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R e la tio n s h ip b e t w e e n M e d i c a t i o n E rro rs a n d
d v e r s e Dr u g Ev e n t s
Dav id W. Bates MD MSc De borah L. Boy le BA M artha B. Va nd er Vl iet RN
James Schneider RPh Lucian Leap e M D
OBJECTIVE
T o e v a l u a t e t h e f r e q u e n c y o f m e d i c a t i o n e r r o r s
u s i n g a m u l t i d i s c i p l i n a r y a p p r o a c h , t o c l a s s i f y t h e s e e r r o rs
b y t y p e , a n d t o d e t e r m i n e h o w o f t e n m e d i c a t i o n e r r o r s a r e
a s s o c i a te d w i t h a d v e rs e d r u g e v e n t s ( A D E s) a n d p o t e n t i a l A D E s .
DESIGN
M e d i c a t i o n e r r o rs w e r e d e t e c t e d u s i n g s e l f - r e p o r t
b y p h a r m a c i s t s , n u r s e r e v i e w o f a ll p a t i e n t c h a r t s , a n d r e v i e w
o f a l l m e d i c a t i o n s h e e t s . I n c i d e n t s t h a t w e r e t h o u g h t t o r e p -
r e s e n t A D E s o r p o te n t i a l A D E s w e r e i d e n t i f i e d t h r o u g h s p o n -
t a n e o u s r e p o r ti n g f r o m n u r s i n g o r p h a r m a c y p e r s o n n e l , s o -
l i c i te d r e p o r t in g f r o m n u r s e s , a n d d a i l y c h a r t r e v i e w b y t h e
s t u d y n u r s e. I n c i d e n t s w e r e s u b s e q u e n t l y c l a s s if i e d b y t w o
i n d e p e n d e n t r e v i e w e r s a s A D E s o r p o t en t i a l A D E s .
SETTING
T h r e e m e d i c a l u n i t s a t a n u r b a n t e r ti a r y c a re h o s -
p i t a l .
PATIEN TS
A c o h o r t o f 3 7 9 c o n s e c u t i v e a d m i s s i o n s d u r i n g
a 5 1 - d a y p e r i o d ( 1 , 7 0 4 p a t i e n t - d a y s ) .
INTERVENTION N o n e .
MEASUREMENTS AND M A IN RESULTS O v e r th e s t u d y p e -
r io d , 1 0 , 0 7 0 m e d i c a t i o n o r d e r s w e r e w r i t te n , a n d 5 3 0 m e d -
i c a t i o n s e r r o r s w e r e i d e n t i f i e d ( 5 . 3 e r r o r s / 1 0 0 o r d e r s ), f o r a
m e a n o f 0 . 3 m e d i c a t i o n e r r o r s p e r p a t i e n t - d a y , o r 1 . 4 p e r
a d m i s s i o n . O f t h e m e d i c a t i o n e r ro r s , 5 3 i n v o l v e d a t l e a s t
o n e m i s s i n g d o s e o f a m e d i c a t i o n ; 1 5 i n v o l v e d o t h e r d o s e
e r r o r s , 8 f r e q u e n c y e r r o r s , a n d 5 r o u t e e r r o r s . D u r i n g t h e
s a m e p e r i od , 2 5 A D E s a n d 3 5 p o t e n t i al A D E s w e r e f o u n d . O f
t h e 2 5 A D E s , f iv e ( 2 0 ] w e r e a s s o c i a t e d w i t h m e d i c a t i o n
e r ro r s; a l l w e r e ju d g e d p r e v e n t a b l e . T h u s , f i v e o f 5 3 0 m e d i -
c a t i o n e r r or s ( 0 . 9 ) r e s u l t e d in A D E s . P h y s i c i a n c o m p u t e r
o r de r e n t ry c o u l d h a v e p r e v e n t ed 84 o f n o n - m i s s i n g d o s e
m e d i c a t i o n e r r o rs , 8 6 o f p o t e n t i a l A D E s , a n d 6 0 o f p r e -
v e n t a b l e A D E s .
CONCLUSIONS M e d i c a t i o n e rr o rs a r e c o m m o n , a l t h o u g h
r e l at i v el y f e w r e s u l t i n A D E s . H o w e v e r , t h o s e t h a t d o a r e p r e -
v e n ta b l e , m a n y t h r o u g h p h y s i c i a n c o m p u t e r o r d er e n t r y.
KE Y WORDS m e d i c a t i o n e r r o r; a d v e r s e d r u g e v e n t ; c o m -
p u t e r o r d e r e n t r y .
J G EN IN T E R N M E D 1 9 9 5 ; 1 0 : 1 9 9 - - 2 0 5 .
Received from the Division of General Medicine, Depart ments
of Medicine and Pharmacy. Brigham and Women s Hospital
and Harvard Medical School, Boston. Massachusetts.
Supported in part by the Risk Management Foundation. Dr.
Bates is the recipient of National Resourc e Service Awa rd I
F32 HS00040-01 fro m the Agency for H ealth Care Policy and
Research.
