affected by an MAE. Coadministration were wrong dose, wrowrong technique. Proximal causes owere slips and memory lapses, lack rule violations. 

Colen 200388 Types of MAEs Prospective cohort study One phase of a study of the evaluation of a 

medication distribution system involving direct observation of administration. Observers would intervene if error was considered harmful to patient. 

1,077 doses were observed in 1 teaching hospital in the Netherlands 

The MAE rate was 27.2% including wexcluding wrong time. The major typwrong time (20.0%) and omissions (

15
16

Source Safety Issue Related to Clinical Practice Design Type Study Design & Study Outcome Measure(s) Study Setting & Study Population Key Finding(s) Grasso 200343 Types of MAEs Retrospective cohort study Review of patient records for patients discharged from the Augusta Mental Health Institute in Maine, during a period of 14 weeks 2,194 medication errors, of which 1,432 were MAEs, from 31 patient records MAEs represented 65.3% of all med

61.9% of MAEs were due to a scheddocumented as administered, 29.1% without an order, 8% as missed dose transcription, and 3% resulting from entered in the pharmacy computer. Kapborg 199980 Types of MAEs Retrospective cohort study Analysis of malpractice cases and small interview survey with 8 nurses working in nursing homes and home care setting using semistructured questions 68 cases of MAEs occurring in several types of home care settings and nursing homes during a 4-year period, reported to a regional supervisory unit of the National Board of Health and Welfare in Sweden The majority of MAEs made by nurswhat was prescribed and when the ddelegated to subordinate staff; the mwrong drug or wrong concentration o

Kopp 200645 Types of MAEs Prospective cohort study Direct observation over 6 months by 2 pharmacy residents specializing in critical care pharmacy. Pharmacy residents 

would intervene if MAE would have resulted in patient harm. 

1 16-bed medical/surgical ICU in a tertiary care academic medical center in Arizona 

Overall, 27% of doses were in error. (32%) were attributed to medication of those (48%) were errors of omissitypes were wrong dose, extra dose, Thirty seven (34%) of ADEs attributeadministration were considered potethose were intercepted. 

McCarthy 200086 Types of MAEs Cross- sectional 

study 

Voluntary, randomly selected survey of members of the National Association of School Nurses 

649 school nurses (64.9% response rate) in the United States 

48.5% of respondents reported medmajority of the types of errors were mundocumented doses. 
17

Source Safety Issue 

Related to Clinical Practice 

Design Type Study Design & Study 

Outcome Measure(s) 

Study Setting & Study Population 

Key Finding(s) 

Prot 200578 Types of MAEs Prospective cohort study Direct observation of nurses administering 

medications to patients. Observers would intervene if MAE would have resulted in patient harm. 

1,719 doses were observed on 4 units at a pediatric teaching hospital in Paris, France. 

27% of doses were in error (538 MAwere 36% of MAEs, wrong route wa15%, and unordered drug was 10%. The risk of an MAE increased if the madministered by a nurse intern, a temnurse, or a pool nurse (OR = 1.67, P medication had been prepared by th= 0.02). 

Schneider 199825 Frequency and types of MAEs Cross- sectional Direct observation 275 doses were observed on a 

pediatric ICU in Switzerland 

26.9% of the doses were in error inc18.2% excluding wrong-time errors. types were wrong dose preparation technique. 

Taxis 200389 Types of MAEs in Intravenous 

(IV) drug administration 

Crosssectional Ethnographic—direct observation of nurses 

administering medications 

430 IV drug doses were observed for nurses working in 10 wards in 2 hospitals in the UK. 

Overall error rate was 49%; wrong-ticounted. Of the 212 errors observedadministering a bolus dose too fast, accounted for 15%. Majority of preparations errors by nurequiring multiple-step preparations, wrong dose or selecting the wrong s

Taxis 200390 Types of MAEs in IV drug 

administration 

Crosssectional Ethnographic—direct observation of nurses 

administering medications 

22 staff nurses on 2 units in a German hospital were observed administering 122 IV doses. 

Overall error rate was 48%. Wrong-tcounted. Of the errors, the largest prmultiple-step drug preparation procelargest was administering incompatibsame line. Majority of preparations epreparing the wrong dose or selectin

Tissot 200391 Type of MAEs Prospective cohort study Direct observation of nurses administering 

medications to patients by a pharmacist 

Medical ICU in France 

Of the 2,009 nursing acts observed, Wrong dose was the most frequent erate of administration, errors in prepaphysicochemical incompatibility. 

Ven den Bernt 200294

Frequency and type of MAEs 

Crosssectional Direct observation of nurses administering 

medication to patients 

233 drug administrations in 2 Dutch hospitals 

Overall, 104 doses had errors (44.6%77 (33%) excluding wrong time. The were wrong dose preparation and wtechnique. 

Wirtz 200337 Types of MAEs in IV drug 

administration 

Crosssectional Ethnographic— disguised observation 

of nurses preparing and administering medications 

337 drug preparations and 278 drug administration were observed in 2 German and one UK hospital. 

Across the three sites, the rate for pand the rate for administration errors common errors were wrong administwrong dose. The types of errors varied across the different pharmacy systems, althougadministered IV meds on the wards. 
18

So

urce Safety Issue Related to Clinical Practice Design Type Study Design & Study Outcome Measure(s) Study Setting & Study Population Key Finding(s) Wolf 200644 Types of MAEs Retrospective cohort study Analysis of MAEs reported January 1, 1999, to December 21, 2003, by nursing students during the administration phase MAEs reported by 1,305 nursing students in the USP MEDMARX program Majority of MAEs were associated w

dose (17%), wrong time (17%), and The major causes of MAEs were rep(human) deficit (51%), procedure/proand knowledge deficit (27%). Of the reported contributing factors, inexperience of staff. When an MAE occurred, 55% of the were informed and 44% received ed
Medication Administration Safety

Impact of Working Conditions on Medication Errors 

Medication safety for patients is dependent upon systems, process, and human factors, which 

can vary significantly across health care settings. A review of the literature found 34 studies that 

investigated some aspect of working conditions in relation to medication safety. 

Systems factors. Systems factors that can influence medication administration include 

staffing levels and RN skill mix (proportion of care given by RNs), shift length, patient acuity, 

and organizational climate. There were 13 articles presenting research findings and three 

literature reviews. The major systems/organizational factors included nurse staffing, workload, 

organizational climate/favorable working conditions, policies and procedures, and technologies 

enabling safety or contributing to MAEs. 

Nurse staffing: Medication administration is a key responsibility of nurses in many settings, 

and three studies assessed the relationship between nurse staffing, hours of nursing care in 

hospitals, RN skill mix, and medication errors. Two studies associated the total hours of care and 

the RN skill mix at a patient care unit to reported medication error rates in those units; one study 

used 42 units in a large Midwestern hospital95 and the other used 39 units in 11 small hospitals.96

Rates of MAEs, when the number of doses was the denominator, were highest in medicalsurgical and obstetric units; when patient days were the denominator, the highest rate was in 

ICUs. In both studies the type of unit was controlled and the rate of reported medication errors 

declined as the RN skill mix increased up to an 87 percent mix. A third study of nurses in ICUs 

in 10 hospitals found an inverse relationship between rates of medication errors and staffing 

work hours per patient day in specific settings (e.g., cardiac ICUs and noncardiac intermediate 

care settings). A little over 30 percent of the variance in medication error rates resulted from the 

variance in staffing work hours per patient day.97 

Other studies conducted prior to 1998 did not find a relationship between staffing and 

medication errors. Three literature reviews,30, 39, 98 concluded that the direct evidence for a 

relationship between staffing and MAE rates was inconsistent. Nurses’ perceptions of the impact 

of staffing or workload on medication errors, however, is quite consistent. 

Workloads: These findings are consistent with three studies and two literature reviews on the 

impact of heavy workloads, a component of nurse staffing, on errors. In one survey of nurses in 

11 hospitals, both pediatric and adult nurses reported staffing ratios and the number of 

medications being administered as being the major reasons why medication errors occur.58 A 

second survey found that nurses from Taiwan also indicated that workload was a major factor in 

medication errors.93 Beyea, Hicks, and Becker81, 82 and Hicks and colleagues38 analyzed 

MEDMARX data for medication errors in the operating room, postanesthesia, and in same-daysurgery units. Most of these errors involved nurses (64–76 percent) and medication 

administration (59–68 percent). In all three sets of error reports, workload increases and 

insufficient staffing were noted to be causes of errors. 

The effect of heavy workloads and inadequate numbers of nurses can also be manifested as 

long workdays, providing patient care beyond the point of effective performance. In a national 

survey by Rogers and colleagues,99 self-reported errors by nurses found that the likelihood of a 

medication error increased by three times once the nurse worked more than 12.5 hours providing 

direct patient care. Among nurses working more than 12.5 hours, the reported errors, 58 percent 

of actual errors and 56 percent of near misses were associated with medication administration.

19 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

Other findings support the importance of adequate nurse staffing and understanding the 

impact of shift work in decreasing medication errors. A review of incident reports found that the 

major contributing factors to errors were inexperienced staff, followed by insufficient staffing, 

agency/temporary staffing, lack of access to patient information, emergency situation, poor 

lighting, patient transfers, floating staff, no 24-hour pharmacy, and code situations.44 Certain 

aspects of shift work can also impact medication safety, as shown in a review of research 

conducted in the 1980s and early 1990s that indicated that there was a difference in the number 

of errors by shift, but no difference in the number of hours worked (8 versus 12 hours). However, 

there were more errors with nurses working rotating shifts.30 

Organizational climate: Other systems/organizational issues include the presence of 

favorable working conditions, effective systems, policies and procedures, and technologies that 

enable safety or contribute to MAEs. An assessment of medication administration behaviors of 

176 nurses in rural Australia, using structural equation modeling to test the association between 

organizational climate and the administration behaviors of nurses, found that the variable 

“violations” was the only variable with a direct contribution to MAEs, but there was no direct 

linkage to actual errors. While it was not possible to determine the effect of organizational 

climate on violations, distress was positively associated with violations, while quality of working 

life, morale, and organizational climate had a negative association. The organizational climate 

was found to be linked with safety behavior.100 Hofmann and Mark101 did find that the safety 

climate on patient care units was linked to the rate of harm-producing medication errors in a 

study using data collected from 82 units in 41 hospitals. Higher overall safety climate was related 

to lower rates of medication errors and urinary tract infections. 

Policies, procedures, and protocols: Lack of appropriate policies, procedures, and protocols 

can impact medication safety, as seen in a few small studies. In a study of malpractice cases, 

medication errors were associated with lack of administration protocols and ineffective nurse 

supervision in delegating administration.80 However, even when policies are in place, they may 

not necessarily improve safety. For example, a review of two studies in the literature found that 

medication errors did not necessarily decrease with two nurses administering medications (e.g., 

double-checking).30 In addition, appropriate policies may not be followed. Double-checking 

policies are commonly used as a strategy to ensure medication safety. When errors occurred 

under such policies, failure to double-check doses by both pediatric and adult nurses 58 and 

nurses in a Veterans Affairs (VA) hospital102 were reported. However, research presented in two 

literature reviews offers somewhat conflicting information. In the first review of three studies, 

following double-checking policies did not necessarily prevent errors.39 Yet in the other review, 

failure to adhere to policies and procedures was associated with errors.30 

Process factors. Process factors that influence medication administration include latent 

failures that can instigate events resulting in errors, such as administrative processes, 

technological processes, clinical processes, and factors such as interruptions and distractions. 

These factors reflect the nature of the work, including “competing tasks and interruptions, 

individual vs. teamwork, physical/cognitive requirements, treatment complexity, workflow.”103

A review of the literature found 18 studies and 2 literature reviews that contained process factors 

and their association to medication errors by nurses. 

Distractions and interruptions: Factors such as distractions and interruptions, during the 

process of delivering care can have a significant impact on medication safety. Nine studies, four 

with nationwide samples, and two literature reviews present information on the association 

between MAEs and distractions and interruptions. One survey of nurses in three hospitals in 

20 
Medication Administration Safety

Taiwan found that they perceived distractions and interruptions as causes of errors.93 In three 

other surveys in the United States, nurses ranked distractions as major causes for the majority of 

medication errors.58, 61, 102 In a small, five-site observational study of medication administration 

among 39 RNs, licensed practical nurses (LPNs) and certified medical technicians/assistants 

(CMT/As), Scott-Cawiezell and colleagues104 found an increase in medication errors attributable 

in part to interruptions, and when wrong-time errors were excluded, the error rate actually 

increased during medication administration. 

