The problem of look‐alike, sound‐alike name errors: Drivers and solutions

Abstract

Look‐alike or sound‐alike (LASA) medication names may be mistaken for each other, e.g. mercaptamine and mercaptopurine. If an error of this sort is not intercepted, it can reach the patient and may result in harm. LASA errors occur because of shared linguistic properties between names (phonetic or orthographic), and potential for error is compounded by similar packaging, tablet appearance, tablet strength, route of administration or therapeutic indication. Estimates of prevalence range from 0.00003 to 0.0022% of all prescriptions, 7% of near misses, and between 6.2 and 14.7% of all medication error events. Solutions to LASA errors can target people or systems, and include reducing interruptions or distractions during medication administration, typographic tweaks, such as selective capitalization (Tall Man letters) or boldface, barcoding, and computerized physician order entry.

Full text

REVIEW ARTICLE
The problem of look-alike, sound-alike name errors: Drivers
and solutions
Rachel Bryan
1
| Jeffrey K. Aronson
2
| Alison Williams
1
| Sue Jordan
1
1
Swansea University, UK
2
University of Oxford, UK
Correspondence
Rachel Bryan, Swansea University, UK.
Email: r.bryan@swansea.ac.uk
Look-alike or sound-alike (LASA) medication names may be mistaken for each other,
e.g. mercaptamine and mercaptopurine. If an error of this sort is not intercepted, it
can reach the patient and may result in harm. LASA errors occur because of shared
linguistic properties between names (phonetic or orthographic), and potential for
error is compounded by similar packaging, tablet appearance, tablet strength, route
of administration or therapeutic indication. Estimates of prevalence range from
0.00003 to 0.0022% of all prescriptions, 7% of near misses, and between 6.2 and
14.7% of all medication error events. Solutions to LASA errors can target people or
systems, and include reducing interruptions or distractions during medication admin-
istration, typographic tweaks, such as selective capitalization (Tall Man letters) or
boldface, barcoding, and computerized physician order entry.
KEYWORDS
look-alike, medication error, nomenclature, similarity, sound-alike
1|INTRODUCTION
In this review we introduce the problem of look-alike, sound-alike
(LASA) name errors; give an overview of the landscape of medication
nomenclature; outline the scope, importance and prevalence of LASA
name errors; and explore solutions. This paper is to be complemented
by a systematic review in a forthcoming issue. We adopted a step-
wise approach to exploring the literature. After identifying papers that
are central to the problem of LASA name errors, we handsearched for-
ward citations (paper that cited it after publication) and backward cita-
tions (key papers they cited), and identified further relevant literature.
2|MEDICATION ERRORS INVOLVING
LASA NAMES
Of all events that are reported to cause patient harm in the UK, medi-
cation errors are the most common. Between January and March
2018 they accounted for 10.7% of incidents (206 485 medication
incidents out of a total of 1 936 812 incidents), and 63 deaths.
1
Medi-
cation errors can occur when medications have similar-looking or
similar-sounding names, and/or shared features of product packaging.
These wrong drug errors are so-called LASA errors.
2
LASA errors make
up a high proportion of all medication errors; estimates range from
6.2
3
to 14.7%,
4
representing a significant threat to patient safety.
5,6
They can occur during prescribing, dispensing or administration of
medicines, and can lead to administration of the wrong medication.
LASA errors can result in overdosing, under-dosing, or inappropriate
dosing.
7
Confusion can occur between: generic–generic names
(e.g. penicillin–penicillamine); brand–brand names (e.g. Prozac–
Provera); brand–generic names (e.g. Soriatane–sertraline); or generic–
brand names (e.g. methadone–Metadate); these examples are taken
from error reports.
8
Most LASA pairs are reciprocal, i.e. each has been
mistaken for its counterpart, revealing the influence of inherent
pairwise similarity, rather than external environmental factors.
This review is primarily concerned with errors that are caused by
look-alike names and sound-alike names, and interventions to reduce
their prevalence. A systematic review in a forthcoming issue explores
Received: 5 November 2019 Revised: 24 January 2020 Accepted: 5 February 2020
DOI: 10.1111/bcp.14285
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any
medium, provided the original work is properly cited and is not used for commercial purposes.