Address correspondence and reprint requests to Dr. Bates:
Division o f General Medicine, Depart ment of Medicine. Brigha m
and Women s Hospital, 75 Franc is Street. Boston, MA 02115.
njuries due to drugs were the most freque nt cause of
adverse events in the Harvar d Medical Practice Study,
in which about 1 of all hospitalized pati ents suffered
a disabling injury related to medic ations. ~ Other s tudi es
have also suggested that drugs are a major mediator of
iatrogenic illness.2,
Adverse drug events (ADEs}, defi ned as inj uri es re-
sulting from medical int erve ntio ns related to a drug, are
common. However, spon tan eou s reporting, the usua l
means of ADE identif i cation, overlooks as m an y as 95-
99 of ADEs tha t are detectab le by other me tho ds. 4-6
In addition, most ADEs are dose-dependent and poten-
tially predictable; a smaller num be r are unpredi ctabl e,
idiosyncratic, or allergic react ions to drugs. 7-9 Almost
all errors result ing in ADEs are associ ated with the f irs t
type of ADEs, which are particularly imp ort ant b ecause
they may be preventable.
Medication errors
are errors in the process of or-
dering or delivering a medi cation, regardless of wheth er
an in ju ry occu r r ed o r the po ten t i a l f or in ju ry w as
present. Some med icat ion errors result in ADEs. Med-
ication errors can occur at any stage in the drug order-
ing , d ispens ing, and admi nis t r a t io n process .
A number of s tudies have evaluated the frequency
of medication errors , most of which do not result in
ADEs. lo-13 Two rece nt stud ies of error freq uenc y iden-
tified the errant orders inter cepted by pha rma cis ts in
pediatric hospi tals, I°. 1~ an d foun d a rate of 3- 5 medi-
cation errors per 1,000 orders. However, these stu die s
did not dete rmin e the frequency of medic ation errors
that were unk nown to pharmacis ts , the nu mbe r of ADEs
resulting from medica tion errors , or the am oun t of re-
work that medic ation errors cause for providers . Others
have developed comprehen sive re comm end ati ons for er-
ror prevent ion , in cluding improved educat ion in drug
proper t ies and s tand ardi zed drug label ing , 14-17 a l-
though these rec ommenda t ions have not been pr ior i -
tized.
Because physician errors in writing orders account
for many medication errors , one major technologic in-
tervention that appears to have subs tan tia l potential for
reducing the num ber of medicat ion er rors is phys ic ian
comp uter order entry, ~8. 19 in wh ich phy sic ian s write or-
ders directly on the compu ter. Orders can be s truct ured,
reducing dose errors a nd legibili ty problems, a nd the
computer can c onduc t checks for the presence of such
th ings as drug a l lerg ies and drug-drug in teract ions .
However, the perce ntage of medica tion errors t hat may
be preventable us ing such a sys tem is unknown .
t99
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2 B a t e s e t a l ., M e d i c a t i o n E r ro r s a n d A D E s JGIM
To develop effective strategies for impro vin g the cur-
rent drug ordering and delivery system, the frequenc y
and types of medicat ion er rors a nd their re la t ionships
with ADEs must be better defined. Thus, we undertook
a study to: 1 ) evaluate the frequen cy of medic ation errors
us ing a comprehens ive mult id isc ip l in ary approach; 2)
classify medicatio n errors accordi ng to type; 3] deter-
mine how often medicat ion errors are associated with
ADEs and potential ADEs; 4) evaluate the cons equen ces
of medication errors in terms of rework for providers;
and 5) evaluate the prop ortio n of medic ation errors t hat
may be preventable us ing phys ic ian computer order en-
try.
M E T H O D S
P a t i e n t P o p u l a t i o n
The patient population consisted of a cohort of all
adul ts admit ted to three medical uni ts a t Br igha m and
Women's Hospital durin g October and November 1992.
Two general medical units and one medical intensive
care unit (ICU) were st udi ed over a 51-day period. T hese
units were selected because we previously found in an-
other s tudy and separate data collection period that
medical units had higher rates of ADEs tha n did surgical
units , and ICUs had higher rates of ADEs th an did non-
ICUs. 7 Inte rns order most of the medica tions on these
uni ts . The uni t of evaluat ion was the pat ient-day.
D ef in i t ions
M e d i c a t i o n e r ro r s were defined as errors occurring
at any stage in the process of ordering or delivering a
medication. They included the en tire ra nge of severity,
from trivial errors, suc h as orders that necessit ated clar-
if ication or missi ng doses (defined as in stan ces in which
a drug was not available in the medic ation drawer whe n
the nurs e went to give it), to l ife -threate ning errors , su ch
as a patient 's receiving ten tim es the accepted dose of a
drug with a nar row toxic- therapeut ic ra t io . R u l e v i o -
l a t i o n s were orders tha t were faulty in some way bu t h ad
litt le potential for har m or extra work b ecause they were
in terpreted by nurs ing and pharmacy without c lar i f i -
cation, presum ably correctly. An example is an order
such as MgS04 1 amp IV now, becau se ampu les come
in several s t rengths b ut one s t rength is s tandard .
A d v e r s e d r u g e v e n t s A D E s ) were defined as inju ries
resulting from medical int erv enti ons related to a drug.