These finding are furthered by research concerning self-reported errors from a nationwide 

sample of nurses.84 The nurses believed the cause of their reported medication errors and near 

errors were interruptions and distractions. In a secondary analysis of the MEDMARX® data base, 

distractions and interruptions were prominent contributing factors to medication errors.81–83

Furthermore, these findings are supported by three reviews of the literature: one found that 

distractions and interruptions interfered with preparing and administering medication, potentially 

causing errors;30 interruptions were perceived as causing medication errors in the second 

review;98 and the third indicated that rapid turnover and changes as well as distractions and 

interruptions contributed to errors.39

Documentation of the medication administration process: One small study investigated nurse 

adherence to a hospital policy to document medications administered and their effects on 

patients. From a sample of 12 nurses in one hospital, one-third of progress notes were found to 

contain information about administered medications, yet only 30 percent of those progress notes 

included medication name, dose, and time of administration, and only 10 percent documented 

information about desired or adverse effects of medications. Medication education, outcomes of 

administered medication, and assessment prior to administering were not documented in any 

progress note. Only half of withheld medications were documented.105 In a review of records to 

detect medication errors, Grasso and colleagues43 found that 62 percent did not document doses 

as administered. 

Communication: Five studies and one literature review assessed the relationship between 

communication failures and medication errors. A small observational study of 12 nurses found 

that they communicated with other nurses about information resources on medications, how to 

troubleshoot equipment problems, clarification in medication orders, changes in medication 

regimens, and patient assessment parameters when handing over patients.106 Nurses 

communicated with physicians informally to exchange information, about the absence of other 

physicians, and in both unstructured and structured ward rounds. Nurses also communicated with 

pharmacists about information on medication administration and organizing medications for 

patient discharge. Another direct observational study of medication administration found 

opportunities for errors associated with incomplete or illegible prescriptions.91 This finding was 

supported by two related literature reviews that indicated that illegible and poorly written drug 

prescriptions and breakdowns in communication led to errors.30, 39 Another survey found that 

nurses ranked difficult/illegible physician handwriting as a cause of the majority of medication 

errors, but did not consider withholding a dose because a lab report was late or omitting a 

medication while the patient was sleeping as something that should have been communicated to 

physicians or others.61

A small survey of 39 nurses in three hospitals in Nova Scotia about communication failures 

during patient transfers found that more than two-thirds of nurses reported difficulty in obtaining 

an accurate medication history from patients when they were admitted; 82 percent reported 

patients were unable to provide accurate medication histories. When patients were transferred 

21 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

from across units, 85 percent of nurses reported that medication orders were rewritten at transfer, 

92 percent that medication orders were checked against electronic medical records, 62 percent 

that it was time consuming to clarify medication orders, 66 percent that the reasons for 

medication changes were made at transfer, and 20 percent that blanket orders are often written as 

transfer orders.107 

Complexity: Three studies investigated the impact of complexity on medication safety. In a 

small, five site observational study of medication administration of 39 RNs, LPNs and CMT/As 

in long-term care settings, Scott-Cawiezell and colleagues104 found that even though RNs 

administered fewer medications they had more MAEs, compared to LPNs and CMT/As. The 

suggested explanation was that the mediations RN must administer in long-term care are those 

with more complexity. Another survey of 284 RNs in 11 hospitals found that pediatric and adult 

nurses reported numbers of medications being administered as a major reason on why 

medication errors occur.58 Also, another survey of nurses found that they perceived that 

complicated doctor-initiated orders (24 percent) and complicated prescription were the major 

causes of MAEs related to the medication administration process.93 

Equipment failure while administering medication: Three studies found that systems and 

process factors can interfere with medication administration when equipment used in 

administration does not perform properly, exposing the nurse and patient to safety risks. In two 

ICU studies, infusion pump problems were involved in 6.7 percent of 58 MAEs in one study24

and 12 percent of the 42 MAEs in the other sutdy.45 Another investigation of smart pumps with 

integrated decision-support software found that half of the ADEs were considered preventable 

(2.12 of 100 patient-pump days), and 72 percent of preventable ADEs were serious or lifethreatening.108 Given the number of ADEs, the fact that the drug library was bypassed in 24 

percent of the infusions, and the frequency of overriding alerts, the investigators concluded that 

use of the smart pumps did not reduce the rate of serious medication errors—but possibly could 

if certain process factors could be modified, such as not allowing overrides. 

Monitoring and assessing: An essential component of the medication process related to the 

administration of medications is monitoring and assessing the patient by the nurse. Only two 

studies provided information in this area, offering scant evidence. In the first, based on a small 

sample of nurses in one unit in one hospital, a qualitative analysis of observed medication 

administration found that participants monitored patients before, during, and after medication 

administration.109 Nurses assessed vital signs, lab values, ability to swallow, and patients’ selfreport of health. They also felt responsible for timing medication administration and providing 

as-needed (e.g., PRN) medications. In the second study, where ICU nurses were surveyed, no 

administration errors were found to be associated with inadequate monitoring or lack of patient 

information.24 

Effects of Human Factors on Medication Administration Errors 

There are a wide range of system-related human factors that can impact medication 

administration. These factors include characteristics of individual providers (e.g., training, 

fatigue levels), the nature of the clinical work (e.g., need for attention to detail, time pressures), 

equipment and technology interfaces (e.g., confusing or straight-forward to operate), the design 

of the physical environment (e.g., designing rooms to reduce spread of infection and patient 

falls), and even macro-level factors external to the institution (e.g., evidence base for safe 

practices, public awareness of patient safety concerns).103 There were 10 studies that assessed the 

22 
Medication Administration Safety

association of human factors with MAEs. Four major themes emerged in the review: fatigue, 

cognitive abilities, experience, and skills. 

Effects of fatigue and sleep loss: Five studies assessed the association between fatigue and 

sleep loss with MAE errors. The first specifically investigated the effects of fatigue and sleep 

loss on errors using a national sample of nurses over a 2-week period. In this study, the rate of 

errors increased after working 12.5 hours.99 A subpopulation of critical care nurses reported 

forgetfulness, heavy workload, distractions, and high patient acuity as causes for their 

medication errors or near errors.84 Fatigue and sleep loss was also a factor in a subpopulation of 

ICU nurses, who reported errors with high-alert medications (e.g., morphine, chemotherapeautic 

agents).85 The other two studies assessed fatigue along with other variables associated with 

medication errors. In one of these, a survey of 57 nurses, respondents reported that the majority 

of medication errors were attributable to fatigue.70 The other study, a survey of 25 nurses in one 

hospital, found that one of the most frequently perceived causes of medication errors for nurses 

was being tired and exhausted (33.3 percent).102

The thought processes of nurses during medication administration was assessed in two 

studies. A semistructured, qualitative interview of 40 hospital nurses prior to implementation of a 

bar-coding system explored the thinking processes of nurses associated with medication 

administration.110 Their thought processes involved analyzing situations and seeking validation 

or a solution when communicating about patients; using knowledge, experience, and 

understanding of patients’ responses to anticipate problems; integrating their knowledge of lab 

values and patterns of pathophysiological responses to determine possible need to change dosage 

or administration timing; checking orders for validity and correctness; assessing patients’ 

responses for possible side effects and effectiveness of the drug; using cues from patients or 

family members about need for explanations about drugs; bypassing protocols or procedures, 

some taking a risk, to get drugs to patients or use time more efficiently; anticipating needs for 

future problem solving; and applying professional knowledge during drug administration. The 

other study of nurses, using direct observation in a medical and surgical unit in Australia, found 

that participants used hypothetico-deductive reasoning to manage patient problems.111 Graduate 

nurses used pattern recognition of patient characteristics and medications during decisionmaking. 

Intuition and tacit knowledge was used in relation to changes in patients’ vital signs and to 

objectively monitor patients. 

Thought process can also be distorted by distractions and interruptions. One study employed 

direct observation of medication administration to determine the effects of human factors on 

MAEs.24 The investigators found that slips and memory lapses were associated with 46.7 percent 

of MAEs. During both the prescribing and administration of medications, the causes of errors 

were attributable to slips and memory lapses (23.1 percent during prescribing vs. 46.7 percent 

during administration), lack of drug knowledge (46.2 percent during prescribing vs. 13.3 percent 

during administration), and rule violations (30.8 percent during prescribing vs. 13.3 percent 

during administration). Another study using direct observation found causes associated with 

MAEs to include slips and memory lapses (40 percent), rule violations (26 percent), infusion 

pump problems (12 percent), and lack of drug knowledge (10 percent).45

Experience and skills also impact thought processes. In one study of 40 student nurses and 6 

nurses using a computerized program to assess the impact of dyslexia found that the greater the 

tendency towards dyslexia, the poorer the potential cognitive ability to effectively provide the 

skills associated with effective drug administration.112 Similarly, in two reviews of the literature, 

23 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

24 

a number of medications errors were found to be caused by poor mathematical skills,30 especially 

if mathematical skills were needed to properly administer drugs.39

Lack of medication knowledge is a constant problem, and there is a need to continually gain 

more knowledge about current and new medications.30 Nurses with more education and 

experience may have greater knowledge of medications.39 However, experience has not been 

found to mitigate the effect of poor mathematical skills nor frequency of MAEs.30 Those new to 

a unit or profession may be at risk for errors.39 In a survey of nurses working in three hospitals in 

Taiwan, nurses reported causes of MAEs as new staff (37.5 percent), unfamiliarity with 

medication (31.9 percent), unfamiliarity with patient’s condition (22.2 percent), and insufficient 

training (15.3 percent).93 Inexperience may also contribute to performance (human) deficit, 

willingness to follow a procedure/protocol, and knowledge deficit. Of these reported contributing 

factors, 78 percent were due to the inexperience of staff.44 Blegen, Vaughn, and Goode113 found 

that medication errors rates were inversely related to the proportion of nurses on a unit with 

greater experience, but were not related to the educational level of the staff on the unit. 
Evidence Table 2. Working Conditions Associated With Medication Administration Errors and Adverse Drug Event

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Aitken 2006105

Process Factors: 

Documentation of medication administered by nurse 

Crosssectional study 

Review of patient medication charts and progress notes for one working shift. Each participant was interviewed. 

47 nurses in one urban teaching hospital in Australia 

None 34% of progress no

about administered 30% of progress nomedication name, dadministration. Medication educatioany progress note. Outcomes of adminnot documented, noadministering. 10% of progress noinformation about dof medications. Only half of withheldocumented. 

25
26

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Armitage 200339 System Factors: Workload 

Process Factors: Lack of doublechecking Failure to follow 

policies and procedures 

Distractions and 

interruptions 

Communication 

processes 

Human Factors:

Individual characteristics and abilities associated with medication administration errors (MAEs) 

Literature review 

Expanded upon the O’Shea (1999)30review 

Literature on drug administration, drug error, and nursing was reviewed. 

None Workload—4 studie

findings on the relatand errors. Lack of double-chethat double-checkinprevent errors. Failure to follow polstudies indicated thpolicies has been aDistractions and intindicated that rapid well as distractions contributed to errorCommunication failthat illegible and poprescriptions led to Mathematical skills indicated that poor put nurses at risk foneed complex mathadminister drugs. 3 indicated weight-bamathematical calcuin potential risk of eKnowledge of mediindicated that knowbe greater in nurses experience. Length of nursing eindicated that those profession may be 

Balas 200684 System Factors: Workload and 

staffing Process Factors:Distractions and interruptions 

Crosssectional Qualitative 14-day self-reported record 

of shift work and errors 

502 RNs in critical care units 

None Nurses reported for

workload, distractioas causes for their errors. 
27

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Beyea 200381 System Factors: Workload and 

staffing Process Factors: Distractions and interruptions Human Factors: 

Experience 

Secondary analysis 

179 reported medication errors in same-day surgery 

MEDMARX

®

data 

None Workload increase 

insufficient staffing Distraction associatInexperienced staff reports. 

