Context Iatrogenic injuries, including medication errors, are an important problem
in all hospitalized populations. However, few epidemiological data are available
regarding medication errors in the pediatric inpatient setting.
Objectives To assess the rates of medication errors, adverse drug events (ADEs),
and potential ADEs; to compare pediatric rates with previously reported adult
rates; to analyze the major types of errors; and to evaluate the potential
impact of prevention strategies.
Design, Setting, and Patients Prospective cohort study of 1120 patients admitted to 2 academic institutions
during 6 weeks in April and May of 1999.
Main Outcome Measures Medication errors, potential ADEs, and ADEs were identified by clinical
staff reports and review of medication order sheets, medication administration
records, and patient charts.
Results We reviewed 10 778 medication orders and found 616 medication errors
(5.7%), 115 potential ADEs (1.1%), and 26 ADEs (0.24%). Of the 26 ADEs, 5
(19%) were preventable. While the preventable ADE rate was similar to that
of a previous adult hospital study, the potential ADE rate was 3 times higher.
The rate of potential ADEs was significantly higher in neonates in the neonatal
intensive care unit. Most potential ADEs occurred at the stage of drug ordering
(79%) and involved incorrect dosing (34%), anti-infective drugs (28%), and
intravenous medications (54%). Physician reviewers judged that computerized
physician order entry could potentially have prevented 93% and ward-based
clinical pharmacists 94% of potential ADEs.
Conclusions Medication errors are common in pediatric inpatient settings, and further
efforts are needed to reduce them.
Iatrogenic injuries occur frequently in hospitalized patients and often
have serious sequelae.1 The Harvard Medical
Practice Study estimated that 3.7% of hospitalized patients experienced an
adverse event related to medical therapy in New York State in 1984.1 Of these iatrogenic injuries, 69% were preventable.2 A more recent study reached similar estimates.3 An Institute of Medicine report in 1999 estimated
that 44 000 to 98 000 people die each year at least in part because
of medical error.4 Although there has been
some controversy about the accuracy of these extrapolated estimates,5-7 the report dramatically
increased awareness of the problem of medical errors.
In the Harvard Medical Practice Study, the most common adverse events
were complications of medication use (19.4% of all events).8
Thirty percent of patients with drug-related injuries died or were disabled
for more than 6 months, although not all morbidity and mortality was directly
attributable to these drug-related injuries.1
In response to these concerning findings, the Adverse Drug Event Prevention
Study was performed, which addressed medication errors and adverse drug events
(ADEs) in hospitalized adults in more detail.9,10
It found that ADEs were common (occurring at a rate of 6.5 per 100 adult admissions),
costly, and often had severe sequelae.9,11
Other studies largely confirmed these findings.12,13
Several studies suggest that about one third of ADEs are associated
with medication errors and are thus preventable.9,14
Bates et al15 found that medication errors
were common, occurring at a rate of 5 per 100 medication orders. However,
only 7 in 100 medication errors had significant potential for harm, and 1
in 100 actually resulted in an injury.15
Analysis of the origin of errors has suggested that specific improvements
in the medication ordering and processing system might reduce the risk of
error.10 Several studies have demonstrated
that some of these interventions can be effective. In particular, physician
computer order entry reduced medication errors significantly in an academic
medical center,16 as did a dedicated clinical
pharmacist in an academic intensive care unit (ICU).17
Similarly, a computerized clinical decision support program dramatically decreased
antibiotic-associated medication errors and ADEs, as well as total costs for
patients in an ICU.18
Less information is available regarding the epidemiology and prevention
of medication errors and ADEs in pediatric inpatient settings.19
Children pose unique challenges to the system for ordering, dispensing, administering,
and monitoring medications. For example, since weight-based dosing is needed
for virtually all drugs in pediatrics, ordering medications typically involves
more calculations than for adults. Dispensing drugs in pediatrics is also
error-prone because pharmacists often must dilute stock solutions. Young children
do not have the communication skills to warn clinicians about potential mistakes
in administering medications, or about adverse effects that they may experience.
Finally, all children, especially neonates, may have more limited internal
reserves than adults with which to buffer errors. For example, the cardiovascular
system of a premature baby may be unable to cope with even a small error in
the dosage of an inotropic agent.