Adverse drug events may result from medication errors
or from adverse drug reactions in which there was no
error. For example, s eda ti on from a n overdose of a ben-
zoidazapine and a rash caused by an allergic response
to penicill in are bot h ADEs. Medication errors with po-
tential for injury bu t in which no i njury occurred were
classified as p o t e n t i a l A D E s . A n example is an order for
penicill in for a patie nt with a k nown allergy to the dr ug
in which the order was intercepted or the patient re-
ceived the dru g and e xperien ced no allergic reac tio n (Fig.
1 ). I n c i d e n t s
were defined as occurrences that the s tudy
nurse thought might represent an ADE or a potent ia l
ADE, whether or not there was an error.
a s e F i n d in g
All new orders were evaluat ed to det ermi ne wheth er
they represented potential medication errors . Renewal
orders were counted but were excluded from the anal-
yses, because we felt they would less often be associated
with medication errors . Potenti al medica tion errors were
detected in three ways: f irs t , pharmacists reported any
prescr ibing errors ident i f ied dur ing the d ispens i ng pro-
cess; second, the s tudy nurse reviewed all charts for
evidence of medic ation errors: an d third, a trai ned re-
viewer evaluated all medication sheets received by the
pharmacy. The chart review includ ed a careful daily
reading of the progress notes in each chart, followed by
a more detailed investigat ion if the n urs e identif ied in-
dications of a possible medi cati on error (e.g., major
bleeding, new confusion, unanticipated ICU transfer,
use of an antidot e such as naloxone, or prescripti on of
cer ta in medicat ions such as d iphenhydramine) . The
trained reviewer looked for orders that necessita ted clar-
if ication or change, which was also often noted by the
pharmacis ts on medicat ion sheets .
Incidents that were tho ught to represent ADEs or
potential ADEs were identif ied in a s imilar fashion, but
in addition reports of inc idents were solicited from nurse s
through dai ly v is its to the uni ts by the s tudy nurse , and
by daily electronic-mail notes to nurs es on the unit s .
Providers reporting inci dent s were assured a nonymi ty.
Clinical data collected from th e medica l record for
all pati ents involved in an ADE or a potent ial ADE in-
cluded the date and time of the incident, the name and
dose of the drug involved, complicati ons, an d the source
of identif ication of the incide nt. For medic ation errors
we determined whether contact between the provider
and the s taff had been necessary for the problem's res-
olution; for example, whethe r the ph arm aci st had called
the physician to clarify an order. From this , we estimat ed
the amou nt of rework (defined as addition al work cause d
by system malfun ctions) required.
R ev iew Process
All potential med icati on errors were evaluated by a
physician reviewer, who classif ied them as med icati on
error, rule violation, or no error. A 10% sample was re-
reviewed by a second p hysic ian to dete rmin e reliabili ty.
Medication errors were classified by type: dose error
(overdose, underdose, mis sin g dose, wrong dose form,
dose omitted), route error ( incorrect route, wro ng route,
route omitted), frequency error ( incorrect frequency, fre-
quency omitted), sub sti tut ion error (wrong drug given,
wrong pat ient received drug) , dru g-dr ug in teract ion ,
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JGIM
V o l u m e 1 0 A p r il 1 9 9 5
2 t
inappropriate drug, illegible order, kno wn allergy to drug,
nonformulary drug, avoidable delay in t rea tment , and
preparation error.
Incidents (suspected ADEs or po tentia l ADEs) were
evaluated inde pend entl y by two reviewers, a nd classified
into one of four categories: ADEs: pot ent ial ADEs; med-
ication errors, wh en an error was presen t but there was
no injury or potential for injury; and exclusions, whe n
no error was made an d the injury was mino r. When the
reviewers disagreed about the classif ication, they met
and came to a consens us. P rec onse nsus reliabili ty for
jud gme nts for presence of an AIDE or a potentia l ADE
made usi ng this methodology was previously found to
be good, 7 with kapp a scores of appr oxim ate ly 0.8.
The ADEs and potential ADEs were the n classified
according to severity and preventabili ty, as previously
reportedY Severity was classified as life-threatening, se-
rious, or sig nific ant. 1o Preve ntabi lity was classifie d us-
ing a four-point scale adapted from Dub ois an d Brook. 2°
For purposes of analysis, this four-point scale was col-
lapsed into two categories: preventable and not pre-
ventable. We previously found 7 that kappa s for judg-
ment s o fADEs regarding prevent ability and severity usin g
these scales were 0.63-0.89. Medication errors were also
evaluated as to the likelihood that they would be pre-
ventable , us ing a computer ized phys ic ian order entry
system. Service responsible for the inc ide nt was also
identif ied; categories were physicians, nur sin g, phar-
macy, secretary, other, multifactorial, and none.