© 2020 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society
386 Br J Clin Pharmacol. 2021;87:386–394.wileyonlinelibrary.com/journal/bcp

interventions to reduce the prevalence of LASA errors. Given the
wide variation in definitions of a medication error, it is difficult to
quantify the proportion of medical errors that concern medications:
for example, the authors of 1 review found 26 definitions of a medica-
tion error in 45 medication error studies, but no association between
definitions of error and prevalence.
9
Under the 5 rights framework, a
LASA error is typically a wrong drug error, which may be due to a
LASA name (e.g. morphine vs hydromorphone
10
) or LASA packaging
(e.g. acebutolol vs amiodarone packaged in identical drug blisters
11
),
with or without a similar name.
LASA errors occur because of shared linguistic properties
between 2 or more names, and lead to incorrect substitution of
1 medicinal product for another. If not interrupted, this results in erro-
neous drug administration. The cause of the error may lie in similarities
in orthography (the written forms) or phonology (the spoken forms),
and several similarity measures have been proposed.
12,13
The poten-
tial for LASA errors may also be compounded by similarities in product
packaging, dosage form, or strength. LASA errors often involve selec-
tion of the wrong medication from a shelf or from an electronic list.
5
There is no universally agreed definition of a LASA error—Table 1
illustrates the range of published usages of the term. These examples
show that (i) the property LASA is usually applied to medication name
pairs, rather than the error itself; and (ii) LASA names are viewed as
the cause of medication errors. This is important—LASA name pairs
are present in the nomenclature as potential errors, regardless of
whether an error has occurred. For the sake of brevity, we shall use
the term LASA error in this review.
5,13,14
3|MEDICATION NOMENCLATURE—
NAMES AS MEANINGFUL LINGUISTIC ITEMS
Medications have at least 3 names. The first is the chemical name,
published by the International Union of Pure and Applied Chemistry
(IUPAC). The chemical name (e.g. N-acetyl-para-aminophenol) is based
upon the chemical formula of the substance. Secondly, a medication
will have at least 1 brand name, chosen by each manufacturer
(e.g. Tylenol, Panadol). The name is commercially motivated, with an
upper-case initial, and may be followed by the registered trademark
symbol. Legally the name is required not to imply any therapeutic ben-
efit; it is typically laconic and euphonious. Once out of patent (up to
20 years in the EU), a substance can be marketed and sold by compet-
itors and will be given more brand names. Thirdly, in each country in
which the medication is licensed to be marketed, it will be assigned a
national generic name (such as a British Approved Name, BAN, in the
UK; a United States Adopted Name, USAN, in the USA; or a
Denominazione Comune Italiana, DCIt, in Italy). It will also be assigned
a global generic name—an International Nonproprietary Name (INN)
by the World Health Organization (WHO). Examples include paraceta-
mol (INN, BAN), acetaminophen (USAN), and paracetamolo (DCIt).
There are multiple strata in the nomenclature of generic names:
they are formed on international, regional and national levels, and are
published multilingually. INNs are the most commonly used generic
names, with over 8000 already designated; INNs are used by default
in both the UK and the EU, with only a few notable exceptions (such
as adrenaline in the UK, see
26
). These names are formally placed in
the public domain to promote consistency of global communications
between manufacturers, clinicians, prescribers, and patients. The
nomenclature is published in 7 languages: English, Spanish, French,
Chinese, Arabic, Russian and Latin.
27
Historically, the classical languages Latin and Greek were used
to form terms in medicine. However, throughout the 19th century
medicine was transformed into an applied science and started to
move away from publication in Latin.
