relation of medication errors and adr

8/18/2019 Relation of medication errors and adr

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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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2 0 2

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 )


6/7

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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7/7

J G I M

Volume 10 April 1995

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c i an . 1 9 9 2 ; 4 5 : 2 7 2 0 - 2 .

1 6 . Z e I lm e r W A . M e d i c a t i o n e r r o r v e r s u s m e d i c a t i o n m i s a d v e n t u r e - -

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1 9 9 2 ; N S 3 2 : 2 8 - 9 , 3 2 .

1 8 . S c h r o e d e r C G , P i e r p a o l i PG . D i r e c t o r d e r e n t r y b y p h y s i c i a n s i n a

c o m p u t e r i z e d 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 . A m J H o s p P h a r r n .

1 9 8 6 : 4 3 : 3 5 5 - 9 .

1 9 . T i e r n e y W M , M i l le r M E , O v e r h a g e J M , M c D o n a l d C J . P h y s i c i a n i n -

p a t i e n t o r d e r w r i t i n g o n m i c r o c o m p u t e r w o r k s t a t i o n s . E f f e c t s o n

r e s o u r c e u t i l iz a t i o n . J A M A . 1 9 9 3 ; 2 6 9 : 3 7 9 - 8 3 .

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w h y . A n n I n t er n M e d. 1 9 8 8 ; 1 9 0 : 5 8 2 - 9 .

2 1 . F e l n s t e i n A R . C l i n ic a l E p i d e m i o l o g y : T h e A r c h i t e c t u r e o f C l i n ic a l

R e s e a r ch . P h i l a d e l p h i a : W . B . S a u n d e r s . 1 9 8 5 .

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2 : 3 7 4 - 6 .

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3 2 .

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8 3 : 3 2 4 - 6 .

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E f fe c t o f r e a c ti v e p h a r m a c y i n t e r v e n t i o n o n q u a l i t y o f h o s p i t a l p r e -

s c r i b in g . B M J . 1 9 9 0 ; 3 0 0 : 9 8 6 - 9 0 .

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a n d a c o m p u t e r - b a s e d u n i t d o s e d r u g d i s t r i b u t i o n s y s t e m . A m J

H o s p P h a r m . 1 9 7 5 ; 3 2 : 1 8 6 - 9 1 .

3 3 . P a n g F, G r a n a t J A . M i s s i n g m e d i c a t i o n s a s s o c i a t e d w i t h c e n t r a l i z e d

u n i t d o se d i sp e n s i n g . A m J H o s p P h a r m . 1 9 7 5 ; 3 2 : 1 1 2 1 - 3 .

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 .

relation of medication errors and adr

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