S t a t i s t i c a l M e t h o d s
Univariate analyses were carried out usi ng the chi-
square test for categorical variables . Int errat er reliabil-
it ies for whether an ADE was pres ent a nd for ju dgm ent s
of preventabili ty and severity were calculat ed us ing the
kappa statis tic. 2~ Dete rmi nati on of interr ater reliabili ty
for whether a medic ation error, rule violation, or nei ther
was present was made u sin g a three-way kappa statis-
tic. 22 The SAS statist ical p ackag e was use d to con duc t
the analy ses. 2~
R E S U L T S
The 51-day s tudy per iod included 379 admiss ions
and 1,704 patient-days, duri ng which 10,070 medica-
tion orders were written on the three medical units . In
addition, 1,532 renewal orders were written. Th e 10,070
orders include d 3,913 o rderin g sets (a set is a group of
F IG U RE t . T h e r e la t io n s h i p s b e tw e e n me d i c a t i o n e r r or s a d v e r s e
d r u g e v e nts [AD Es] a n d p o te n t i a l AD Es . O n l y a s ma l l p r o p o r t i o n
o f me d i c a t i o n e r ro rs re p r e s e n t a n AD E o r a p o te n t i a l AD E a n d
w h i l e a l l p o te n t i a l AD Es a r e me d i c a t i o n e r ro rs o n l y t h e m i n o r i ty
o f AD Es a r e a s s o c i a te d w i t h a me d i c a t i o n e r ro r.
medication orders written at one time). Among these
10,070 orders, there were a total of 530 m edi cat ion er-
rors (5.3 ), or 1.4 medi cati on errors per admiss ion (Table
I). In addit ion, 128 of the 10,070 ord ers were jud ged to
be rule violations (0.08 rule violat ions per patient-day}.
The kappa between reviewers was 0.68 for the judg me nt
of whether an order repre sented a me dicat ion error, a
rule violation, or neither of the above.
Medication order error rates were compared by uni t
(Table 2). Many more orders were written in the ICU
(12.6 orders/patient day) than on the two medical units
(3.8 and 3.9 orders/patient-day), bu t the error rates were
similar (4.5, 6.0, a nd 6.0 errors/100 orders) across the
units. However, serious errors were 4.5 times more fre-
quent in the f irs t medical unit (0.9 serious errors/100
orders) th an in the other medical unit and the ICU (0.2
serious errors/100 orders each) (p < 0.001). The reason
for this difference is unclear, as the two medical units
share staffing.
Classif ication of medic atio n errors showed tha t 53
(280) represente d missi ng doses, and 47 (250) were
no n-m is si ng dose errors . While mis sing dose errors are
relatively min or from the clinical perspective, they can
result in s ignifican t delays in giving medicatio ns to pa-
t ients . Contact between pharmacy an d n urs i ng person-
nel was required for all 280 of these errors.
T a b l e I
M e d i c a t i o n O r d e r a n d E rr or R a t e s
n~ lO0 n / l 00 0
n O r d e r s P a t i e n t - d a y s n / A d m i s s i o n
Medication orders I 0,070 5,910 26.6
Medication errors 530 5.3 311 1.4
Adverse drug events 25 0.25 14.7 0.07
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B a t e s e t a l . , M e d i c a t i o n E r r o r s a n d A I D E s JGIM
T a b l e 2
M e d i c a t i o n O r d e r a n d E rr or R a t e s b y U n it
P a t ie nt - Ord e rs / E r rors /10 0 S e r ious E r rors /
O r d e r s d a y s P a t i e n t - d a y O r d e r s 1 0 0 O r d e r s
General unit 1 2,498 648 3.9 6 0.9
General uni t 2 2,496 653 3.8 6 0.2
intensive care unit 5,076 403 12.6 4.5 0.2
* S e r io u s er ro r s a r e d e f i n e d a s t h o s e a s s o c i a t e d w i t h a d v e r s e d r u g e v e n t s A D E s ) a n d p o t e n t i a l A D E s .
Among the non- mis sin g dose errors (Table 3), dose
errors , frequenc y errors , a nd ro ute errors were the most
common. However, less freque nt types of errors were
sometime s serious, for example, the 11 instances in whic h
a medicat ion was ordered for a pat ient with a known
allergy. Physicians were judge d responsible for 81% of
these errors; computerized order entry could have a s ig-
nificant effect on re duct i on of these errors , and indeed,
84% of all non -mi ssi ng dose errors were judge d pre-
ventable by computerized order entry. Provider contact
was required for resolut ion of the error in 83%.
For bo th miss i ng dose er rors and the re mainder o f
medicat ion errors , ant ibiot ics were the drug class most
often involved. Antibiot ic s were associa ted with 19% of
non -m iss ing dose medicat ion errors , fol lowed by elec-
t rolyte conc entr ates (10%), cardiovasc ular drugs (8%l,
and analgesics (7%).
In all , 82% of medi cat i on err ors were ident i f ie d
through review of medi cat ion sheets ; phar macy self-re-
port yielded 9%, and nurse self-report and chart review
yielded the remaining 9%. Missing dose errors were
ident i f ied almost exclusively throu gh review of medica-
t ion sheets . Even when these errors were excluded from
the analysis , review of medi cat i on sheets rema ined the
most product ive source, an unexpected finding.