28
Nevertheless, Latin and
Greek live on in word formation processes in English, in particular
for terms in specialist domains such as medicine. Neoclassical word
formation is a process in which a morph (a word part) is borrowed
from a classical language and combined with other morphs to form
a word with a new meaning that did not exist in the classical lan-
guage. An analogy would be using parts from a classic car to create
a new, modern car. This is helpful to users of the specialist lan-
guage, as the terms formed are readily understandable by speakers
of various European languages, sharing as they do lexical roots. For
example, neuroblastoma comprises neuro- (Greek νευρο-, nerve),
blast (Greek βλαστός, embryo) -oma (Greek -ωμα, tumour)
29
; and
antimicrobial comes from anti- (Latin, against), micro- (Greek μικρός,
small) and -bial Greek βίος, life).
Medication names are artificial terms, created by official bodies
such as the WHO. They are morphologically complex and can be
analysed into base components, or stems. The stems are determined
by the naming body (WHO 2009), and they are formed from neoclas-
sical roots or other methods. Stems may be acronyms (e.g. -mab for
monoclonal antibody) or abbreviations (such as -vir for antivirals or
-ast for antiasthmatics). They are often indirectly formed from neo-
classical compounds. For example, the suffix stem -kin is an abbrevia-
tion of interleukin, which in turn is a neoclassical combining form of
the morphs inter- (Latin, between) and -leuk- (Greek λευκο-, white
and κύτος, cell), plus the suffix -in.
We have previously identified multiple problems with WHO nam-
ing guidelines for INNs,
2,30
in that they are sometimes vague and
unquantifiable, and expose a tension between the 2 primary goals of
the INN programme: on 1 hand, to reduce the risk of confusion, and
on the other hand, to ensure that names are easy to use, remember,
and understand and are clearly related to chemical composition, phar-
macological action, and/or therapeutic use. Almost half of the INNs
we analysed use pharmacological stems inconsistently, and a fifth of
them are distinguishable from other names by just a single letter, cre-
ating the potential for confusion.
2
4|SCOPE AND IMPORTANCE
The impact of a LASA error can vary, depending on the medicinal
product administered, the dose or route of administration, and the
condition of the patient. LASA errors may be spotted before the
wrong medicinal product reaches the patient, or they may be
BRYAN ET AL.387

TABLE 1 Usage of the terms LASA and look-alike, sound-alike
Citation
Relationship between LASA names and
medication errors (ME) Reference
“Around 1 in 4 medication errors has
been attributed to orthographic
(look-alike) and phonetic (sound-alike)
similarity between drug names and/or
look-alike or confusable packaging.”
LASA as a cause of ME.
5
“One of every 4 medication errors
reported in the United States is a
name-confusion error.”
LASA as a hyponym of ME.
13
“Many hundreds of drugs have names
that either look or sound so much alike
that doctors, nurses and pharmacists
can get them confused, dispensing the
wrong one in errors that can injure or
even kill patients.”
LASA as a cause of error.
14
“Some of the more common sources of
medication errors are confusion
between sound-alike medication names
or look-alike medication names, and
confusion due to similar appearances
for medication packages, or similar
labels for different medications.”
LASA as a risk factor of ME.
15
“Medication names that look-alike [or]
sound-alike (LASA) are the most
common cause contributing to
medication errors [sic].”
LASA as a cause of ME.
16
“Medication errors commonly involve
drug names that look or sound alike.”
“Similar-looking commercial labelling and
packaging are common causes of
medication error, often from the use of
nearly identical packaging for 2
separate items.”
LASA as a cause of ME.
17
“Confusions between drug names that
look and sound alike are common,
costly, harmful, and difficult to
prevent.”
The event is the confusion. LASA as a
hyponym of ME.
18
“Confusions between drug names that
look and sound alike account for
between 15 and 25% of reported
medication errors.”
Confusion (LASA) as a hyponym of ME.
19
“Similarity between drug names can cause
errors in short-term memory as well as
in visual and auditory perception.”
Similarity as a cause of error.
19
“Patients sometimes receive the wrong
drug because similarity in the spelling
and/or pronunciation of drug names
leads to errors in prescribing,
dispensing and administration.”
Similarity as a cause of error.
20
“The term LASA (look-alike sound-alike)
delineates a confusion of medication
due to the similar labelling and
packaging of different drugs, or similar
labelling and packaging of the same
drug containing different strengths.”