Beyea 200382 System Factors: Workload and 

staffing Process Factors:

Distractions and interruptions Human Factors:

Experience 

Secondary analysis 

731 reported medication errors in the operating room 

MEDMARX

®

data 

None Workload increase 

insufficient staffing Distraction associatInexperienced staff 

Blegen 199895 System Factors: Staffing and RN 

skill mix 

Crosssectional Administrative data for nurse staffing and 

medication errors at the patient care unit level 

42 units in 1 large tertiary care hospital 

None Rates of medication 

associated with RN proportion of 87.5%errors were positive(0.192). 

Blegen 199896 System Factors: Staffing and RN 

skill mix 

Crosssectional study 

Analysis of event reports and nurse staffing patterns for 10 quarters 

39 units in 11 hospitals 

None Rates of MAEs by 1

in medical-surgical were highest by 1,0Units with RN propohad higher rates of 

Blegen 2001113

Human Factors:

RN education and experience 

Crosssectional study 

Secondary data analysis 

80 units in 12 hospitals 

None MAEs were inverse

experience but wereducation. 
28

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Buckley 200724

Process Factors: Communication 

processes 

Medication 

administration process 

Human Factors:

Individual characteristics associated with MAEs 

Prospective cohort study 

Anonymous survey of pediatric ICU nurses about the medication process, followed by a direct observation over 6 months of medication process, determining actual and potential errors. Observers of medication administration would intervene if error was considered harmful to patient. 

In a 16-bed pediatric medical/surgical ICU at a tertiary care academic medical center 

None Faulty interaction w

and infusion pump administration errorassociated with druinadequate monitorinformation. Majority of MAEs wand memory lapses knowledge (13.3%)

Carlton 200698 System Factors: Length of work 

shift 

Staff skill mix Patient acuityProcess Factors: Interruptions Unclear orders Medications 

received late 

Human Factors: 

Skill/education/ 

experience 

Knowledge of 

medications

Literature review 

Medication administration literature published before 2005 

None 5 studies reviewed 

skill mix with MAEson skill mix is confli1 study reviewed a found increasing nu(MEs) associated wnewborns. Many MAEs are no1 study of a cross-sfound that nurses pcaused by late arrivpharmacy, RNs too failure in oversight, administration reco1 study found lack oskill/experience, faiand procedures, anas active errors by 
29

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Chevalier 2005107

Process Factors: 

Nurse management of the medication administration process 

Crosssectional study 

Retrospective survey on safety culture 

39 nurses (35% response rate) in 3 hospitals in the Capital Health district of Nova Scotia 

None 69% of nurses repo

an accurate medicawhen they were admpatients were unabmedication histories When patients were unit, 85% of nurses orders were rewrittemedication orders welectronic medical rtime consuming to c66% that the reasonmade at transfer, anorders are often wri

Eisenhauer 2007110

Human Factors:

Individual characteristics associated with MAEs 

Crosssectional study 

Semistructured, retrospective, qualitative interview of nurses; then used basic content analysis of the narrative data. 

40 staff nurses in one northeastern U.S. hospital where barcoding was being implemented 

None Nurses’ thought pro

medication adminis

- Analyzed situa

validation or a communicating 

- Used knowled

understanding anticipate prob

- Integrated thei

and patterns oresponses to dchange dosag

- Checked orde

correctness. 

- Assessed patie

possible preseeffectiveness o

- Used cues from 

members abouabout drugs. 

- Bypassed prot

taking a risk, to use time more 

- Anticipated ne

solving. 

- Applied profes

drug administr
30

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Fogarty 2006100 System Factors: Organizational 

climate 

Crosssectional study 

Survey included a 6-item quality of work life, satisfaction with working conditions, positive and negative affect, organizational climate, and a procedure violation scale. 

176 nurses in rural Australia working in 11 public sector hospitals 

None “Violations” was the 

contribution (24%) tDistress was positivviolations, while quaand organizational association. It was not possible organizational climamediated by stress organizational climabehavior. 

Hicks 200438 System Factors: Workload and 

staffing Process Factors: Distractions and interruptions Human Factors: 

Experience 

Retrospective cohort study 

645 reported medication errors in postanesthesia care unit 

MEDMARX

®

data 

None Workload increase 

insufficient staffing Distraction associatInexperienced staff error reports. 

Hofmann 2006101 System Factors: Safety climate Cross- sectional 

study 

Survey and administrative data from 82 units in 41 hospitals 

None Increased safety cli

with lower rate of mharm. 

Kapborg 199980

Process Factors:

Policies and 

procedures 

Supervision Documentation of 

administration 

Retrospective cohort study 

Analysis of malpractice cases and small interview survey with 8 nurses working in nursing homes and home care setting using semistructured questions 

68 cases of MAEs occurring in several types of home care and nursing home settings 

None Reported causes of 

administration protoorders, ineffective ndelegating administdocumentation. 
31

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Kopp 200645 Process Factors:

Equipment malfunction during medication administration Human Factors:

Individual characteristics associated with MAEs 

Prospective cohort study 

Voluntary survey of nurses on the medication use process followed by direct observation over 6 months by 2 pharmacy residents specializing in critical care pharmacy. Pharmacy residents would intervene if MAE would have resulted in patient harm. 

1 16-bed medical/surgical ICU in a tertiary care academic medical center in Arizona 

None 12% of the 42 MAE

pump problems. Causes associated and memory lapses (26%), lack of drug 

Manias 2004109

Process Factors:

Medication management and patient monitoring 

Prospective cohort study 

Qualitative participant observation and questioning of nurses during medication administration 

12 graduate nurses in medical and surgical units of a university teaching hospital in Melbourne, Australia 

None To monitor patients 

medication adminisvital signs, lab valuepatient self-report oParticipants felt resmedication adminisneeded medications

Manias 2004111

Human Factors:

Cognitive reasoning 

Prospective cohort study 

Qualitative participant observation of nurses during medication administration 

12 graduate nurses in medical and surgical units of a university teaching hospital in Melbourne, Australia 

None Participants used h

reasoning to managGraduate nurses uspatient characteristdecisionmaking. Intuition and tacit knrelation to changes objective monitoring 
32

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Manias 2005114

Process Factors:

Communication with health care providers 

Prospective cohort study 

Qualitative participant observation of nurses during medication administration 

12 graduate nurses in medical and surgical units of a university teaching hospital in Melbourne, Australia 

None Nurses communica

about information rehow to troubleshoot clarification in medimedication regimenparameters when hNurses communicainformally to exchanabsence of other phunstructured and stNurses communicainformation on medorganizing medicati

Manias 2005106

Process Factors:

Adhering to protocols for medication administration 

Prospective cohort study 

Qualitative participant observation of nurses during medication administration 

12 graduate nurses in medical and surgical units of a university teaching hospital in Melbourne, Australia 

None Protocols were use

were acceptable, obmedications, providseeking additional iphysicians, and proworking in another Nurses examined ththe time before meddouble-checked ceradministration with time; did not complemedication errors (owere observed); sounfamiliar medicatiosought clarity on un100% of the time; ataking oral medicati
33

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Mayo 200461

Process Factors:Lack of order 

clarity 

Communicating 

missed doses 

Crosssectional study 

Random sample of RNs surveyed about perceived causes of medication errors; percentage of medication errors reported to nurse managers; types of reportable incidents; and reporting behaviors, including medication errors scenarios. 

983 RNs (a 20% response rate) in the United Nurses Association of California/Union of Health Care Professionals 

Nurses ranked diffichandwriting, distracexhausted as causemedication errors. Nurses would not cor others when a romedication was withwas late (91.8%) or patient was sleepin

Millward 2005112

Human Factors:

Cognitive skills involved in drug administration 

Prospective cohort study 

Used a computerized program to assess the presence of dyslexia and its effects on drug administration skills 

40 students and 6 qualified nurses 

None The greater the ten

poorer the potential effectively provide sadministration. 

Osborne 199970

Process Factors: Distractions Failure to comply 

with procedures 

Human Factors:

Confusion Fatigue 

Crosssectional study 

Self-reported perception of nurses on medication errors, their causes, and how medication errors should be reported 

57 full-time and part-time RNs (a 62% response rate) in a medicalsurgical unit in a 700-bed community hospital in south Florida 

Main cause of medidentify the right patindicated the effects 
34

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

O’Shea 199930 System Factors: Workload 

Nurse staffing Medication 

delivery systems 

Process Factors:Shift and hours 

worked 

Single nurse drug 

administration 

Adherence to 

policy and procedures 

Distractions and 

interruptions

Human Factors:

Mathematical skills Knowledge of 

medications 

Experience 

Literature review 

Retrospective review of 97 articles published in 1995 and earlier, involving the definition and contributing factors to MAEs 

Studies involving nurses and medication administration 

None Staffing—2 studies 

implications on the the incidence of meShift and hours worthat there was a differrors by shift; and there was no differehours worked (8 vserrors with nurses wWorkload—3 studieof a heavy workload distractions; use of inadequate skill mix errors. Medication delivery indicated that the eunits using a medicmedications. Single nurse drug aindicated that medicnecessarily decreasadministering medicchecking). Adherence to policy studies indicated thfailure to adhere to Distractions and intindicated that distrainterfere with prepamedication, potentiaMathematical skills—a number of medicapoor mathematical Knowledge of mediindicated that not oconstant problem, bcontinually gain mocurrent and new me
35

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

O’Shea 199930

(cont.) 

Length of experienc

that experience did poor mathematical MAEs 

Rogers 200499 System Factors: Nurse staffing 

Shift work 

Crosssectional study 

Qualitative 14-day self-reported record of shift work and errors 

Nationwide sample of 393 nurses (a 40% response rate) 

None The risk of medicat

was nearly three timworked more than 1hour period. In over 80% of shiftafter their schedule

55 minutes longer tWork duration, overworked in a week werrors. 

Rothschild 2005108

Process Factors:

Using smart pumps to decrease medication administration errors 

Randomized clinical trail 

Prospective, randomized timeseries trial comparing the rate of serious medication errors with and without decision support during 11 months. 

1 cardiac surgical intensive care and 2 stepdown units in a hospital in Boston 

Implementation of new intravenous infusion pumps with decision support (i.e., alerts, reminders, and unit-specific drug rate limits) used during medication administration 

During the trial, half preventable (2.12 o72% of preventable threatening. During the interventlibrary (24% of infuswere frequent. Use of the smart purate of serious med

ScottCawiezell 2007104

Process Factors:

Distractions and interruptions 

Prospective cohort 

Naïve, direct observation of medication administration 

8 RNs, 12 LPNs, 19 CMT/As in 5 Midwestern nursing homes 

None RNs administered 1

LPNs 23.3%, and Crate for RNs was 34CMT/As 34.2%. RNs had more interLPNs had more dis

Stratton 200458 System Factors: Workload 

Process Factors:Distractions and interruptions 

Crosssectional study 

Nurses were surveyed to assess the perceived causes of MAEs. 

284 RNs (227 adult and 57 pediatric nurses) in 11 hospitals in 2 States (40% response rate) 

None Pediatric and adult 

distractions and intepediatric nurses anRN-to-patient ratios of medications admand not double-che28%) as the most im
36

Source 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Tang 200793 System Factors:

Workload Process Factors: 

Complicated orders Distractions and interruptions 

Human Factors:

Experience Knowledge and 

skills 

Crosssectional study 

A semistructured questionnaire was used to assess MAE events, background of the nurse, and perceived contributing factors. 

72 female nurses at 3 acute care hospitals (80% response rate) 

None Nurses reported pe

heavy workload (38initiated order (24%prescription as the related to the medicprocess. Personal ndistraction, interrupand poor mood. Nurses reported ca(37.5%), unfamiliari(31.9%), unfamiliari(22.2%), and insuffi

Tissot 200391 System Factors: Workload

Process Factors: Incomplete/illegible orders 

Prospective cohort study 

Direct observation of nurses administering medications to patients by a pharmacist 

A geriatric unit and a cardiovascularthoracic surgery unit within a hospital in France 

None Opportunities for er

incomplete/illegible workload (OR = 2.4

= 0.006). 