D Es a n d M e d i c a t i o n E rro rs
During the same t ime period, 25 ADEs were iden-
t if ied, f ive of whic h we re asso ciated with medic at io n er-
rors and were judge d prevent able (Table 4). Therefore,
five of 530 medic at ion errors (0.9%) resul ted in an ADE;
an addi t ional 35 medic at io n errors (6.7%) were judg ed
to be potent ial ADEs. No missing dose error was asso-
ciated with an ADE or a potent ial ADE.
Severi ty of the potent ial ADEs and ADEs was also
assesse d (Table 4); no pat ien t di ed of an ADE. The five
preventable ADEs included a hypotensiv e episode, he-
moptysis , gastrointent inal bleeding, a local toxic reac-
t ion , and an asp i ra t ion pneumonia . Errors associa ted
with the five prevent able ADEs included a dose error, a
frequency error, an insta nce in which fol low-up of ther-
apy was inadequate , a d rug- drug in terac t ion , and a
t ranscr ip t ion er ror . Phys ic ians were judged respons ib le
for three and nurses for two.
Most of the po tent ial AD Es (27 of 35, 77%) wer e
errors that were intercepted before the medicat ion was
administered (Table 3). In the remaining eight an ad-
verse outcome was avoided only by chance. These eight
potent ial ADEs included three dose errors , a frequency
error, an inst ance in which a pat ie nt rece ived a drug
ordered for ano ther pa t i en t , a n inadver ten t d i scont in -
uat ion of a drug, an avoidable delay in t rea tment , and
a case in which a drug was not given when needed. Of
the 27 potent ial ADEs that were intercepted before the
medicat ion reached the pat ient , 11 (41%) were the resul t
of an order for a drug to which the pat ient had a known
allergy. Physicians were judg ed responsib le for 93% of
the intercepted potent ial ADEs, and verbal orders ac-
counted for 19%.
Compu ter order ent ry was judg ed to have the po-
tential to prevent three preventable ADEs (60%), five
{62 %) of the noni nter cept ed poten tial ADEs, and 25 (93 %)
of the intercepted potent ial ADEs.
D I S C U S S I O N
We found that medica t ion er rors were more co mmon
than has been sugges ted by other reports , t hat relat ively
few resul ted in adverse events , and that they created a
subs tan t ia l burden of p rov ider rework . Most medicat ion
errors appeared potent ial ly preventable by the use of
physician computer order entry.
The rate of medic at ion err ors that we found, 53 per
1,000 orders , is substant ial ly higher than has been pre-
viously reported.~°-~3 24-31 Clearly, th e rate of detec tion
depends on the intensi t y of survei l lance. To maximiz e
our abi l i ty to f ind errors , we used a comprehensive ap-
proach to case detect ion: a comb ina t ion of pharm acist s
review of prescript ions, pat ien t h ospi tal record review,
sol ici tat ion of reports by nurses , and detai led review of
all medication sheets. Using more limited methods, lower
rates will be found. For example, two of the large st s tud-
ies of medicat io n errors ident i f ied only three to f ive
errors per 1,000 orders , but these were restricted to
order ing er rors iden t i f i ed and prevented by pharma-
cists, ~o., ~ while we identi fied e rro rs whe the r or not they
were prevented , and a l so dur ing the admin i s t ra t io n and
dispens ing processes . Others have found that when
pharmacy er ror de tec t ion was combined wi th a rev iew
of all prescript ions, 32 med icat ion erro rs per 1,000 or-
ders were found . 24
While the exhaust ive approach we used would be
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JGIM Volume 10 April 1995 2 3
p r o h i b i t i v e l y e x p e n s i v e f o r a l a r g e - s c a l e s t u d y o r f o r o n -
g o i n g q u a l i t y m e a s u r e m e n t , t h i s l i m i t e d s t u d y p r o v i d e s
a n e s t i m a t e o f t h e u p p e r b o u n d o f e r r o r i n t h e m e d i -
c a t i o n o r d e r i n g , d i s p e n s i n g , a n d a d m i n i s t r a t i o n p r o -
c e s s es . T h e r a t e of s e v e n A D E s p e r I 0 0 a d m i s s i o n s t h a t
w e d e t e c t e d d u r i n g t h i s s t u d y p e r i o d w a s s i m i l a r t o t ha t
i n a p r e v i o u s s t u d y w e c o n d u c t e d , 7 a n d t o f i n d i n g s i n a
m u c h l a r g e r s t u d y w e h a v e r e c e n t l y c o m p l e t e d o n t h e
i n c i d e n c e a n d c a u s e s o f A D E s ( u n p u b l i s h e d d a t a , 1 9 9 4 )
s o it i s l i ke l y t h a t t h e r e l a t i o n s h i p o f m e d i c a t i o n e r r o r s
t o i n j u r i e s h e r e d e s c r i b e d ( 1 0 0 : 1 ) i s r e p r e s e n t a t i v e .