Similarity as a cause of error.
21
“The potential for drug name similarity to
cause medication errors is widely
Similarity as a cause of error.
22
388 BRYAN ET AL.

recognized only much later. There have been many case reports of
LASA errors. A few indicative examples are described here. Often, the
outcome is not reported, so it is difficult to assess intensity and seri-
ousness accurately. These examples show the range of events that
can arise from LASA errors.
4.1 |Example 1: Mercaptopurine INSTEAD OF
mercaptamine
31
In 2010 the MHRA reported that an infant with nephropathic
cystinosis was given mercaptopurine instead of mercaptamine. After
taking the wrong medicinal product for 1 month, the infant developed
pancytopenia but made a full recovery after the error was noticed and
rectified.
4.2 |Example 2: Hydromorphone INSTEAD OF
morphine
10
In 2005 it was reported that in a US emergency department a nurse
gave oral hydromorphone 10 mg (standard dose 1.3 mg 4 hourly)
instead of oral morphine 10 mg (standard dose 5–10 mg 4 hourly) to
an elderly man, a 3–5-fold overdose. She had been distracted by
another patient. When she returned, she forgot to fill in the medicines
reconciliation record for the cupboard. Also, hydromorphone was not
usually stored in that cupboard, so she was not primed to be prepared
for the confusion. The patient was discharged before the error was
noticed and suffered a fatal respiratory arrest on his way home.
4.3 |Example 3: Cisatracurium INSTEAD OF
vecuronium
32
In 2010 it was reported that cisatracurium had been dispensed
instead of vecuronium and administered to a 1-week-old neonate.
The error was realized immediately and no changes in vital signs were
observed. This error occurred due to similarity of the loaded syringes,
despite different labels.
4.4 |Example 4: Sufentanil INSTEAD OF
fentanyl
33
In 2000 sufentanil instead of fentanyl was administered to a 15-year-
old boy and a 45-year-old man (who were admitted to the same ward
on the same day). Both developed apnoea, cyanosis, flaccidity and
vital signs far below baseline (e.g. oximetry as low as 60%), but both
made a full recovery. This was an approximately 6-fold overdose. For
the 15-year-old, 20 μg of intravenous fentanyl was prescribed, and
supposedly administered—in actuality this was sufentanil in the same
dose. For the 45-year-old, 100 μg of intravenous fentanyl was pre-
scribed, but 50 μg was supposedly administered—in actuality this was
sufentanil (the same dose). Owing to similar names and packaging and
TABLE 1 (Continued)
Citation
Relationship between LASA names and
medication errors (ME) Reference
acknowledged by health care
professionals.”
“It is approximated that 1/4 of
medication-related incidents voluntarily
reported in the United States are
caused by drug name confusion”.
“Look-alike, sound-alike medication errors
occur when the names of 2 drugs have
orthographic similarity […], or phonetic
similarity […], forming a look-alike,
sound-alike pair.”
LASA as a hyponym of ME.
23
“Considerable research on medication
error has focused on the provision of
an incorrect drug to a patient caused by
confusion between orthographically
similar drug names or similar drug
packaging.”
LASA as a cause of ME.
24
“Wrong-drug errors, thought to be caused
primarily by drug names that look
and/or sound alike, occur at a rate of
about 1 error per thousand dispensed
prescriptions in the outpatient setting
and 1 per thousand orders in the
inpatient setting.”
LASA as a cause of ME.
25
BRYAN ET AL.389

the same manufacturer, they were put into the wrong medication
drawer. The ampoules contained the same concentration.
5|PREVALENCE
There is a dearth of quantitative evidence about the prevalence of
LASA errors, and wide variations have been reported. A summary of
the prevalence of LASA errors is given in Table 2.
LASA errors occur in up to 0.0022% of all prescriptions.