To assess the epidemiology of medication errors, potential ADEs, and
ADEs in hospitalized children, we performed a prospective cohort study in
2 academic institutions. Our goals were to (1) determine the rates of medication
errors, potential ADEs, and ADEs; (2) compare rates in a pediatric hospital
setting with previously reported rates in adult hospitals; (3) analyze the
major types of errors; and (4) assess the potential impact of prevention strategies.
The study was conducted at 2 urban teaching hospitals with socioeconomically
diverse patient populations. One hospital (hospital A) is a freestanding pediatric
institution. The other hospital (hospital B) treats both adult and pediatric
patients, but has a geographically and administratively distinct pediatric
service. Adults comprise less than 5% of patients treated on the pediatric
wards. They generally have complex long-term medical and surgical conditions,
such as congenital diseases (eg, cystic fibrosis, cardiac anomalies, metabolic
diseases, sickle cell disease), multiple disabilities, immunosuppressive conditions,
and eating disorders.
At hospital A, we studied 2 randomly selected general medical wards,
1 randomly selected general surgical ward, the short-stay medical ward, and
the pediatric medical/surgical ICU (which has few cardiac patients because
there is a separate cardiac ICU). The oncology ward and neonatal ICU (NICU)
were not studied at this hospital because these units were preparing for possible
introduction of computerized order entry. At hospital B, all pediatric wards
were studied, including the general medical/surgical wards (including oncology
patients), the pediatric medical/surgical ICU, and the NICU. In total, we
studied 9 wards. There were clear differences in case mix, as well as staffing,
among individual wards of the 2 hospitals.
Physicians at both hospitals currently handwrite orders, copies of which
are sent to the pharmacy. At hospital A, nurses transcribe orders into the
medication administration record (MAR). Hospital A has satellite-based pharmacists
who dispense ready-to-administer doses to the floor, but do not actively participate
in other activities, such as ward-based rounds.
At hospital B, clerks transcribe orders into the MAR. A supply of medications
is provided to the units, with nurses subsequently performing dose calculations
and drug administration. Pediatric clinical pharmacists attend work rounds,
monitor transcriptions, and assist nurses with calculations. Since these pharmacists
are assigned to multiple units daily, they have limited time to spend on each
unit.
Medication errors were defined as errors in
drug ordering, transcribing, dispensing, administering, or monitoring. An
example is an order written for amoxicillin without a route of administration.
Some medication errors have significant potential for injuring a patient and
are considered potential ADEs. Potential ADEs may be intercepted before reaching
the patient. An example of an intercepted potential ADE would be an order
written for a 10-fold overdose of morphine that is intercepted and corrected
by a pharmacist before reaching the patient. A nonintercepted potential ADE
would be an overdose of acetaminophen administered to a patient who does not
experience any sequelae. ADEs are injuries that result from the use of a drug.
Some ADEs are associated with a medication error and therefore are considered
preventable, while some are not associated with a medication error and therefore
are considered nonpreventable. An example of a preventable ADE is the development
of rash after the administration of ampicillin/sulbactam to a patient known
to be allergic to penicillin. In contrast, a nonpreventable ADE would be development
of Clostridium difficile colitis after appropriate
antibiotic use. Finally, rule violations are faulty medication orders with
little potential for harm or extra work because nursing and pharmacy staff
typically interpret them correctly without additional clarification. An example
is a pain medication ordered on a per need basis for a postoperative patient
without an explicit reason for administration stated. Rule violations were
not considered medication errors.
One physician (R.K.) trained all data collectors, who were nurses, pharmacists,
and physicians, in an identical manner. During the 2-week training period,
the unique perspectives of these different disciplines were shared to maximize
appreciation of potential error types and to develop a comprehensive, uniform
approach to error detection. We determined inter-rater reliability by a random
sampling of 10% of the data collected at each institution by a data collector
from the other institution.