I n c l a s s i f y i n g m e d i c a t i o n e r r o r s , m a n y s t u d i e s h a v e
f o u n d th a t d o s e e r r o r s ( u n d e r d o s e , o v e r d o s e , a n d w r o n g
d o s e ) a r e t h e m o s t f r e q u e n t t y p e . t °. ~ . ~3 .2 6, 3 1, 3 2 H o w -
e v er , n o n e o f t h e s e s t u d i e s m a d e a c o n c e r t e d s e a r c h f o r
m i s s i n g d o s e s , w h i c h w e f o u n d t o b e b y f a r t h e m o s t
c o m m o n t y p e o f m e d i c a t i o n e r r o r . W e a ls o f o u n d t h a t
a f t e r m i s s i n g d o s e s , d o s e e r r o r s w e r e t h e m o s t f r e q u e n t
t y p e o f e r r o r . I n t e r e s t i n g l y , a s m a l l g r o u p o f m e d i c a t i o n
e r r o r s c a u s e d a l a r g e p r o p o r t i o n o f A D E s a n d p o t e n t i a l
A D E s . F o r e x a m p l e , o r d e r s f o r a d r u g t o w h i c h t h e p a -
t i e n t h a d a k n o w n a l l e rg y a c c o u n t e d f o r o n l y 2 o f t h e
m e d i c a t i o n e r r o r s i n t h i s s t u d y , b u t 3 1 o f t h e p o t e n t i a l
A D E s . T h i s s u g g e s t s t h a t i m p r o v e m e n t s i n o r d e r i n g s y s -
t e m s s h o u l d t a r g e t b o t h h i g h - f r e q u e n c y e r r o r s ( s u c h a s
d o s e e r r o r s ) a n d i n f r e q u e n t s e r i o u s e r r o r s . F o r e x a m p l e ,
a u t o m a t e d a l le r g y c h e c k i n g a t t h e t i m e a n o r d e r i s p l a c e d
c o u l d s u b s t a n t i a l l y r e d u c e t h e f r e q u e n c y o f A D E s d u e t o
a k n o w n a l le r g y .
S e v e r a l s t u d i e s h a v e a s s e s s e d t h e p o t e n t ia l o f m e d -
i c a t i o n e r r o r s t o c a u s e A D E s , to. ~ . ~a. az b u t t h e r a n g e o f
e s t i m a t e s i s v e r y w i d e ; p r o p o r t i o n s f r o m 0 t o 5 8 h a v e
b e e n r e p o r t e d . M o r e o v e r , t h e s e n u m b e r s a r e o n ly e s t i-
m a t e s , n o t a c t u a l m e a s u r e m e n t s . O n e f o u r - y e a r s u r v e y
T a b l e 3
C l a s s i f i c a t i o n o f M e d i c a t i o n E rr or s O t h e r T h a n M i s s i n g D o s e s
T o t a l M e d i c a t i o n P o t e n t i a l A D E s : P o t e n t i a l A D E s :
E rr or s* P r e v e n t a b l e A D E s t N o t I n t e r c e p t e d I n t e r c e p t e d
n = 2 5 0 ] n = 5 ) n = 8 ] n = 2 7 ]
E r r o r t y p e
D o s e e r r o r s 7 7 ( 3 1 ) i { 2 0 ) 3 ( 3 8 ) I 0 ( 3 7 )
F r e q u e n c y e r r o r s 4 3 ( 1 7 ) I ( 2 0 ) l { 1 2 ) 2 ( 7 )
R o u t e e r r o r s 2 6 ( I 0 ) 0 0 3 ( I I )
I l l e g ib l e o r d e r 1 6 (6 ) 0 0 0
K n o w n a l l e r g y t o d r u g l I ( 4 ) 0 0 I I ( 4 1 )
W r o n g d r u g o r p a t i e n t 1 1 ( 4 ) 0 I ( 1 2 ) 2 ( 7 )
O t h e r 6 6 ( 2 6 ) 3 ¢ t 6 0 ) 3 § ( 3 8 ) 0
S e r v i c e r e s p o n s i b l e
P h y s i c i a n s 2 0 3 ( 8 1 ) 3 ( 6 0 ) 2 ( 2 5 ) 2 5 ( 9 3 )
N u r s i n g 3 4 ( 1 4 ) 2 ( 4 0 } 6 ( 7 5 ) l ( 4 }
P h a r m a c y 7 ( 3 ) 0 0 0
O t h e r 6 ( 2 ) 0 0 0
P r e v e n t a b l e b y o r d e r e n t r y
Y e s 2 0 9 ( 8 4 ) 3 ( 6 0 ) 5 ( 6 2 ) 2 5 1 9 3 )
No 4 1 (1 6 ) 2 (4 0 ) 3 (3 8 ) 2 (7 )
O r d e r t y p e
V e r b a l 4 1 ( 1 6 ) 0 0 5 ( 1 9 )
W r i t t e n 2 0 0 ( 8 0 ) 5 ( I 0 0 ) 7 ( 8 8 ) 2 1 ( 7 8 )
Un c l e a r 9 (4 ) 0 I (1 2 ) I (4 )
*Includes medicat ion errors that we re ADEs or potent ia l ADEs, so the categories are not mutual ly exclusive .
¢ ADEs = a dver se drug events .
*Errors were: inadequate fo l lowup, drug -dru g in teract ion , and a t ranscrip tion error leading to a fa i lu re to administe r the drug.