17,23,34,38
Since over 1 billion prescriptions are issued in the UK each year (1.1
billion in England in 2017
39
), we can extrapolate this error incidence
to 2.2 million such errors each year. It is often stated that they
account for up to 25% of medication errors,
13,15,22,40
although this
seems to be a rather shaky upper ceiling, as the sources cited in these
papers are not original studies (e.g.
41
a list of suggested LASA pairs
cited by
13
), or are anecdotal case reports (e.g.
42
a commentary and
case study, cited by
13
), or are studies finding a lower prevalence
(e.g. on average 11.4% of medication errors committed in a hospital
were due to similar names,
35
cited by
15
). A lower prevalence is
suggested by other original studies, such as 6.2% of reported medica-
tion events (37 of 597 event reports
3
), 7% of medication near misses
(143 or 2044 near miss reports
36
) and 15% of vaccine errors (89 of
607 error reports
4
). Searches aiming to ascertain the prevalence of
LASA errors indicate little evidence and a problematic reliance on sec-
ondary citations.
TABLE 2 Summary of the results of studies of the prevalence of look-alike, sound-alike (LASA) errors
Reference % (n/N) Details
3
6.2% of paediatric medication events
(37/597)
Based on incident reports collected in 18
emergency departments in the USA;
paediatric medication events accounted
for 19% of 597 events; 6.2% (37) were
due to LASA errors
4
14.7% (89/607) This was an analysis of 607 error reports to
US MEDMARX between 2003 and 2006;
errors can be categorized under 1 or
more different types; 105 of 607 reports
pertained to a wrong vaccine error, of
which 89 (14.7%) were errors within
LASA groups (as defined by the authors),
such as td, Tdap, DTaP, and DT).
23
0.00003% of all prescriptions
(395/1,420,091).
A database rather than clinical outcomes;
this US study identified 0.28 alerts to
potential LASA errors per 1000
prescriptions; all the errors arose from 22
LASA name pairs prescribed over
6 months in South Carolina.
34
0.0022% of all prescriptions (244/113,346) This was the proportion of errors attributed
to brand name confusion in a general
hospital in Delhi.
35
11.4% of medication errors due to similar
names, both brand and generic (79/2103)
Evaluation of prescribing errors in a
631-bed teaching hospital in the US, and
causes attributed; the figure of 11.4%
includes ‘wrong drug’errors due to similar
names, wrong dosages, and wrong
abbreviations, and so this is an upper
estimate
36
7% of medication near misses (143/2,044) A systematic evaluation of 2044 near miss
prescribing events; 7% were due to
sound-alike names.
37
22% of errors reported; absolute numbers
not available as we have not retrieved the
paper; numerators and denominators not
stated
Multiple papers cite this report from the US
Pharmacopoeia Medication Errors
Reporting Program (date unknown but
published in 1996); it reports that
similarity in appearance or sound of
medicinal product names played a key
roles in the commission of 22% of errors.
The original paper cannot be retrieved,
but it is pertinent to include here as it is
cited by so many other papers.
390 BRYAN ET AL.

6|SOLUTIONS
Unlike other forms of medication error (such as wrong patient or
wrong route of administration), the onus does not squarely fall on
the healthcare professionals who prescribe, dispense, or administer
the medication. More broadly, the problem of LASA name confusion
should also be considered to be the responsibility of the manufac-
turer, regulators and naming bodies.
43
There is little focus in the
error literature on manufacturers and regulators, and indeed there is
a clear incentive for pharmaceutical companies to avoid error reduc-
tion activities, for fear of exposure to liability, regulatory interfer-
ence, and loss of competitive advantage.
44
Furthermore, naming
bodies, such as the WHO and the British Pharmacopoeia Commis-
sion, have a central responsibility to work against the designation of
highly confusable pairs, but our previous research demonstrates
vague and unquantifiable guidelines, which are applied very
inconsistently.
2
If LASA pairs were identified at the pre-marketing stage, the
errors would not have occurred, because the names would not exist,
and several similarity measures between proposed names and existing
names have been created.
19,45
In 2002 the Food and Drug Adminis-
tration, in collaboration with academics, developed the phonetic and
orthographic computer analysis (POCA) tool, an algorithm that mea-
sures the phonetic and orthographic similarities of a proposed brand
name against multiple datasets of both brand and generic names.