Data collectors identified medication errors, potential ADEs, and ADEs
by voluntary and verbally solicited reports from house officers, nurses, and
pharmacists; and by medication order sheet, MAR, and chart review of all hospitalized
patients on study wards. On a given day, 1 data collector was assigned to
each study ward based on individual availability. Data collected for each
incident included name, dose, route and category of drug, point in the system
where the error occurred, and type of error. Data collectors worked 5 days
per week, with recording of weekend data on Mondays for patients still hospitalized.
At the end of the study, we obtained administrative data for each patient
hospitalized on the study wards, including age, sex, and race.
Reliable detection of medication errors requires cooperation and engagement
of the staff, which depends in large measure on reducing suspicion and fear
of reporting. Before initiating this study, we gained the support of the leadership
of nursing, pharmacy, medical staff, and administration at each hospital.
House staff, nurses, and pharmacists received informal seminars that emphasized
the roles of complex systems and human factors in predisposing to error, as
opposed to individual blame. We stressed the importance of understanding the
epidemiology and causes of error, and reinforced the multidisciplinary nature
of systems improvement. We performed the study over 6 weeks in April and May
of 1999, after obtaining institutional review board approval at each institution.
Two physicians (D.W.B. and D.A.G.) independently reviewed suspected
ADEs and potential ADEs and classified them as ADEs, potential ADEs, medication
errors, and rule violations. The physician reviewers rated ADEs and potential
ADEs according to the severity of injury to the patient using a 4-point Likert
scale. They also rated ADEs on preventability using a 5-point Likert scale
and attribution (ie, the likelihood that the incident is due to the specific
drug) using the Naranjo algorithm.20 The 2
evaluators resolved all disagreements through discussion and consensus.
We report rates of errors per 100 orders, 100 admissions, and 1000 patient-days.
We did subanalyses of preventable and potential ADEs. We measured age-specific
rates per 100 admissions, and analyzed them assuming that the number of errors
occurring during an admission followed a Poisson distribution. We measured
ward-specific rates per 100 orders and compared them using the χ2 test for categorical variables since it was extremely rare for more
than 1 error to occur during a single order. Similarly, we compared rates
per 100 orders between adult and pediatric hospital settings and analyzed
them using the χ2 test. When we assumed that the number of
errors per order followed a Poisson distribution, we obtained similar results,
so we report only the χ2 test results. The SAS statistical
package (for Windows 6.12) was used (SAS Institute Inc, Cary, NC).
We calculated inter-rater reliabilities using the percentage of agreement
and the κ statistic. The data collectors and physician reviewers had
moderate-to-excellent agreement with 87%-to-100% agreement and κ statistics
of 0.65 to 1.0.
The 36-day study period included 1120 admissions and 3932 patient-days,
during which 10 778 orders were written. The patients included 183 (16%)
neonates, 326 (29%) infants, 223 (20%) preschoolers, 161 (14%) school-aged
children, 191 (17%) teenagers, and 36 (3%) adults. Of the children, 525 (49%)
were female, 731 (65%) were white, 139 (12%) were Hispanic, and 79 (7%) were
black.
There were 616 medication errors (5.7%) or 55 medication errors per
100 admissions (Table 1). In total,
320 patients accounted for these medication errors and 64 patients had 3 or
more errors. We found 26 ADEs (0.24%), of which 5 (19%) were preventable.
In addition, we identified 115 potential ADEs (1.1%), which occurred at a
rate of 10 potential ADEs per 100 admissions.
Medication errors occurred more frequently in adults compared with other
age groups (86 vs 62 for neonates, 41 for infants, 48 for preschoolers, 58
for school-aged children, and 63 for teenagers per 100 admissions; P = .006). The rate of potential ADEs was considerably higher in neonates
than in other age groups (20 vs 5 for infants, 8 for preschoolers, 12 for
school-aged children, 11 for teenagers, and 14 for adults per 100 admissions; P<.001).
Given the high rate of neonatal potential ADEs, we performed a subanalysis
comparing the 54 neonatal patients in the NICU with the 129 neonatal patients
in other wards. The NICU neonates were primarily premature with low birth
weights and respiratory and nutritional issues, while non-NICU neonates were
primarily admitted for infections or congenital abnormalities. Neonates in
the NICU experienced significantly higher medication error and potential ADE
rates (91 and 46 per 100 admissions, respectively) than neonates in other
wards (50 and 9 per 100 admissions, respectively) (P<.001
for both comparisons).