Ulanimo 2007102

Process Factors:

Perceived causes of MAEs Human Factors:

Distractions

Crosssectional study 

Survey on perceived causes of medication errors and percentage of all medication errors that are reported to the nurse manager, completing an incident report. 

25 nurses (44% response rate) in a VA hospital in Northern California 

None The most frequent p

medication errors focheck patient name administration recoexhausted (33.3%)(29.2%); confusion drugs (29.2%); distrinfusion devices bemedication labelingwrong infusion devi(24%). 

Whitman 200297 System Factors: Nurse staffing Prospective cohort study Secondary data analysis of a 

prospective, observational cohort study 

95 patient care units in 10 adult acute care hospitals in an integrated health care system in the eastern United States 

None Rates of medication 

associated to staffinday in cardiac ICU intermediate (r = -0

30.3% of the varianrates resulted from work hours per pati
37

Sourc

e 

Safety Issue Related to Clinical Practice 

Design Type 

Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(s) 

Wolf 200644 Process Factors:

Distractions Human Factors:

Knowledge deficit Inexperience 

Retrospective cohort study 

Analysis of MAEs reported January 1, 1999, to December 21, 2003, by nursing students during the administration phase 

MAEs reported by 1,305 nursing students in the USP MEDMARX® program; 763 reports included contributing factors. 

None The major contribut

inexperienced staff (20%). The other, significawere insufficient stastaffing, lack of accemergency situationtransfer, floating staand code situation. The major causes operformance (humaprocedure/protocol knowledge deficit (2
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

Strategies To Improve Medication Administration Safety

Strategies to improve medication safety focused on acute care settings. Twenty-six studies 

and descriptions of quality improvement projects were identified. Strategies used included 

recommendations from a nationwide voluntary organization to improve safety, education of 

nurses and other providers in safe practices, and system change and technology. 

Nationwide voluntary efforts. Lucian Leape and colleagues116 reported on a 15-month 

Institute for Healthcare Improvement Breakthrough Series Collaborative intended to reduce 

ADEs. Eight types of strategies were successfully used, including documentation of allergies, 

nonpunitive reporting, and standardizing medication administration times. Effective leadership 

and appropriateness of intervention were associated with successful change implementation. The 

converse was associated with failure, as were unclear aims, poorly designed interventions, lack 

of focus on underlying system failures, unclear measures, too much focus on data collection, 

involvement from only some stakeholders, opposition from physicians and nurses, and 

conflicting time demands for team members. The findings were limited by the lack of an analysis 

of the relationship between established safety policies and practices and the success of 

implementing new strategies, as well as the relationship between the implementation and the 

occurrence of ADEs. 

A survey of 148 hospitals about the characteristics and barriers associated with adoption of 

the National Quality Forums’ 30 safe practices was done by Rask and colleagues.117 These 

practices included unit dosing, adopting computerized physician order entry (CPOE), and having 

a culture of safety. Of the recommended practices, there was high adoption of standardized 

labeling and storage of medications (90.5 percent), identification of high-alert medications (81 

percent), and use of unit doses (81 percent). For-profit hospitals were more likely than not-forprofit hospitals to have unit-dose medication distribution systems (93.1 percent vs. 78.2 percent) 

and policies on reading back verbal orders (83.1 percent vs. 58.4 percent). There were greater 

distractions affecting medication administration in large hospitals. Hospitals with 100–299 beds 

were more likely to report using pharmacists to review and approve nonemergency orders prior 

to dispensing; and, 69.4 percent of all hospitals used data analysis to drive patient safety quality 

improvement efforts. 

Nurses’ education and training. Educational strategies aimed to improve medication safety 

and avert unnecessary medication errors. One randomized controlled study used an interactive 

CD-ROM education program to improve the use of safe medication practices and decrease the 

rate of MAEs.118 Direct observation of medication administration was used to assess the impact. 

After the training, nurses’ use of safe administration practices increased, but preparation errors 

did not decrease. There were too few actual medication errors to analyze pre-post differences. 

Another approach used an 11 module Web-based educational strategy to improve drug safety 

with a small sample of nurses.119 Direct observation of medication administration was used to 

determine the outcome. After using these modules, rates of nonintravenous MAEs decreased 

from 6.1 percent to 4.1 percent. Rates of errors in intravenous drug administration did not decline 

as expected. Dennison120 reported the results of a medication safety training program for nurses. 

Knowledge scores improved in this pre-post test study, but there was no significant change in 

safety climate scores, labeling of intravenous infusion setups, or the number of self-reported 

errors. 

Attempts to improve basic and continuing education in medication safety have been reported, 

but they have not assessed the impact on actual error rates. In a small pilot study, a problem38 
Medication Administration Safety

based learning approach was found to enable students to use findings from topic-specific 

research to develop and apply solutions for clinical problems. Papastrat and Wallace121 proposed 

using problem-based learning and a systems approach to teach students how to prevent 

medication errors and suggested content, but their approach was not compared to other teaching 

methods. Another proposed educational strategy for practicing nurses was to use simulation of 

medication administration and errors in a controlled setting to improve medication safety, 

“duplicate the complexity of the nurse-patient interaction and related cognitive 

thought”122 (p. 249). Simulations could be used to prepare nurses to recognize and manage 

medication errors when and if they occur. 

System change. Several attempts to change the system have been tested. Some of the 

strategies addressed the thoroughness of error reporting, some the processes and events 

surrounding medication administration, and some focused directly on reducing errors. Using a 

hospitalwide performance improvement project that emphasized system factors, not individual 

blame, error reporting increased from a rate of 14.3 percent to 72.5 percent.123 To address 

intravenous infusion problems, a medication safety education program and medication 

calculation worksheets were introduced, followed by ongoing Plan-Do-Study-Act cycles.124

Multiple system changes were also used to improve safety of intravenous drug infusion. These 

included removing 90 to 95 percent of potassium chloride ampoules from the bedside; 

developing preprinted labels for five common drug infusions; removing four-channel infusion 

pumps the unit and replacing them with double-channel infusion pumps with a simple interface 

design; standardizing administration of drugs given by bolus dose using a syringe pump; 

decreasing missed doses of immunosupression drugs for transplant patients from 25 percent to 9 

percent by incorporating them into the main drug chart; implementing standardized prefilter and 

heparin-lock central venous catheters and heparin infusions into ICU protocol; redesigning drug 

infusion administration practices throughout the hospital; eliminating burettes for IV drug 

infusion; preparing standardized drug infusions for 36 drugs; and providing Intranet-based up-todate drug information. 

A time study and focus groups were used to compare nurse efficiency during medication 

administration using either medication carts with unit doses or a locked wall-mounted cupboard 

in each patient room.125 After 12 weeks, the wall-mounted units were found to have decreased 

medication administration time for nurses an average 23 minutes per 12-hour shift. Time saved 

by not having to search for missing medications saved 0.38 full-time equivalent (FTE) annually. 

Pharmacists spent an additional 0.05 FTE in stocking room cupboards. Nurses reported more 

contact time with patients when using room cupboards and fewer interruptions by colleagues 

during medication preparation and administration. Two small experimental studies attempted to 

reduce distractions that frequently interrupt nurses during medication administration and thereby 

introduce the potential for error.126, 127 In both studies a standardized protocol for safe 

administration of medications was introduced to the nursing staff in the experimental group and 

signage was used to remind others (physicians, patients, other staff) to not interrupt. The signage 

in the first study was a vest that the nurse administering medication wore; in the second it was a 

sign above the preparation area. Direct observation of the number and types of distractions 

provided the outcome measures in the first study; a questionnaire completed by each nurse 

administering medications provided the measure of distractions for the second. In both studies, 

the number of distractions was significantly reduced. Medication error rates were not captured. 

One randomized controlled trial compared the use of a dedicated nurse for medication 

administration to nurses providing comprehensive care, including administering medications, to 

39 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

their patients in two hospitals.128 MAEs were then assessed using direct observation. The 

investigators found the error rates to be 15.7 percent at the intervention hospital and 14.9 percent 

in the control hospital. The rate of MAEs was not significantly different between control and 

experimental groups. 

Involving patients in the administration of medications while in the hospital is another 

system strategy that has been assessed. With this intervention, hospitalized patients have the 

responsibility for administering their own medication under the supervision of nursing staff. A 

literature review reported on 12 studies that described and evaluated a patient self-administration 

program.129 This review found that the patients’ knowledge about their medications and the 

prescribed dosing increased, but knowledge about the potential side effects of their medications 

did not. Given the body of the reviewed literature, it appeared as though patients and families 

make as many or more MAEs than do health care providers. 

System change with technology. Another rapid-cycle implementation project over 6 months 

used continuous quality improvement data before and after implementing a modular, 

computerized, integrated infusion system.130 Most infusion error warnings occurred between 3 

p.m. and 9 p.m., peaking at 6 p.m. Nurses responded to 12 percent of the infusion error warnings 

by altering the setting and averting errors. The nature of the 88 percent of warnings not 

responded to was not discussed. Risk scores associated with heparin infusion rates decreased 

almost fourfold. Almost all nurses used the new software correctly. 

Two studies focused on documentation of medication administration. One study introduced a 

charting system with decision support and used a quasi-experimental design to determine the 

effects.131 Researchers collected medication charting data for 8 weeks in both the control and 

study units. Staff in the study unit received an educational intervention about error avoidance 

through real-time bedside charting, followed by 12 weeks of monitoring and performance 

feedback. After the 12 weeks, medication charting rates increased from 59 percent to 72 percent 

in the intervention group. The second study used a computer-based “unreported meds followup” 

to remind nurse staff about scheduled medications omitted or not documented.132 After charts 

were prospectively reviewed, a mandatory medication error prevention seminar was given to 

nurses, and a medication review report was created for nurses. Reported medication errors and 

documentation of medication administration were reviewed, medication administration policies 

were developed, and focus changed to the potential causes of errors. Documentation errors 

decreased over the 3 years of the study, and reported error rates increased by 0.5 percent each 

year. 

Bar-coded medication administration (BCMA) is promoted as the most effective way to 

reduce administration errors and is being implemented widely. Conceptually this technology 

should catch nearly all errors, but rigorous evaluation of the impact of technology on error rates 

has lagged behind implementation. The biggest challenge to determining the effectiveness of 

BCMA or other interventions is the lack of valid measures of MAEs. Data from voluntary selfreported medication errors are known to capture only a small portion (5 percent to 50 percent) of 

actual errors, and the BCMA system itself greatly alters nurses’ awareness of errors, thereby 

systematically affecting reported error rates. Many studies reporting analysis of the impact of 

BCMA have used data collected by the system only after implementation.133–136 From these we 

learn the types of errors intercepted by the system. Three other studies of the impact of BCMA 

on administration errors reported very large reductions: 59–70 percent decrease,137 71 percent 

and 79 percent drops.138 However, the sources of the data for determining these decreases are not 

known. 

40 
Medication Administration Safety

41 

Direct observation of medication administration, a resource- and time-intensive approach to 

data collection, is the only way to gather unbiased data to evaluate the impact of BCMA on 

medication administration errors. Three studies have used direct observation; however, each 

evaluated the implementation of a different set of technology. Franklin and colleagues139

reported a decline in MAE rates from 8.6 percent to 4.4 percent when a new system was 

implemented in a teaching hospital in England. The system included BCMA, computerized order 

entry, automated dispensing, and electronic medication administration record. Prescription errors 

also declined from 3.8 to 2 percent. It is noteworthy that the rate of both administration and 

prescribing errors by direct observation was much lower than other direct observation studies 

have reported. Paoletti and colleagues140 used direct observation to determine the impact of 

BCMA and an electronic medication record in a hospital in the United States. They reported that 

the rate of MAEs declined from 13.5 percent to 3 percent. Finally, the implementation of only 

the electronic medication administration record led to a decline in MAEs from 10.5 percent to 

6.1 percent using direct observation.141 Health-related technology designed to increase 

medication safety has great promise, but more study using valid outcome measures and 

controlled interventions needs to be done to demonstrate the potential benefits. 
Evidence Table 3. Strategies To Reduce Medication Administration Errors 

Source Safety Issue Related to Clinical Practice Design Type Study Design & Study Outcome Measure(s) Study Setting & Study Population Study Intervention Key Finding(Anderson 2004137 Bar-coded technology Quality improvement project One hospital Bar-coded point-of-care medication administration 59%–70% red

Positive effec

Bennett 2006125 Dispensing mechanisms to improve medication administration Quality improvement project Time study and focus groups to compare nurse efficiency using medication carts or a unit dose to locked wall- mounted cupboards in each patient room Nurses in 2 units and pharmacists in one hospital Wall-mounted cupboards in patient rooms Wall-mounted 

medication adnurses an avehour shift. Time saved nmedications sPharmacist spFTE in stockinNurses reportpatients when Nurses reportduring medicaadministration

42
43

Source Safety Issue 

Related to Clinical Practice 

Design Type Study Design & 

Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(

Burdeu 2006124 Improving safety of 

intravenous medication administration 

Quality improvement project 

Plan, do, study, act (PSDA) cycle was used to assess deviations in safe practice of drug infusions, using regular audits by ICU nursing management. 