*Errors were: avoidable d elay in t reatment , inadverte nt d iscont inuat ion o f a drug. and a drug not g iven w hen needed.
T a b l e 4
P r e v e n t a b i l i t y o f A d v e r s e D r u g E v e n ts A D E s ] a n d P o t e n t i a l A D E s
A D E s : A D E s : P o t e n t i a l A D E s : P o t e n t i a l A D E s :
N o t P r e v e n t a b l e P r e v e n t a b l e N o t I n t e r c e p t e d I n t e r c e p t e d
n = 2 0 ] n = 5 ) n = 8 ] [ n = 2 7 )
L i f e - t h r e a t e n i n g 0 I ( 2 0 ) I ( 1 2 ) 3 ( I 1 )
S e r i o u s 3 ( 1 5 ) 4 ( 8 0 ) 5 ( 6 3 ) I 2 ( 4 4 )
S i g n i f i c a n t 1 7 { 8 5 ) 0 2 ( 2 5 ) 1 2 ( 4 4 )
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2 4
B a t e s e t a l . M e d i c a t i o n E r r o rs a n d A D E s
JGIM
of d ispens ing and adm inis t ra t ion mediat ion er rors found
that 0.21% of these errors cau sed an ADE, 25 alt hou gh
medication errors due to physici an orders were ex-
cluded, and the me dicat ion had to reach the patien t to
be considered an error. We found t hat approximate ly 1%
of medicatio n errors actually caus ed an ADE (2 % if miss-
ing doses were excluded), and an additional 7% repre-
sented po tential ADEs.
While the design of the s tudy did not permit us to
measure the ho urs of rework caused by medic ation er-
rors , they are clearly subst anti al. Ninety-two percen t of
the errors (all of the m is si ng doses a nd 83% of the re-
mainder) necessitated at least a telephone call between
nurse and pharmacis t , nurse and phys ic ian , or phar-
macist and physician. In previous s tudies in this hos-
pital we found that the re solut ion of a mis sin g dose
requires an average of 8 min ute s of combined nurs i ng
and pharma cy times. Publi shed reports of mis sing doses
also provide anecdotal evidence that missing doses are
a major source of rework.aa-a6 Trac king down ph ysici ans
to correct an order is even more tim e-co nsumi ng. If the
overall average rework time is 8 mi nu te s per error, the
total amo unt of t ime wasted as a result of the 530 med-
ication errors we found would be 71 hours, an average
of about a hal f-hour per u ni t each day. Tierne y et al.
found that the number of t imes a pharmacist called a
physician to clarify an order was reduced by about one
third with physici an order ent ry (Tierney W, commu-
nication, 1994). Medication errors and ADEs have sub-
stantial costs beyond those associated with rework, in-
c luding increased length of s tay , in jury to pat ients , and
malpractice costs . A recent estimate of the cost to the
hospital of an ADE w a s 2 , 0 0 0 . 3 7
I m p l i c a t i o n s f o r P r e v e n t io n
The American Society of Hospital Pharmacists has
recently created a set of comprehe nsiv e guideline s for
medication error preventi on, inc ludi ng advice for pre-
scr ibers , pharmacis ts , nurses , pat ients , adminis t ra-
tors, and drug ma nuf act ure rsJ 4 and o thers have made
recommentat ions for medicat ion er ror prevent ion as
well. m. m-~7, 30. 31 However, the se re co mm en da ti on s ar e
so encyclopedic that i t would be impo ssible to impl emen t
all of them. This s tudy has identif ied those areas most
in need of a t ten t ion by ident i fy ing the mos t c ommon
types of medic ation errors a nd those associated wit h
ADEs.
Fortunately, relatively few medi cati on errors have
the potential to result in ADEs, and the current safety
net for preve nting ADEs catches most se rious errors .
Most potential ADEs are prevented before the pat ient
receives the drug. However, this is an aren a in which
health care should, in our view, strive for a zero defect
rate. One perce nt of medi cati on errors ' resulti ng in ADEs
is too many.
Phys ic ian computer order entry represents a major
system change with great potential for reducing seri-
ous medication errors. In physici an order entry, physi-
cians write orders using the comput er, whic h per mits
interventi on at the ti me orders are written. Several s tud-
ies have described the imp lem ent ati on of order en-
try.iS. 19 38--44 Tar get ing the phy sic ia n th rou gh com-
puter order entry should be highly effective in reduci ng
errors , s ince in the present s tud y physi cia ns were re-
sponsible for 81% of the medication errors other than
mis sin g doses. It is expected tha t o rder ent ry will de-
crease medication errors in several ways. Drug orders
will require a drug name , dose, route, a nd frequency,
which will eliminate errors of omission. All orders will
be legible, and transcription errors will be eliminated.