46,47
The software was made publicly available, and industry manufacturers
are encouraged to use it when proposing new brand names. An INN
report in 2016 briefly mentioned the POCA scores between 2 pro-
posed generic names, so they appear to be making use of the soft-
ware in the name approval process, but to an unknown extent. Use of
software such as POCA should reduce LASA errors involving new
names, but of course it cannot be used retroactively, and an INN, once
recommended, has never been amended. The accuracy of the similar-
ity score and ability to predict error is also heavily reliant on the exact
method of the algorithm.
However, LASA pairs may only become apparent after errors or
near misses are reported, and several strategies to reduce the risks
have been proposed. Reviews focusing on risk reduction commonly
separate interventions into person and system approaches
5,40
; this
dichotomy originates in James Reason's theory of human error.
48
The person approach commonly apportions blame by focusing on
the role of the practitioner in the error, implying negligence, care-
lessness, inattention, incompetence, deficiencies/lack of knowledge
or inadequate professional preparation.
40,49
It also considers the
potentially chaotic circumstances in which medications are pre-
scribed, dispensed or administered, which may include interruptions
and distractions,
50
especially in high intensity environments, such as
emergency departments.
10
The system approach assumes that to err
is human and that the root causes of error lie in nonhuman factors
present in the system.
48,49
The system approach thus attempts to
reduce errors by identifying and addressing latent conditions
48
in the
system that prime the risk of errors. It is generally accepted that
system-based approaches to preventing errors have greater
success.
5,10,48
Elucidating external causative factors encourages
practitioners to report errors and near misses, which may otherwise
be underreported, owing to fear of reprisal, blame and reputation
damage.
51
In recent years, there has been a growing body of research on
LASA errors, and various interventions have been proposed.
5
Below
we introduce 4 key interventions: (i) reducing interruptions and dis-
tractions in relation to LASA errors; (ii) typographic adaptation;
(iii) barcoding; and (iv) computerized physician order entry.
6.1 |Reducing interruptions and distractions.
This intervention falls squarely into the person approach, by aiming to
reduce variability in human behaviour. Since a LASA error may occur
in writing or speaking a name (language production) or in reading or
hearing a name (language reception), it has been recommended that
health care professionals say and/or spell the name out loud (presum-
ably before typing or handwriting or administering it), to ensure cor-
rect understanding and to solidify the name in the working memory.
5
Furthermore, a suite of measures to reduce distractions and interrup-
tions during prescribing/prescription, dispensing, and administration
have been proposed, such as “Do not disturb”tabards to be worn dur-
ing drug rounds and “no interruption”zones, with varying degrees of
success.
50,52
6.2 |Storage strategies
It is recommended that LASA drugs are stored physically apart from
1 another to reduce the risk of selection, or picking, errors. In terms of
psychology, selection of a medicinal product encompasses 2 distinct
processes—choosing the correct item and rejecting distractors.
53
Stra-
tegically organized shelves and storage areas can separate items with
orthographically similar names, and this reduces the number of similar
names (distractors) in the health care professional's visual field. Strate-
gic storage will inevitably be an improvement on alphabetical ordering,
since names that share the initial 2 or 3 letter sequences are more
likely to be confused.
54
6.3 |Typographic intervention, e.g. Tall Man
lettering
Printed and digital names can be presented in various ways to maxi-
mize their readability and distinctiveness, by changing font colour,
weight, kerning, and capitalization. Tall Man lettering is a popular way
of changing the typography of medicinal product names; it has been
endorsed by the US Food and Drug Administration since 2001,
55
and
is used in many hospital pharmacies in the UK (personal communica-
tion, ABMU pharmacist). Tall Man lettering uses selective capitaliza-
tion of LASA name pairs to highlight characters that distinguish them
from each other, for example, DOBUTamine and DOPamine, or
BRYAN ET AL.391

hydrALAzine and hydrOXYzine.