Error rates were similar across units (5.5 errors per 100 orders for
the NICU, 5.7 for pediatric ICUs, 6.0 for medical wards, 6.1 for combined
medical/surgical wards, and 4.7 for the surgical ward; P = .31). However, the NICU had a significantly higher rate of potential
or preventable ADEs compared with other wards (2.8 per 100 orders vs 0.78
for medical wards, 0.44 for surgical wards, 0.77 for combined medical/surgical
wards, and 1.3 for pediatric ICUs; P<.001).
Most medication errors were dosing errors (28%), followed by route of
administration, MAR transcription and documentation, date, and frequency of
administration errors (Table 2).
Similarly, most potential ADEs were due to dosing errors (34%), followed by
frequency and route errors. The most common stage for medication errors and
potential ADEs was physician ordering (74% and 79%, respectively), followed
by transcription and nurse administration. The most common drugs involved
in medication errors and potential ADEs were anti-infective agents, analgesics
and sedatives, electrolytes and fluids, and bronchodilators. The drug routes
of medication errors and potential ADEs were most commonly intravenous followed
by oral and inhalation.
In addition, physician reviewers judged that 93% of the potential ADEs
were potentially preventable by physician computer order entry with clinical
decision support, 94% by ward-based clinical pharmacists, and none by computerized
MAR. Finally, they judged that computerized physician order entry could have
prevented 4 of the 5 preventable ADEs and that ward-based clinical pharmacists
could have prevented 4 of the 5 preventable ADEs. For these judgments, the
role of the clinical pharmacist included full-time participation in work rounds,
monitoring the MAR transcription process, communicating with satellite pharmacies,
and assisting nurses with medication dose calculation and administration.
During the study period, 26 ADEs were identified, 5 of which resulted
from medication errors and thus were judged to be preventable (Table 3). The preventable ADEs included excessive sedation, hypothermia,
worsening pain, a rash, and stool impaction. Errors associated with these
5 incidents included 2 overdoses, a missing dose, a drug administration error,
and administration of a medication to a patient with a known allergy. Two
events involved narcotics, 1 an analgesic, 1 an antibiotic, and 1 a laxative.
The route of 2 medications was intravenous, 1 oral, 1 epidural, and 1 via
suppository. Physician reviewers classified 4 of the preventable ADEs as serious
and 1 as significant. Of the 21 nonpreventable ADEs, 14 were related to antibiotic
use, including C difficile infections, rashes, allergic
reactions, gastrointestinal tract distress, and a yeast infection. The remaining
7 were narcotic-related, including respiratory depression, sedation, and gastrointestinal
tract and allergic reactions. Fifteen of the medications were administered
intravenously, 5 orally, and 1 via epidural.
Of the 115 potential ADEs, 68 (59%) were intercepted while 47 (41%)
were not (Table 3). The physician
reviewers determined that 18 (16%) of the potential ADEs were potentially
fatal or life-threatening, 52 (45%) were serious, and 45 (39%) were significant.
Examples of potentially fatal or life-threatening intercepted potential ADEs
included physician orders for a heparin overdose, a digoxin overdose, and
amoxicillin for a patient with a previous anaphylactic reaction to penicillin.
Among the most common errors associated with potential ADEs were physicians
ordering inappropriately high or low does of medications, ordering medications
despite known allergies, ordering medications without routes, and the pharmacy
dispensing incorrect medications.
We found that medication errors were common in the inpatient pediatric
setting. Potential ADEs occurred more frequently in neonates, particularly
in the NICU. The rate of medication errors was higher in adults cared for
in the pediatric hospital setting. Errors occurred most commonly at the stage
of drug ordering. Dosing errors and errors involving the intravenous route
were most frequent. The drug classes associated most frequently with errors
were anti-infectives, electrolytes and fluids, and analgesics and sedatives.
Most errors appeared to be preventable by physician computer order entry with
clinical decision support or full-time, ward-based clinical pharmacists.