Compu te r i zed dos e check ing and gu ided -dos e a lgo -
rithms should decrease the occurrence of orders with
incorrect dosages. Compu ters can also s tore relevant in-
formation regarding drug -dru g in teract ions , known al-
lergies , and appropriate dosage schedules according to
the pat ien ts's chara cteri stics . 4°. 42 44
This s tudy has several l imit ations . We studi ed three
medical units in one teaching hospital, so our results
may not be generalizable to other settings. Also, despite
a broad net, some medi cati on errors almost certainly
escaped our detection. For example, our m ethod did not
detect cases in which the choice of the drug was inap-
propriate given the patie nt 's characteri s tics , and we un-
doubtedly missed some er rors in adm inis t ra t io n , be-
cause these errors occur at the last step in the medic atio n
delivery process and are the har dest to detect. Anothe r
potential bias that migh t decrease the ADE and medi-
cation error rates is a Hawthorne effect related to the
fact that nurses and pharmacis ts on the s tudy uni ts
were involved in the st udy. Finally, our cl assifi catio n of
ADEs by severity and preventab ili ty is an implicit mea-
sure. However, the inter rater ag reem ent was good, an d
the reliability of this m etho d ha s b een confirm ed by other
studies. 7
We conclude that medication errors are common,
and that most serious errors result from errors in pre-
scribing by physicians. However, relatively few medica-
tion errors results in ADEs, either because they have
litt le potential for injury or because they are int ercepted
by pharma cists a nd nur ses. Nonetheless , 1.4% of the
patients admitte d duri ng the s tudy suffered a potentially
preventable ADE. Of these preventabl e ADEs, mor e t ha n
half could have been prevente d by comp uter order entry.
Medication errors have other costs th at may be sub-
stantial, i ncludi ng malpractic e costs , rework for provid-
ers, and waste for hospitals.
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3 4 . K i t r e n o s J G , G l u c K , S t o t t e r M L . A n a l y s is o f m i s s i n g m e d i c a t i o n
e p i s o d e s in a u n i t d o s e s y s t e m . H o s p P h a r m . 1 9 7 9 ; 1 4 : 6 4 2 , 6 4 8 ,
6 5 2 - 3 .
3 5 . G r a b o w s k i B . M i s s i n g m e d i c a t i o n s i n a u n i t - d o s e s y s te m : q u a l i t y
a s s u r a n c e . H o s p P h a r m . 1 9 8 7 ; 2 2 : 6 7 9 - 8 0 .
3 6 . C h u r c h i l l W W , G a v i n T J , S o u n e y P F , S t a c h o w s k i J S . S o u r c e o f m i s s -
i n g d o s e s i n a
decentralized
u n i t d o s e s y s t e m : a q u a l i t y a s s u r a n c e
r e vi e w . H o s p P h a r m . 1 9 8 8 ; 2 3 : 4 5 3 - 6 .
3 7 . E v a n s R S , C l a s s e n D C , S t e v e n s L E , e t al . U s i n g a h o s p i t a l i n f o r -
m a t i o n s y s t e m t o a s s e s s t h e e f fe c t s o f a d v e r s e d r u g e v e n t s . P r o c
A n n u S y m p C o m p u t A p p l M ed C a re . 1 9 9 4 ; 1 7 : 1 6 1 - 6 .
3 8 . M a s s a r o T A . I n t r o d u c i n g p h y s i c i a n o r d e r e n t r y a t a m a j o r a c a d e m i c
m e d i c a l ce n t e r : I. I m p a c t o n o r g a n i z a t i o n c u l t u r e a n d b e h a v i o r .
A c a d M e d . 1 9 9 3 : 6 8 : 2 0 - 5 .
3 9 . M a s s a r o T A . I n t r o d u c i n g p h y s i c i a n o r d e r e n t r y a t a m a j o r a c a d e m i c
m e d i c a l c en t e r : I I. I m p a c t o n m e d i c a l e d u c a t i o n . A c a d . M e d . 1 9 9 3 :
6 8 : 2 5 - 3 0 .
4 0 . E l li n o y B J , B i l r o y G . A n o t h e r s t e p t o w a r d c o m p u t e r i z e d o r d e r e n t r y .
A m J H o sp P h a r m . 1 9 9 0 ; 4 7 : 2 4 6 0 - I .
4 1 . K a w a h a r a NE . J o r d a n F M . I n f l u e n c i n g p r e s c r i b i n g b e h a v i o r b y
a d a p t i n g c o m p u t e r i z e d o r d e r - e n t ry p a t h w a y s . A m J H o s p P h a r m .
1 9 8 9 ; 4 5 : 1 7 9 8 - 8 0 1 .
4 2 . P o i k o n e n J. C o m p u t e r i z e d o r d e r e n t r y : h o s p i t a l v e r s u s p h a r m a c y -
b a s e d s y s te m s . A m J H o s p P h a r m . 1 9 9 0 ; 4 7 : 2 4 6 1 - 2 .
4 3 . P r ee c e J F , A s h f o r d J R , H u n t R G . W r i t i n g a l l p r e s c r i p t i o n s b y c o m -
p u t e r . J R C o ll G e n P r a c t . 1 9 8 4 : 3 4 : 6 5 5 - 7 .
4 4 . D o n a l d J B . O n ll n e p r e s c r i b i n g b y c o m p u t e r . B M J . 1 9 8 6 : 2 9 2 :
9 3 7 - 9 .
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