Began with 1 25-bed ICU, then applied lessons learned throughout one acute care teaching hospital in Melbourne, Australia 

Provided a medication safety education program and medication calculation worksheets, followed by ongoing PDSA cycles. 

Improved drupractices. 90 to 95% of ampoules webedside. Preprinted labthe 5 drug infused. 4-channel infuremoved from double-channsimple interfaStandardized given by bolupump. Decreased mimmunosuprepatients from incorporating chart. Implemented heparin-lock cEliminated buStandardized 36 drugs and up-to-date dru

Coyle 2005133 BCMA Quality 

improvement project 

Assessed process 161 medical 

centers in the Veterans Health System 

Systemwide change to BCMA and electronic documentation 

Acceptance odecrease” in edecrease not 
44

Source Safety Issue Related to Clinical Practice Design Type Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(

Dennison 2007120 Medication safety 

education program 

Pre-post test Evaluation study of education program 

Technologyenhanced education program 

One coronary care unit in one hospital 

Two computerbased education modules on medication error reduction and intravenous infusion of high-alert meds. 

Nurses knowlto post-test. Safety climate Labeling of inNumber of rechange. 

Fields 2005130 Improving safety of 

intravenous medication administration 

Quality improvement project 

Rapid-cycle implementation over 6 months, using continuous quality improvement data before and after implementation 

100 new systems in 1 hospital in Georgia 

Implemented a modular, computerized, integrated infusion system 

Most infusion between 3 p.mat 6 p.m. 12% changes in puRisk score asinfusion rates fourfold. Almost all nursoftware corre

Force 2006123 Medication error 

reporting 

Quality improvement project 

Used focus groups to gather information on the medication process and process failures to improve error and near-error reporting by pharmacists and nurses 

1 hospital in Illinois 

Implemented a hospitalwide performance improvement project, emphasizing identifying system factors, not individual blame. 

After 1 year oreporting incr14.3% to 72.5
45

Source Safety Issue 

Related to Clinical Practice 

Design Type Study Design & 

Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(

Franklin 2006119 Drug safety 

education Types of MAEs 

Pretest and post-test study 

Conducted a drug safety program for nurses and assessed possible improvements in drug safety. Medication administration processes were observed before and after the program. 

19 nurses in one hospital ward (63% completed all educational modules). 

Web-based drug safety program with 11 modules 

The most comomission, wrofast intravenoRates of nonidecreased froWhile nurses program and nonintravenouimplementatiodifference in timplementatioprogram. 

Franklin 2007139 Health technology 

implementation 

Before-andafter study Reviewed records for prescribing 

errors, direct observation of nurse med administration 

Surgical ward in one hospital in UK 

CPOE, BCMA, automated dispensing, electronic medication administration record 

MAEs declinePrescribing e2%. Ward phaprescription titime on medic

Greengold 2003128

Medication administration nurses 

Randomized controlled trial 

Compared using a dedicated nurse for medication administration to nurses administering medications to their patients 

2 hospitals Using a 

dedicated nurse for medication administration 

Generally, thedifferences in types of intervlower in surgimixed medicaused dedicateadministers. 

Larrabee 2003136 BCMA Quality 

improvement 

Descriptive—process and experiences 

1 hospital BCMA Occurrence re

of systems dafound prevaledose, and wroomitted and mcaptured. 
46

Source Safety Issue Related to Clinical Practice Design Type Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(

Leape 2000116 Interventions for 

reducing adverse drug events 

Quality improvement 

15-month period of rapid-cycle changes. 

36 hospitals participating in an Institute for Healthcare Improvement (IHI) collaborative on reducing adverse drug events. 

Education on IHI’s method for rapid-cycle change and evaluation 

Successful chnonpunitive represcribing to handwriting atrailing zeros; removal of cochloride from documentatiostandardized time; standardchemotherapyinsulin-orderinremoving conchloride from successful, annonpunitive reordering protosuccessful (50respectively). Success of chassociated wicollaborative effective procchoice of inteFailure was aleadership suleadership; undesigned inteunderlying symeasures; too collection; invstakeholders; physicians antime demands 
47

Source Safety Issue 

Related to Clinical Practice 

Design Type Study Design & 

Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(

Mahoney 2007134 Integrated clinical 

information technology 

Quality improvement—measures only after implementation 

Examined medication errors, turnaround time, decision-support overrides. 

Multihospital system 

Included CPOE, electronic record, BCMA, decision support, and drug dispensing 

System decreincreased phaimproved mon73 administra100,000 doseimplementatio

Meadows 2002138 BCMA Review of 

BCMA system and effects 

Relates briefly the results of two system interventions 

2 hospitals BCMA The two hosp

medication erData used to described. 

Nelson 2005131 Decision support to 

improve medication administration 

Pretest and post-test 

Collected medication charting data for 8 weeks in both the control and study units. Staff in the study unit received an educational intervention about error avoidance through real-time bedside charting, 12 weeks of monitoring, and performance feedback. 

Two 40-bed surgical units in one hospital in Utah 

Educational intervention followed up with real-time feedback on documentation. 

Medication ch59% to 72% i

Paoletti 2007140 BCMA and 

electronic medication administration record (MAR) 

Evaluation study—before and after 

Used direct observation to determine MAEs. 

3 units in one hospital: 1 control, 2 intervention 

BCMA and electronic MAR 

Accuracy rate after. 
48

Source Safety Issue Related to Clinical Practice Design Type Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(

Paparella 2004122 Educational 

interventions 

Quality improvement 

Medication safety education, using the NLN Medication Proficiency examination, a medication calculation test, an ongoing continuing educational program on medication safety, and tested medication administration safety simulation models to supplement education. 

235-bed community hospital in Pennsylvania 

Required medication safety education and calculation testing of all new RNs and LPNs, ongoing medication safety education for current staff, using simulation models “What’s Wrong With This Patient.” 

The educationnurses was ua preceptor dadministrationThe simulationursing staff imedication ad

Papastrat 2003121 Educational 

interventions 

Changing practice project 

Pilot testing of problem-based learning and systems analysis methods for medication administration to undergraduate nurses. 

First-semester baccalaureate nursing students at Thomas Jefferson University 

New teaching method 

Problem-basestudents to usspecific reseafor clinical proStudents appsettings. 

Pape 2003126 Reducing 

distractions during medication administration 

Quasiexperiment Three groups: one control, one used 

protocol, one used protocol and signage. Outcomes measured by observing medication rounds for distractions. 

One medical/surgical unit in one hospital, 24 nurses 

Protocol for safe medication administration. Signage—nurse administering medications wore vest asking others not to interrupt. 

Distractions wsignificantly legroups, particgroup using b
49

Source Safety Issue 

Related to Clinical Practice 

Design Type Study Design & 

Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(

Pape 2005127 Reducing 

distractions during medication administration 

Process Improvement 

Interventions introduced after observation of distractions. Measured distractions with self-report tool. 

5 units in one hospital, 20 nurses 

Protocol and checklist for safe medication administration introduced to all nurses. Signage “STOP do not disturb” placed above med prep area. 

Self-report of and after signdecline in distnurses, other conversation, 

Rask 2007117 Medication safety 

practices 

Crosssectional study Survey of hospitals about adoption of 

National Quality Forum’s safe practices and culture of safety 

148 hospitals in the United States 

None There was hig

standardized medications (high-alert medof unit doses For-profit hosthan not-for-pdose medicat(93.1% vs. 78reading back 58.4%). There were gaffecting medlarge hospitalHospitals havmore likely to to review and orders prior to 69.4% of hosdrive patient sefforts. 
50

Source Safety Issue Related to Clinical Practice Design Type Study Design & Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(

Sakowski 2005135 BCMA system Evaluation 

study 

Effect of implementing BCMA using a retrospective audit of warning and error reports generated by the BCMA system 

6 hospitals in a multihospital system. 

BCMA Of 7,120 alert

actionable waoverrode 78%preventable elabeled as poMost common doses, wrong order, doses a

Schaubhut2000132 Expanding error 

reporting system 

Concurrent chart 

review process 

Quality improvement 

Reviewed reported medication errors, documentation of medication administration, identified need for medication administration policies, and focus on potential causes of errors 

1 hospital in a suburb of New Orleans, LA 

A computerbased “unreported meds followup” was created to remind nursing staff about scheduled medications omitted or not documented. Charts were prospectively reviewed, a mandatory medication error prevention seminar was given to nurses, and a medication review report was created for nurses. 

Reported erroeach year oveDocumentatiotime. 
51

Sourc

e Safety Issue 

Related to Clinical Practice 

Design Type Study Design & 

Study Outcome Measure(s) 

Study Setting & Study Population 

Study Intervention 

Key Finding(

Schneider2006118 Educational 

interventions 

Randomized controlled trial 

Nurses were randomly assigned to use an interactive educational tool on medication administration. Direct observation of medication administration before and after the educational tool. 

30 nurses (10 at each site) with at least 1 year experience, working fulltime for at least 6 months, at 3 community hospitals in the Midwest within a large nonprofit health system 

Interactive medication administration program 

Errors in admdecreased at level, errors in slightly, and tdrug events to 

van GijsselWiersma 2005141 Computerized medication charts Before-after study Compared prescription errors 

by review and administration errors by direct observation before and after 

1 internal medicine unit 

Computerized medication chart, updated daily, compared to handwritten 5-day medication record 

Prescribing eomitted name errors decrea

Wright 2006129 Inpatient selfadministration Literature review 12 studies that measured patient 

compliance with self-administration programs (SAPs) 

Retrieved 455 citations that involved patient SAPs, predominately in hospitals. 

None Even though 

structure and reported that their drug regand dosing freimproved, but of possible sidmedications d
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

Evidence-Based Practice Implications 

Medication safety is a significant issue in hospitals and throughout health care. Great 

improvements are needed, and hospitals are engaged in many efforts to reduce errors and 

increase this aspect of patient safety. Unfortunately, there is little evidence on which to base 

interventions. Based on the research literature, we can have confidence in only two aspects of 

our knowledge. First, data from voluntary self-reports of medication errors is neither reliable nor 

valid. Yet, this is the evidence most available for evaluating quality improvement. Interventions 

to improve the quality of voluntary self-report data include changing the culture to focus on 

system issues rather than individual deficiencies and having explicit and visible quality 

management system responses to these data. Staff who do not fear the response to an error report 

and see that the reports are used to improve quality are much more likely to take the time to 

report. 

The second area about which there is some consensus in the literature is the rate and types of 

medication administration errors that commonly occur. Using the more reliable and valid data 

from direct observation studies, we see that the proportion of doses in error is between 20 and 27 

percent counting wrong-time errors and between 7 and 18 percent without the wrong-time errors. 

MAEs are most likely to be wrong time, omissions, and wrong dose (wrong or extra dose). 

Because the nurse is often the last health care provider in the medication-use process, no one, 

except the patient, is in a position to intercept those errors. Given the number of medication 

doses administered each day in U.S. hospitals, the probable number of errors is truly staggering. 

If hospital patients get 10 doses of medication each day, at least 1 and possibly 3 of those will be 

wrong. 