We compared the results of this study to a 1992 study using similar
methods in an adult patient population (Table 4).15 In 1992, physicians at
the adult hospital hand-wrote orders, clerks primarily transcribed orders
to the MAR, and pharmacists were primarily satellite-based, with some ward-based
involvement in the medical ICU. Both studies had similar rates of medication
errors, ADEs, and preventable ADEs; however, the rate of potential ADEs was
about 3 times higher in this pediatric study (1.1% vs 0.35%; P<.001). Inter-institutional comparisons can be difficult to standardize,
although in this case 1 physician (D.W.B.) was involved in both studies.
Relatively little research has addressed the problem of medication errors
and ADEs in pediatric inpatient settings. Reliable error detection requires
intensive, comprehensive, and active ward-based data collection. We used a
multidisciplinary approach that examined all aspects of the medication system,
from the physician's order through administration of the drug to the patient.
Moreover, we encouraged voluntary reporting by emphasizing the role of systems
problems in the origin of errors and by nurturing a blame-free environment.
In a previous pediatric study by Folli et al,19
errors were detected solely by pharmacist review of physician orders, and
lower error rates of 0.45 to 0.49 per 100 orders were found. Although 74%
of errors in our study occurred in drug orders, many of these errors were
detected and corrected prior to the order reaching the pharmacy.
As expected, we found that the errors with potential for harm occurred
most often in the youngest, most vulnerable patients cared for in the NICU.
Neonatal weights change rapidly, making appropriate dosing particularly difficult.
Moreover, medication errors in critically ill neonates may have more serious
consequences compared with relatively healthy neonates or older children because
they have limited ability to buffer errors. Pharmacists also face special
challenges with neonatal drugs because medications generally are not supplied
in dosages suitable for neonates and must be diluted.
The relatively small number of adult patients also had significantly
higher medication error rates. This may be due to the typically high medical
complexity of adult patients cared for in pediatric settings, or the lack
of familiarity of pediatric house staff with adult dosing.
The high risk of medication errors highlights the importance of developing,
testing, and implementing effective error-prevention strategies in pediatrics.
Cogent theories regarding the origin of errors (often categorized as human
factor research)21 have been developed. Most
investigators have focused on problems in health care delivery systems that
predispose to error, rather than emphasizing the role of individuals.22-26
Human fallibility is magnified substantially by complex and poorly designed
systems, poor teamwork, and psychological and environmental stressors such
as fatigue, anxiety, poor lighting, and noise. The safest work environments
address these issues by designing systems to prevent errors, make errors visible,
and mitigate the effects of errors.22 Ongoing
multidisciplinary analysis of incidents, also termed root cause analysis,
is important for developing further system improvements.27
While a number of interventions based on these principles have been
studied in adults, few data are available in pediatrics. The study by Folli
et al19 demonstrated that pharmacy review of
medication orders could prevent erroneous orders from being implemented at
a rate of 14 to 18 per 1000 patient-days. Unfortunately, other interventions
remain largely untested in children.
Review of preventable and potential ADEs by the physician evaluators
in this study suggested that the majority could potentially have been prevented
by computerized physician order entry with clinical decision support (eg,
drug-allergy checks, drug-dose checks, drug-drug interaction checks). This
finding is not surprising since 79% of the potential ADEs occurred at the
stage of ordering of medications. Common types of ordering errors included
physician omission or incorrect choice of dose, route, or frequency; order
illegibility; and physician use of nonstandard terminology.
Studies in adult hospitals have demonstrated the impact of computerized
physician order entry on error reduction. Computerized physician order entry
reduced the rate of nonintercepted serious medication errors by 55% in a large
tertiary care adult hospital.16 In another
study of this system, limited decision support decreased the medication error
rate by 64%, and with more developed decision support the error rate decreased
by 81%.28 Coupling physician order entry with
a computerized MAR is likely to reduce transcription errors, a common class
of inpatient medication errors (10% in this study).
It is important to recognize, however, that some of the factors making
children vulnerable to errors also complicate development of computerized
pediatric systems. For example, pharmacokinetics and appropriate drug doses
change rapidly as a premature neonate gains weight and renal and hepatic drug
elimination systems mature. A pediatric computer order entry system will have
to be sufficiently flexible to respond to these changes.