17,22
Tall Man lettering has the poten-
tial to reduce LASA errors in written/typed, but not spoken, communi-
cations, and it differentiates look-alike packaging. Moreover, it is
relatively easy to implement, both on physical packaging and electron-
ically. According to cognitive theory of visual searching, similarity
between the desired selection (target) and other items (nontargets)
increases the difficulty of the search.
24,56,57
It is thus beneficial to
enhance certain properties of the target that distinguish it from non-
targets, so-called feature-based processing,
58
such as changes to
typography. Examples are bolding, italicizing, colour contrast, or use
of uppercase lettering. In the forthcoming systematic review (by the
same authors) of the efficacy of Tall Man lettering, we found that Tall
Man is a marginally effective intervention to reduce LASA error, with
a number of caveats. We presented a Tall Man placebo effect, whereby
users derive more benefit from the intervention when they are aware
of its purpose, and found a ceiling of efficacy, beyond which in certain
high-risk situations the risk of confusion cannot be mitigated by
typography alone.
6.4 |Barcoding
Some studies have estimated that a third of all errors take place dur-
ing administration, and are therefore more likely to reach the patient
and to cause harm.
59
Barcode medication administration technology
was developed to reduce medication errors during administration, by
confirming at the bedside that the 5 rights of medication are in place:
right drug, dose, time, route and patient. Patients are given a
barcode wristband on admission, and this is scanned before any
medication is administered. Barcode scanning may also be integrated
into dispensing and is used to correlate physical selection of the
medicinal product with selection on the screen. This is used to vary-
ing degrees and is especially popular in Australia owing to financial
incentives.
5,10
A key disadvantage to barcode scanning is that it risks
reproducing errors that were made before dispensing, as these are
then less likely to be spotted if manual checks are also not per-
formed as a result.
6.5 |Computerized physician order entry
Computerized alerts can be introduced into dispensing software to
alert the user to potential LASA medication pairs and to intercept
LASA errors. For example, an alert may read: “This medicinal prod-
uct is typically used for hypothyroidism. No such problem appears
on the problem list of this patient. [Cancel/Ignore/Add diagnosis]”
(taken from
38
). Computerized alerts are used in various forms to
varying degrees.
5
They can reduce errors
38
and contribute to lists
of problem names, jog attention and inform about specific proper-
ties of LASA pairs, such as names that share the initial 3 letters,
which are more likely to be confused. However, professionals can
over-ride computerized warnings and there is associated alert
fatigue.
60
7|SUMMARY
LASA errors between similar medication names pose a complex prob-
lem, with the potential to cause fatal or devastating harm to patients.
Estimates of prevalence are wide-ranging, and are based on multiple,
competing definitions. Several solutions are available, some of which
focus on reducing variability in human behaviour (person approaches,
such as limiting work interruptions) and others, which seek to identify
risk factors or weaknesses in the nomenclature system and create
safeguards (system approaches, such as Tall Man lettering).
ACKNOWLEDGEMENTS
Rachel Bryan is writing a PhD, funded by a Swansea University stu-
dentship award.
COMPETING INTERESTS
R.B., A.W. and S.J. have no conflicts of interest to declare. J.K.A. has
published papers on adverse drug reactions and medical linguistics and
has edited textbooks on adverse drug reactions; he has acted as an
expert witness in cases related to adverse drug reactions; he chairs an
expert working group on nomenclature for the British Pharmacopoeia
Commission and is an Associate Editor of BMJ Evidence Based Medi-
cine and President Emeritus of the British Pharmacological Society.
ORCID
Rachel Bryan https://orcid.org/0000-0001-8617-3882
Jeffrey K. Aronson https://orcid.org/0000-0003-1139-655X
Sue Jordan https://orcid.org/0000-0002-5691-2987
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How to cite this article: Bryan R, Aronson JK, Williams A,
Jordan S. The problem of look-alike, sound-alike name errors:
Drivers and solutions. Br J Clin Pharmacol. 2021;87:386–394.
https://doi.org/10.1111/bcp.14285
394 BRYAN ET AL.