While the research base for practice interventions is growing, it is still weak for most of the 

strategies currently recommended to improve medication safety. System-focused strategies 

include increasing nurse staffing levels, otherwise decreasing workloads, improving the safety 

climate, and instituting policy and procedures such as RN independent double-checks. There are 

few research studies describing nurses’ perceptions of the impact of these system features and 

even fewer assessing the actual impact, and none that have implemented and rigorously 

evaluated the effects of system strategies. Instituting new technological systems is most highly 

recommended. Given the emphasis, there have been surprisingly few studies actually assessing 

the impact on error rates of bar-coded medication administration and other medication safety 

technologies. 

Process-focused factors include minimizing distractions and interruptions during medication 

administration, using equipment correctly, and assessing and monitoring the patients’ responses 

to the medications. Again, a few small, single-site studies have assessed the effects of 

implementing protocols addressing these issues; but overall, the evidence is weak. 

The human factors of knowledge and skills (e.g., mathematical) have been studied for 

decades, and changes in basic education and nurses’ orientation and continuing education have 

been instituted. Studies linking these strategies to outcomes such as the rate of medication errors 

have not been completed. The impact of fatigue on MAEs is currently of great interest. But with 

only one descriptive study available and no interventions tested, it is difficult to know how to 

approach this issue. 

Based on this review of the literature, it is clear that medication errors are an immense 

problem. When implementing interventions to improve medication safety, use the most reliable 

52 
Medication Administration Safety

and valid data available, and share the results through publications to make the knowledge 

available to all. 

Research Implications 

The implications for research follow directly on the discussion of practice implications. 

Research in this area is constrained by the need to carry out these projects “in the field.” 

Secondary analysis of existing data sets cannot be used for most of the pertinent questions in this 

area. Laboratory studies are equally impossible. The situations at the heart of medication safety 

are complex, multifaceted, and multidisciplinary; knowledge about them must be produced with 

studies conducted within that complex environment. This requires health care institutions to 

simultaneously attempt to implement changes that will reduce the problem and evaluate the 

impact. Essentially, this is quality improvement (QI) work. 

The question is, should the results of QI projects be considered evidence and used as part of 

the knowledge foundation for future evidence-based practice projects?142 QI is a set of activities 

intended to improve some aspect of health care processes,143 a dynamic and changing package of 

interventions,144 and identification of ways to implement effective change.145 For the most part, 

definitions of QI do not include assessing the effectiveness of these activities or producing 

knowledge. And yet, reports of QI projects are increasingly used as evidence for practice and 

organizational change. 

Health care institutions are responding to the crisis in quality and safety with frenetic 

activities designed to bring about improvement. They desperately want evidence that will assist 

them in knowing which of these activities to focus on. Massive amounts of money are being 

invested in organizational changes to improve quality and safety with mostly expert advice and 

hunches to go on. There is little doubt that these projects are well intentioned; many of them 

suggest changes that are intuitive or reflect common sense. To move beyond the current state of 

multiple projects targeting similar changes, the industry needs evidence of the effects of specific 

changes: the direct and indirect effects, the intended and unintended effects, and the cost 

effectiveness. 

By their nature, QI efforts are local, attempt to minimize disruption to the organization, and 

try to constrain costs of implementation. To justify the organization’s investment in the project, 

there is a desire to show that the project had the intended effect. Further, the directors of the 

project often want to capitalize on the QI activities by reporting the results publicly, preferably 

through respected journals or presentations at professional meetings. As a result of these multiple 

goals, the project usually has only low-cost, superficial evaluation efforts that are then reported 

as evidence with an emphasis on outcomes supporting the intervention and omission of those that 

did not. Many current QI studies have significant bias and can cause harm by disseminating 

results that lead health care institutions to invest in activities that may not improve quality, while 

ignoring others that could.146 But, there is no consensus on standards that can be applied to 

improve this situation. As Mosser and Kane147 asked recently, What level of proof should we 

require to conclude that improvement has been achieved? What level of proof is there that the 

intervention was the cause of improvement? 

The problem of bias inherent in local efforts to improve quality is crucial. When 

organizations make decisions to invest large amounts of money in a QI project, there is 

understandable reluctance to hear, let alone share, results that show no systematic effects on the 

outcomes of care. Yet, to produce the science required for future QI efforts, reports of activities 

53 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

that were ineffective and those that resulted in unintended and disruptive side effects must also 

be shared with others. Most QI activities cannot be tested with rigorous and controlled research, 

and we therefore need to develop a QI science to enhance the internal and external validity of the 

results. We cannot accept poorly conducted studies of efforts to improve quality and safety—it is 

too crucial to the future of health care. At the same time, we must recognize that the complexity 

of projects taking place in the real world cannot be simplified and that analytic methods must 

substitute for experimental controls in this work.148 Both the practitioners’ distrust of research 

and its accompanying statistics and the researchers’ disdain of the messiness of QI activities 

must be tempered with a better understanding. 

Despite concerns about the rigor of QI, it is crucial that these activities be reported to 

promote learning about implementation methods that worked and those that did not, and the 

types of projects that produced desired results and those that did not. To maximize learning, 

these reports must be thorough and include both the intended and unintended outcomes, 

descriptions of the intervention and implementation must be candid, the robustness of the 

measures must be clear, and the description of the organizational context must be adequate. 

Recent guidelines for the publication of QI projects may assist in achieving this thoroughness 

and transparency.149 Collaboration between the principals involved in the QI project and health 

systems researchers would maximize the potential for producing evidence from these field 

studies. It is unlikely that science will ever develop methods to study implementation and 

evaluation of QI projects in their natural setting with a level of rigor similar to experiments or 

clinical trials, and that makes the results of QI projects even more valuable. It is crucial that we 

learn which QI activities work in which settings and which outcomes can most likely be 

improved with organizational changes. 

The specific issues most in need of research (QI activities) at this time are as follows: 

• Bar-coding and other medication safety technology—widely recommended but little or 

no valid research using before-and-after designs. 

• Independent RN double-checks—logical and widely recommended, but no research has 

been done describing, let alone testing, the effects of this policy. 

• Relationship between nurse staffing and medication errors—a few descriptive studies and 

studies asking RN perceptions of the problem suggest that staffing and workload are 

major factors, but there are no research studies using valid and reliable data. 

• Techniques to reduce distractions, interruptions, other risk factors for medication error 

need to be tested. 

• Methods of effective education in medication safety for nurses and all providers. 

• Effectiveness of implementing new checklists, policies, and procedures. 

• Understanding work-arounds. 

• Methods and techniques for successful implementation of system and process change. 

Despite the national emphasis on patient safety and quality care, very little is known about 

effective medication safety strategies for nurses. The recent IOM report on medication safety 2

identified several areas needing future research, including the following: 

• What are the most effective mechanisms to improve communication between patients and 

clinicians regarding the safe use of medications? 

• What are the most effective mechanisms to improve patient education about the safe use 

of medications? 

• Which self-management support strategies are effective in improving patient outcomes? 

54 
Medication Administration Safety

• How can information about specific medications be effectively used by patients? What is 

the impact of that information on patients’ adherence and communication with clinicians? 

• How can patient-centered approaches to medication safety decrease errors associated 

with medications and improve patient outcomes? 

• How can medication-related competencies become a core competency among the current 

workforce? 

• What is the impact of free samples on patient adherence and health outcomes? 

Conclusion 

There is a large and growing body of research addressing medication safety in health care. 

This literature covers the extent of the problem of medication errors and adverse drug events, the 

phases of the medication-use process vulnerable to error, and the threats all of this poses for 

patients. As this body of literature is evaluated, the fact that there are crucial areas about which 

we know little becomes apparent. Nurses are most involved at the medication administration 

phase, although they provide a vital function in detecting and preventing errors that occurred in 

the prescribing, transcribing, and dispensing stages. Administration errors comprise a significant 

proportion of all errors and yet, beyond that fact, there isn’t much known about the causes or 

about the effectiveness of proposed solutions. Research addressing the complex process of 

medication use in hospitals is badly needed and requires a new approach to produce valid 

knowledge from studies done in the field with few controls of confounding factors. 

Search Strategy 

A search of the literature was conducted using PubMed® and CINAL®. The key words 

employed in the search included “adverse drug events,” “drug administration,” “medication 

administration,” “medication administration errors,” “medication error reporting,” “medication 

safety,” “nursing,” “patient safety,” and “work(ing) conditions.” This resulted in 1,400 abstracts, 

which were narrowed as follows. Literature that addressed topics covered in this book on health 

information technology, specifically computerized provider order entry with clinical decisionsupport systems (for nurses and/or physicians) and bar-code medication administration systems, 

children, and medication reconciliation were excluded from this review, as were studies with 

only physicians and pharmacists as study subjects, those in home health care settings, and those 

related only to prescribing medications or patient compliance. Additional exclusion criteria 

included research not differentiating the nursing role in medication administration, 

administration of medications to reverse adverse drug reactions (e.g., naloxone for opioid 

overdose), prescribing and dispensing process of medications, and unique specifications 

regarding specific medications. Reviewed articles were searched for references that we did not 

already have, and PubMed® links were checked as additional articles were found. The final 

review also excluded editorials, newsletters, single-case studies, medication safety outside 

institutional settings (if dealing with patient self-management or adherence), and studies with 

critically flawed methodology and inadequate reporting. The literature was then also limited to 

reports written in English and research published in 1997 or later. A total of 70 articles were 

identified as having met the inclusion criteria as evidence and were discussed in this chapter. 

55 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

Author Information 

Ronda G. Hughes, Ph.D., M.H.S., R.N., senior health scientist administrator, Agency for 

Healthcare Research and Quality. E-mail: ronda.hughes@ahrq.hhs.gov. 

Mary A. Blegen, Ph.D., R.N., F.A.A.N., professor in community health system and director 

of the Center for Patient Safety, School of Nursing, University of California, San Francisco. 

E-mail: mary.blegen@nursing.ucsf.edu. 

References 

1. Institute of Medicine. To err is human: building a 

safer health system. Washington, DC: National 

Academy Press, 1999. 

2. Institute of Medicine. Preventing medication errors. 

Washington, DC: National Academy Press, 2007. 

3. Food and Drug Administration, Center for Drug 

Evaluation and Research. Drugs@FDA glossary of 

terms. 2007. Available at: 

www.fda.gov/Cder/drugsatfda/glossary.htm#M. 

4. National Coordinating Council for Medication Error 

Reporting and Prevention. What is a medication 

error? www.nccmerp.org/aboutMedErrors.html. 

Accessed October 1, 2007. 

5. Wu AW, Pronovost P, Morlock L. ICU incident 

reporting systems. J Crit Care 2006;17(2):86-94. 

6. Duthie E, Favreau B, Ruperto A, et al. Quantitative 

and qualitative analysis of medication errors: the 

New York experience. In: Advances in patient safety: 

from research to implementation, Vol. 3. Rockville, 

MD: Agency for Healthcare Research and Quality. 

February 2005. AHRQ Publication No. 05-0021. 

7. Phillips J, Beam S, Brinker A, et al. Retrospective 

analysis of mortalities associated with medication 

errors. Am J Health Syst Pharm 2001;58:1835-41. 

8. Leape LL. Preventing adverse drug events. Am J 

Health Syst Pharm 1995;52:379-82. 

9. ASHP. ASHP guidelines on adverse drug reaction 

monitoring and reporting. Am J Health Syst Pharm 

1995;52:417-9. 

10. Joint Commission. Sentinel event glossary of terms. 

2007. www.jointcommission.org/SentinelEvents/ 

se_glossary.htm. 

11. Aspinall MB, Whittle J, Aspinall SL, et al. Improving 

adverse-drug-reaction reporting in ambulatory care 

clinics at a Veterans Affairs hospital. Am J Health 

Syst Pharm 2002 May 1;59(9):841-5. 

12. Bates DW, Cullen DJ, Laird N, et al. Incidence of 

adverse drug events and potential adverse drug 

events: implications for prevention. JAMA 

1995;274:29-34. 

13. Murphy S, Roberts R. “Black box” 101: how the 

Food and Drug Administration evaluates, 

communicates, and manages drug benefit/risk. J 

Allergy Clin Immunol 2006;117:34-9. 