Review of preventable and potential ADEs by the physician evaluators
in this study suggested that full-time, ward-based clinical pharmacists potentially
could have prevented the majority of errors. Traditionally, physicians decide
on drug therapy, and pharmacists and nurses implement these decisions. The
presence of clinical pharmacists on work rounds may lead to more informed
clinical decisions by physicians, as well as interception of errors before
medication orders are finalized. Their presence on the wards should facilitate
communication between clinical staff and the pharmacy. In addition, clinical
pharmacists could independently monitor the transcription process, assist
nurses with drug preparation and administration, and monitor the drug preparation,
storage, and distribution systems. They also could be involved in developing
education programs and drug therapy protocols. Although ward-based pharmacists
were present in one of the hospitals we studied, they were not involved full
time in work rounds, monitoring the transcription process, or other ward-based
error prevention activities.
A clinical pharmacist participating in physician rounds in an adult
ICU decreased preventable ADEs by 66%.17 In
addition, ward-based interventions may reduce costs of care. During a 3-month
study, a clinical pharmacist made 345 interventions in an adult ICU, leading
to a $24 000 cost reduction.29 However,
the impact of ward-based clinical pharmacists has not been assessed in pediatrics.
Our study has several limitations. We studied 2 academic institutions,
so our results may not be generalizable to nonacademic hospitals in which
most children receive care. Despite a comprehensive multidisciplinary approach
to data collection, we probably failed to detect some errors, particularly
administration errors detected more reliably by trained observers following
nurses during routine patient care activities.30
Also, we did not attempt to detect inappropriate drug choice, which is detected
most reliably using explicit criteria based on evidence, rather than implicit
criteria based on clinical judgment.31 Because
nurses and physicians on the study wards were aware of the study, the Hawthorne
effect could have affected both the occurrence and detection of errors. In
addition, the incidence of errors could have been reduced as the study progressed
because we were obliged to take corrective action when we identified serious
practice problems. For example, an incorrect preparation of insulin was dispensed
to one of the medical floors resulting in mild hypoglycemic events in children
with diabetes, and we notified the pharmacy immediately.
Classification bias may have affected our finding that the highest rate
of potential ADEs occurred in neonates, since we used expert clinical judgment
and consensus to classify incidents. The 2 investigators who made these determinations
may have been inclined to consider errors as potentially harmful when they
occurred in critically ill neonates. However, the potential ADE rate was so
much higher in this group that it is unlikely to be completely attributable
to subjectivity. Furthermore, 3 of the 5 preventable ADEs occurred in neonates
in the NICU.
The development and testing of medication error reduction interventions
is important in pediatrics, especially in the NICU, given the increased medical
vulnerability and decreased communication ability of small and critically
ill children, the need for weight-based dosing, and the need for pharmacy
dilution of stock medications. To reduce the rates of potential and preventable
ADEs in pediatrics, the most effective interventions are likely to be computerized
physician order entry with integrated clinical decision support and full-time,
ward-based clinical pharmacists.
1.Brennan TA, Leape LL, Laird N.
et al. Incidence of adverse events and negligence in hospitalized patients:
results from the Harvard Medical Practice Study I.
N Engl J Med.1991;324:370-376.Google Scholar 2.Leape LL, Lawthers AG, Brennan TA, Johnson WG. Preventing medical injury.
QRB Qual Rev Bull.1993;19:144-149.Google Scholar 3.Thomas EJ, Studdert DM, Burstin HR.
et al. Incidence and types of adverse events and negligent care in Utah and
Colorado.
Med Care.2000;38:261-271.Google Scholar 4. To Err is Human: Building a Safer Health System. Washington, DC: National Academy Press; 1999.
5.Leape LL. Institute of Medicine medical error figures are not exaggerated.
JAMA.2000;284:95-97.Google Scholar 6.McDonald CJ, Weiner M, Hui SL. Deaths due to medical errors are exaggerated in Institute of Medicine
report.
JAMA.2000;284:93-95.Google Scholar 7.Brennan TA. The Institute of Medicine report on medical errors—could it do
harm?
N Engl J Med.2000;342:1123-1125.Google Scholar 8.Leape LL, Brennan TA, Laird NM.
et al. The nature of adverse events in hospitalized patients: results from
the Harvard Medical Practice Study II.