14. Szefler SJ, Whelan GJ, Leung DY. “Black box” 

warning: wake-up call or overreaction? J Allergy 

Clin Immunol 2006;117:26-9. 

15. Generali J. Black box warnings: drugs with black box 

warnings—comprehensive list. 2007. Available at: 

www.formularyproductions.com/master/showpage.ph

p?dir=blackbox&whichpage=9. Accessed March 31, 

2008.

16. Wagner AK, Chan KA, Dashevsky I, et al. FDA drug 

prescribing warnings: is the black box half empty or 

half full? Pharmacoepidemiol Drug Saf 2006 

Jun;15(6):369-86. 

17. Cohen M. Patient safety alert: “high-alert” 

medications and patient safety. Int J Qual Health 

Care 2001;13:339-40. 

18. Leape LL, Brennan TA, Laird N, et al. The nature of 

adverse events in hospitalized patients. Results of the 

Harvard Medical Practice Study II. N Engl J Med 

1991;324:377-84. 

19. Brennan TA, Leape LL, Laird NM, et al. Incidence of 

adverse events and negligence in hospitalized 

patients. Results of the Harvard Medical Practice 

Study I. N Engl J Med 1991;324:370-6. 

56 
Medication Administration Safety

20. Bates DW. Medication errors—how common are 

they and what can be done to prevent them? Drug Saf 

1996;15:303-10. 

21. Bates DW, Boyle DL, Vander Vliet MB, et al. 

Relationship between medication errors and adverse 

drug events. J Gen Intern Med 1995;10:199-205. 

22. Cowley E. Assessing and preventing medication 

errors in home care. Home Health Care Consultant 

2000;7(3):33-40. 

23. Kaushal R, Bates DW, Landrigan C, et al. 

Medication errors and adverse drug events in 

pediatric inpatients. JAMA 2001;285:2114-20. 

24. Buckley MS, Erstad BL, Kopp BJ, et al. Direct 

observation approach for detecting medication errors 

and adverse drug events in a pediatric intensive care 

unit. Pediatr Crit Care Med 2007;8(2):145-52. 

25. Schneider MP, Cotting J, Pannatier A. Evaluation of 

nurses’ errors associated in the preparation and 

administration of medication in a pediatric intensive 

care unit. Pharm World Sci 1998;20:178-82. 

26. Classen DC, Pestotnik SL, Evans RS, et al. Adverse 

drug events in hospitalized patients: excess length of 

stay, extra costs, and attributable mortality. JAMA 

1997;277(4):301-6. 

27. Leape LL, Bates DW, Cullen DJ, et al. Systems 

analysis of adverse drug events. JAMA 1995;274:35-

43. 

28. Pepper G. Errors in drug administration by nurses. 

Am J Health Syst Pharm 1995;52:390-5. 

29. Kaushal R, Bates D. Computerized physician order 

entry (CPOE) and clinical decision support systems 

(CDSSs). In: Shojania K, Duncan B, McDonald K, et 

al., eds. Making health care safer: a critical analysis 

of patient safety practices. Rockville, MD: AHRQ; 

2001. p. 59-69. 

30. O’Shea E. Factors contributing to medication errors: 

a literature review. J Clin Nurs 1999;8:496-504. 

31. Dean B, Schachter M, Vincent C, et al. Causes of 

prescribing errors in hospital inpatients: a prospective 

study. Lancet 2002;359:1373-8. 

32. Dean B, Schachter M, Vincent C, et al. Prescribing 

errors in hospital inpatients: their incidence and 

clinical significance. Qual Saf Health Care 

2002;11:340-4. 

33. Cook AF, Hoas H, Guttmannova K, et al. An error by 

any other name. Am J Nurs 2004;104(6):32-44. 

34. Raju TN, Kecskes S, Thorton JP, et al. Medication 

errors in neonatal and paediatric intensive care units. 

Lancet 1989;2:374-6. 

35. Leape LL, Cullen DJ, Clapp MD, et al. Pharmacist 

participation on physician rounds and adverse drug 

events in the intensive care unit. JAMA 

1999;282:267-70. 

36. Walsh KE, Kaushal R, Chessare JB. How to avoid 

paediatric medication errors: a user’s guide to the 

literature. Arch Dis Child 2005;90:698-702. 

37. Wirtz V, Taxis K, Barber ND. An observational 

study of intravenous medication errors in the United 

Kingdom and in Germany 2003;25(3):104-11. 

38. Hicks R, Becker S, Krenzischeck D, et al. Medication 

errors in the PACU: a secondary analysis of 

MEDMARX findings. J PeriAnesth Nurs 2004; 

19(1):18-28. 

39. Armitage G, Knapman H. Adverse events in drug 

administration: a literature review. J Nurs Manag 

2003;11:130-40. 

40. Murphy MD. Individual characteristics of nurses who 

committed medication administration errors. Cases 

which resulted in licensure discipline by the Colorado 

Board of Nursing. Issues 1992;13:11-13. 

41. Burroughs TE, Waterman AD, Gallager TH, et al. 

Patient’s concerns about medical errors during 

hospitalization. J Qual Patient Safety 2007;33:5-14. 

42. Massachusetts Nurses Association (MNA). Nurses’ 

six rights for safe medication administration. Paper 

presented at MNA Congress on Nursing Practice; 

Canton, MA. 2006. Available at: 

www.massnurses.org/nurse_practice/sixrights.htm. 

43. Grasso BC, Genest R, Jordan CW, et al. Use of chart 

and record reviews to detect medication errors in a 

state psychiatric hospital. Psychiatr Serv 

2003;54(5):677-81. 

44. Wolf ZR, Hicks R, Serembus JF. Characteristics of 

medication errors made by students during the 

administration phase: a descriptive study. J Prof Nurs 

2006;22(1):39-51. 

45. Kopp BJ, Erstad BL, Allen ME, et al. Medication 

errors and adverse drug events in an intensive care 

unit: direct observation approach for detection. Crit 

Care Med 2006;34(2):415-25. 

46. Milch CE, Salem DN, Pauker SG, et al. Voluntary 

electronic reporting of medical errors and adverse 

events. An analysis of 92,547 reports from 26 acute 

care hospitals. J Gen Intern Med 2006;21(2):165-70. 

57 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

47. Cohen MR, ed. Medication errors: causes and 

prevention. Washington, DC: American 

Pharmaceutical Association;1999. 

48. Carroll P. Medication issues: the bigger picture. RN 

2003;66(1):52-8. 

49. Institute of Medicine. Crossing the quality chasm: a 

new health system for the 21st century. Washington, 

DC: National Academy Press; 2000. 

50. Institute of Medicine. Keeping patients safe: 

transforming the work environment of nurses. 

Washing, DC: National Academy Press; 2004. 

51. Jenkins R, Elliot P. Stressors, burnout and social 

support: nurses in acute mental health settings. J Adv 

Nurs 2004;48:622-31. 

52. Benjamin DM. Reducing medication errors and 

increasing patient safety: case studies in clinical 

pharmacology. J Clin Pharmacology 2003;43:768-83. 

53. Reason J. Human error: models and management. 

BMJ 2000;320(7237):768-770. 

54. Runciman WB, Sellen A, Webb RK, et al. Errors, 

incidents and accidents in anesthetic practice. Anesth 

Intensive Care 1993;21:506-19. 

55. Cullen DJ, Bates DW, Small SD, et al. The incident 

reporting system does not detect adverse drug events: 

a problem for quality improvement. Jt Comm J Qual 

Improv 1995;21:541-8. 

56. Kritchevsky SB, Simmons BP. Continuous quality 

improvement. JAMA 1991;266:1817-23. 

57. Beckman U, Runciman WB. The role of incident 

reporting in continuous quality improvement in the 

intensive care setting. Anesth Intensive Care 

1996;24:311-13. 

58. Stratton KM, Blegen MA, Pepper C, et al. Reporting 

of medication errors by pediatric nurses. J Pediatr 

Nurs 2004;19(6):385-392. 

59. Rapala K. Mentoring staff members as patient safety 

leaders: the Clarian safe passage program. Crit Care 

Nurs Clin North Amer 2005;17:121-6. 

60. Wakefield BJ, Uden-Holman T, Wakefield DS. 

Development and validation of the medication 

administration error reporting survey. In: Advances 

in patient safety: from research to implementation, 

Vol. 4. Programs, tools, and products. Surveys (p. 

475-88). Retrieved Nov 11, 2005 from http:// 

www.ahrq.gov/qual/advances/Vol4/Wakefield2pdf. 

61. Mayo A, Duncan D. Nurse perceptions of medication 

errors: what we need to know for patient safety. J 

Nurs Care Qual 2004;19(3):209-17. 

62. Wakefield BJ, Blegen MA, Uden-Holman T, et al. 

Organizational culture, continuous quality 

improvement, and medication administration error 

reporting. Amer J Med Qual 2001;16(4):128-34. 

63. Wakefield DS, Wakefield BJ, Uden-Holman T, et al. 

Understanding why medication administration errors 

may not be reported. Am J Med Qual 1999;14(2):81-

8. 

64. Wakefield DS, Wakefield BJ, Uden-Holman T, et al. 

Perceived barriers in reporting medications 

administration errors. Best Pract Benchmarking 

Health Care 1996;1(4):191-7. 

65. Walters JA. Nurses’ perceptions of reportable 

medication errors and factors that contribute to their 

occurrence. Appl Nurs Res 1992;5(2):86-8. 

66. Wolf ZR, Serembus JF, Smetzer J, et al. Responses 

and concerns of healthcare providers to medication 

errors. Clin Nurs Spec 2000;14(6):278-89. 

67. Blegen MA, Vaughn T, Pepper GA, et al. Patient and 

staff safety: voluntary reporting. Am J Med Qual 

2004;19(2):67-74. 

68. Chiang H, Pepper GA. Barriers to nurses’ reporting 

of medication administration errors in Taiwan. 

Journal of Nursing Scholarship 2006;392-9. 

69. Karadeniz G, Cakemakci A. Nurses’ perceptions of 

medication errors. Int J Clin Pharmacol Res. 

2002;22(3-4):111-6. 

70. Osborne J, Blais K, Hayes JS. Nurses’ perceptions: 

when is it a medication error? J Nurs Adm 1999; 

29(4):33-38. 

71. Lawton R, Parker D. Barriers to incident reporting in 

a healthcare system. Qual Saf Health Care 2002; 

11(1):15-8 

72. Uribe CL, Schweikhart SB, Pathak DS, et al. 

Perceived barriers to medical-error reporting: an 

exploratory investigation. J Healthc Manag 

2002;47:263-80. 

 73. Edmondson AC. Learning from mistakes is easier 

said than done: group and organization influences on 

the detection and correction of human error. J Appl 

Behav Anal 1996;32:5-28. 

74. Bates DW, Leape LL, Petrycki S. Incidence and 

preventability of adverse drug events in hospitalized 

adults. J Gen Intern Med 1993;8:289-94. 

58 
Medication Administration Safety

75. O’Neil AC, Petersen LA, Cook EF, et al. Physician 

reporting compared with medical-record review to 

identify adverse medical events. Ann Intern Med 

1993;119:370-6. 

76. Michel P, Quenon JL, Sarasqueta AMD, et al. 

Comparison of three methods for estimating rates of 

adverse events and rates of preventable adverse 

events in acute care hospital. BMJ 2004;328:199. 

77. Flynn EA, Barker KN, Pepper GA, et al. Comparison 

of methods for detecting medication errors in 36 

hospitals and skilled-nursing facilities. Am J Health 

Syst Pharm. 2002 Mar 1;59(5):436-46. 

78. Prot S, Fontan JE, Alberti C, et al. Drug 

administration errors and their determinants in 

pediatric in-patients. Int J Qual Health Care 

2005;17(5):381-9. 

79. Olsen S, Neale G, Schwab K, et al. Hospital staff 

should use more than one method to detect adverse 

events and potential adverse events: incident 

reporting, pharmacist surveillance and local real-time 

record review may all have a place. Qual Saf Health 

Care 2007;16:40-4. 

80. Kapborg I, Svensson H. The nurse’s role in drug 

handling within municipal health and medical care. J 

Adv Nurs 1999;30(4):950-7. 

81. Beyea SC, Hicks RW, Becker, SC. Medication errors 

in the OR—a secondary analysis of MEDMARX. 

AORN Jr 2003;77(1):122-34. 

82. Beyea SC, Hicks RW, Becker, SC. Medication errors 

in the day surgery setting. Surgical Services Mgmt 

2003;9:65-76. 

83. Hicks RW, Cousins DD, Williams RL. Selected 

medication-error data from USP’s MEDMARX 

program for 2002. Am J Health Syst Pharm. 2004 

May 15;61:993-1000. 

84. Balas MC, Scott LD, Rogers AE. Frequency and type 

of errors and near errors reported by critical care 

nurses. Can J Nurs Res 2006 Jun;38(2):24-41. 

85. Balas MC, Scott LD, Rogers AE. The prevalence and 

nature of errors reported by hospital staff nurses. 

Appl Nurs Res 2004;17:224-230. 

86. McCarthy AM, Kelly MW, Reed D. Medication 

administration practices of school nurses. J School 

Health 2000;70:371-6. 

87. Barker KN, Flynn EA, Pepper GA, et al. Medication 

errors observed in 36 health care facilities. Arch 

Internal Med 2002;163:1897-903. 

88. Colen HB, Neef C, Schuring RW. Identification and 

verification of critical performance dimensions: 

phase I of the systematic process redesign of drug 

distribution. Pharm World Sci 2003;25(3):118-25. 

89. Taxis K, Barber N. Ethnographic study of incidence 

and severity of intravenous drug errors. BMJ 

2003;326(7391):684-7. 

90. Taxis K, Barber N. Incidence and severity of 

intravenous drug errors in a German hospital. Eur J. 

Clin Pharmacol 2003;59:815-7. 

91. Tissot E, Cornette C, Limat S, et al. Observational 

study of potential risk factors of medication 

administration errors. Pharm World Sci 2003 

;25(6):264-8. 

92. Handler SM, Nace DA, Studenski SA, et al. 

Medication error reporting in long-term care. Am J 

Geriatr Pharmacother 2004;2(3):190-6. 

93. Tang FI, Sheu SJ, Yu S, et al. Nurses relate the 

contributing factors involved in medication errors. J 

Clin Nurs. 2007 Mar;16(3):447-57. 

94. ven den Bernt PM, Fijn R, ven der Voort PH, et al. 

Frequency and determinants of drug administration 

errors in the intensive care unit. Crit Care Med 

2002;30:846-50. 

95. Blegen MA, Goode CJ, Reed L. Nurse staffing and 

patient outcomes. Nurs Res 1998;47:43-50. 

96. Blegen MA, Vaughn T. A multisite study of nurse 

staffing and patient outcomes. Nurs Econ 1998; 

16(4):196-203. 

97. Whitman GR, Kim Y, Davidson LJ, et al. The impact 

of staffing on patient outcomes across specialty unit. 

JONA 2002;32:633-9. 

98. Carlton G, Blegen MA. Medication-related errors: a 

literature review of incidence and antecedents. Annu 

Rev Nurs Res 2006;24:19-38. 

99. Rogers AE, Hwang WT, Scott LD, et al. The working 

hours of hospital staff nurses and patient safety. 

Health Aff 2004;23(4):202-12. 

100. Fogarty GJ, McKeon CM. Patient safety during 

medication administration: the influence of 

organizational and individual variables on unsafe 

work practices and medication errors. Ergonomics 

2006;49:444-56. 

101. Hofmann D, Mark BA. Errors, violations and 

climates for error and safety: A theoretical 

investigation of health care correlates. Journal of 

Personnel Psychology 2006; 59:847-869. 

59 
Patient Safety and Quality: An Evidence-Based Handbook for Nurses

102. Ulanimo, VM, O'Leary-Kelley C, Connolly PM. 

Nurses’ perceptions of causes of medication errors 

and barriers to reporting. J Nur Care Qual 

2007;22:28-33. 

103. Henrickson K, Dayton E, Keyes MA, et al. 

Understanding adverse events: a human factors 

framework. In: Hughes RG (ed.), Patient safety and 

quality: an evidence-based handbook for nurses. 

Rockville, MD: AHRQ, 2008. 

104. Scott-Cawiezell J, Pepper GA, Madsen RW, et al. 

Nursing home error and level of staff credentials. 

Clinc Nurs Res 2007 Feb;16(1):72-8. 

105. Aitken R, Manias E, Dunning T. Documentation of 

medication management by graduate nurses in patient 

progress notes: a way forward for patient safety. 

Collegian 2006;13(4):5-11. 

106. Manias E, Aitken R, Dunning T. How graduate 

nurses use protocols to manage patients’ medications. 

J Clin Nurs 2005;14:935-44. 

107. Chevalier BA, Parker DS, MacKinnon NJ, et al. 

Nurses’ perceptions of medication safety and 

medication reconciliation practices. Can J Nurs 

Leadersh 2006;19(3):61-72. 

108. Rothschild JM, Keohane CA, Cook F, et al. A 

controlled trial of smart infusion pumps to improve 

medication safety in critically ill patients. Crit Care 

Med 2005;33:533-40. 

109. Manias E, Aitken R, Dunning T. Medication 

management by graduate nurses: before, during and 

following medication administration. Nurs Health Sci 

2004;6:83-91. 

110. Eisenhauer LA, Hurley AC, Dolan N. Nurses’ 

reported thinking during medication administration. J 

Nurs Scholarsh 2007;39:82-7. 

111. Manias E, Aitken R, Dunning T. Decision-making 

models used by graduate nurses managing patients’ 

medications. J Adv Nurs 2004;47:270-8. 

112. Millward LJ, Bryan K, Evaratt J, et al. Clinicians and 

dyslexia—a computer-based assessment of one of the 

key cognitive skills involved in drug administration. 

Int J Nurs Stud 2005;42:341-53. 

113. Blegen MA, Vaughn T, Goode CJ. Nurse experience 

and education: effect on quality of care. J of Nurs 

Admin 2001;31:33-9. 

114. Manias E, Aitken R, Dunning T. Graduate nurses’ 

communication with health professionals managing 

patients’ medications. J Clin Nurs 2005;14:354-62. 

115. Manias E, Bullock S. The educational preparation of 

undergraduate nursing students in pharmacology: 

perceptions and experiences of lecturers and students. 

Int J Nurs Stud 2002;39:757-69. 

116. Leape LL, Kabsenell AI, Gandhi TK, et al. Reducing 

adverse drug events: lessons from a breakthrough 

series collaborative. J Qual Improv 2000;26:321-31. 

117. Rask K, Culler S, Scott T, et al. Adopting National 

Quality Forum medication safe practices: progress 

and barriers to hospital implementation. J Hosp Med 

2007 July/Aug;2(4):212-8. 

118. Schneider PJ, Pedersen CA, Montanya KR, et al. 

Improving the safety of medication administration 

using an interactive CD-ROM program. Am J 

Health-Syst Pharm 2006;63:59-64. 

119. Franklin BD, O’Grady K, Parr J, et al. Using the 

internet to deliver education on drug safety. Qual Saf 

Health Care 2006;15:329-33. 

120. Dennison RD. A medication safety education 

program to reduce the risk of harm caused by 

medication errors. The J Contin Educ Nurs 

2007;38(4):176-84. 

121. Papastrat K, Wallace S. Teaching baccalaureate 

nursing students to prevent medication errors using a 

problem-based learning approach. J Nurs Educ 

2003;42(10):459-64. 

122. Paparella SF, Mariani BA, Layton K, et al. Patient 

safety simulation: learning about safety never seemed 

more fun. J Nurses Staff Dev 2004;20(6):247-52. 

123. Force MV, Deering L, Hubbe J, et al. Effective 

strategies to increase reporting of medication errors 

in hospitals. J Nurs Admin 2006;36:34-41. 

124. Burdeu G, Crawford R, van de Vreede M, et al. 

Taking aim at infusion confusion. J Nurs Care Qual 

2006;21(2):151-9. 

125. Bennett J, Harper-Femson LA, Tone J, et al. 

Improving medication administration systems: an 

evaluation study. Can Nurse 2006 

October;102(8):35-9. 

126. Pape TM. Applying airline safety practices to 

medication administration. MEDSURG Nurs 

2003;12(2):77-94. 

127. Pape, TM, Guerra DM, Muzquiz M, et al. Innovative 

approaches to reducing nurses’ distractions during 

medication administration. J Contin Educ Nurs 

2005;36(3):108-16. 

60 
Medication Administration Safety

128. Greengold NL, Shane R, Schneider P, et al. The 

impact of dedicated medication nurses on the 

medication administration error rate. Arch Intern 

Med 2003;163:2359-67. 

139. Franklin BD, O’Grady K, Donyai P, et al. The impact 

of a closed loop electronic prescribing and 

administration system on prescribing errors, 

administration errors, and staff time: a before-andafter study. Qual Saf Health Care 2007;16:279-84. 

129. Wright J, Emerson A, Stephens M, et al. Hospital 

inpatient self-administration of medicine 

programmes: a critical literature review. Pharm 

World Sci. 2006;28(3):140-51. 

140. Paoletti RD, Suiess TM, Lesko MG et al. Using barcode technology and medication observation 

methodology for safer medication administration. 

Am J Health Syst Pharm 2007;64(5):536-43. 

130. Fields M, Peterman J. Intravenous medication safety 

system averts high-risk medication errors and 

provides actionable data. Nurs Admin Q 

2005;29(1):78-87. 

141. van Gijssel-Wiersma DG, van den Bemt PM, 

Walenbergh-van Veen MC. Influence of 

computerized medication charts on medication errors 

in a hospital. Drug Saf 2005;28(12):1119-29. 

131. Nelson NC, Evans RS, Samore MH, et al. Detection 

and prevention of medication errors using real-time 

bedside nurse charting. J Am Med Inform Assoc. 

2005 Jul-Aug;12(4):390-7 

142. Blegen MA. Knowledge from quality improvement 

activities. Nurs Research 2008, in press;57(1). 

143. Nerenz DR, Stoltz PK, Jordan J. Quality 

improvement and the need for IRB review. Qual 

Manag Health Care 2003;1:159-70. 

132. Schaubhut R, Jones C. A systems approach to 

medication error reduction. J Nurs Care Qual 

2000;14(3):13-27. 

144. Lynn J. When does quality improvement count as 

research? Human subject protection and theories of 

knowledge. Qual Saf Health Care 2004;13:67-70. 

133. Coyle GA, Heinen M. Evolution of BCMA within 

the Department of Veterans Affairs. Nurs Admin Q 

2005;29(1):32-8. 

145. Baker GR. Strengthening the contribution of quality 

improvement research to evidence based health care. 

Qual Saf Health Care, 2006;15:150-1. 

134. Mahoney CD, Berard-Collins CM, Coleman R, et al. 

Effects of an integrated clinical information system 

on medication safety in a multi-hospital setting. Am J 

Health Syst Pharm 2007;64(18):1969-77. 146. Pronovost P, Wachter R. Proposed standards for 

quality improvement research and publication: one 

step forward and two steps back. Qual Saf Health 

Care 2006;15:152-3 

135. Sakowski J, Leonard T, Colburn S, et al. Using a barcoded medication administration system to prevent 

medication errors in a community hospital network. 

Am J Health Syst Pharm 2005;62:2619-25. 147. Mosser G, Kane RL. How do you prove quality 

improvement? J Am Geriatr Soc 2007;55:1672-3. 

136. Larrabee S, Brown MM. Recognizing the 

institutional benefits of var-code point-of-care 

technology. Jr Comm J Qual Saf 2003;29(7):345-53. 

148. Berwick DM. Broadening the view of evidence-based 

medicine. Qual Saf Health Care 2005;14:315-6. 

137. Anderson S, Wittwer W. Using bar-code point-ofcare technology for patient safety. J Healthc Qual 

2004;26(6):5-11. 

149. Davidoff F, Batalden, P. Toward stronger evidence 

on quality improvement. Draft publication 

guidelines: the beginning of a consensus project. 

Qual Saf Health Care 2005;14:319-25.

138. Meadows G. Safeguarding patients again medication 

errors. Nurs Econ 2002;20(4):192-4. 

61