N Engl J Med.1991;324:377-384.Google Scholar 9.Bates DW, Cullen D, Laird N.
et al. Incidence of adverse drug events and potential adverse drug events:
implications for prevention.
JAMA.1995;274:29-34.Google Scholar 10.Leape LL, Bates DW, Cullen DJ.
et al. Systems analysis of adverse drug events.
JAMA.1995;274:35-43.Google Scholar 11.Bates DW, Spell N, Cullen DJ.
et al. The costs of adverse drug events in hospitalized patients.
JAMA.1997;277:307-311.Google Scholar 12.Classen DC, Pestotnik SL, Evans RS, Lloyd JF, Burke JP. Adverse drug events in hospitalized patients: excess length of stay,
extra costs, and attributable mortality.
JAMA.1997;277:301-306.Google Scholar 13.Lazarou J, Pomeranz BH, Corey PN. Incidence of adverse drug reactions in hospitalized patients: a meta-analysis
of prospective studies.
JAMA.1998;279:1200-1205.Google Scholar 14.Bates DW, Leape LL, Petrycki S. Incidence and preventability of adverse drug events in hospitalized
adults.
J Gen Intern Med.1993;8:289-294.Google Scholar 15.Bates DW, Boyle DL, Vander Vliet MB, Schneider J, Leape LL. Relationship between medication errors and adverse drug events.
J Gen Intern Med.1995;10:199-205.Google Scholar 16.Bates DW, Leape LL, Cullen DJ.
et al. Effect of computerized physician order entry and a team intervention
on prevention of serious medication errors.
JAMA.1998;280:1311-1316.Google Scholar 17.Leape LL, Cullen DJ, Clapp MD.
et al. Pharmacist participation on physician rounds and adverse drug events
in the intensive care unit.
JAMA.1999;282:267-270.Google Scholar 18.Evans RS, Pestotnik SL, Classen DC.
et al. A computer-assisted management program for antibiotics and other antiinfective
agents.
N Engl J Med.1998;338:232-238.Google Scholar 19.Folli HL, Poole RL, Benitz WE, Russo JC. Medication error prevention by clinical pharmacists in two children's
hospitals.
Pediatrics.1987;79:718-722.Google Scholar 20.Naranjo CA, Busto O, Sellers EM.
et al. A method for estimating the probability of adverse drug reactions.
Clin Pharmacol Ther.1981;30:239-245.Google Scholar 21.Reason J. Human Error. Cambridge, England: Cambridge University Press; 1990.
23.Perrow C. Normal Accidents. New York, NY: Basic Books; 1984.
24.Forrester JW. Counterintuitive behavior of social systems.
MIT Technol Rev.1971;73:52-68.Google Scholar 25.Berwick DM. Continuous improvement as an ideal in health care.
N Engl J Med.1989;320:53-56.Google Scholar 26.Glauber J, Goldmann DA, Homer CJ, Berwick DM. Reducing medical error through systems improvement: the management
of febrile infants.
Pediatrics.2000;105:1330-1332.Google Scholar 27.Joint Commission on Accreditation of Healthcare Organizations. Comprehensive Accreditation Manual for Hospitals:
The Official Handbook. Oakbrook, Ill: Joint Commission on Accreditation of Healthcare Organizations;
1999.
28.Bates DW, Teich J, Lee J.
et al. The impact of computerized physician order entry on medication error
prevention.
J Am Med Inform Assoc.1999;6:313-321.Google Scholar 29.Katona BG, Ayd PR, Walters JK, Caspi M, Finkelstein BW. Effect of a pharmacist's and a nurse's interventions on cost of drug
therapy in a medical intensive-care unit.
Am J Hosp Pharm.1989;46:1179-1182.Google Scholar 30.Allan EL, Barker KN. Fundamentals of medication error research.
Am J Hosp Pharm.1990;47:555-571.Google Scholar 31.Asthon CM, Kuykendall DH, Johnson ML.
et al. An empirical assessment of the validity of explicit and implicit process-of-care
criteria for quality assessment.
Med Care.1999;37:798-808.Google Scholar