Computerized Physician Order Entry and Medication Errors in a
`Pediatric Critical Care Unit
`
`Amy L. Potts, PharmD*; Frederick E. Barr, MD, MSCI‡; David F. Gregory, PharmD, BCPS*;
`Lorianne Wright, PharmD*; and Neal R. Patel, MD, MPH‡§
`
`ABSTRACT. Objective. Medication errors are a major
`concern of health care professionals and medical institu-
`tions, especially errors involving children. Studies in
`adults have shown that computerized physician order
`entry (CPOE) systems reduce medication errors and ad-
`verse drug events (ADEs). The effect of CPOE implemen-
`tation in a pediatric population has not been reported.
`The objective of this study was to evaluate the impact of
`CPOE on the frequency of errors in the medication or-
`dering process in a pediatric critical care unit (PCCU).
`Methods. A prospective trial was conducted of 514
`pediatric patients who were admitted to a 20-bed PCCU
`in a tertiary-care children’s hospital before and after im-
`plementation of CPOE. Medication errors were identi-
`fied after review of all orders during the study period
`and then further classified as potential ADEs, medication
`prescribing errors (MPE), and rule violations (RV).
`Results. A total of 13 828 medication orders were re-
`viewed. Before implementation, potential ADEs occurred
`at a rate of 2.2 per 100 orders, MPEs at a rate of 30.1 per
`100 orders, and RVs at a rate of 6.8 per 100 orders. After
`implementation, the rate of potential ADEs was reduced
`to 1.3 per 100 orders, MPEs to 0.2 per 100 orders, and RVs
`to 0.1 per 100 orders. The overall error reduction was
`95.9%. Potential ADEs were reduced by 40.9%, and MPEs
`and RVs were reduced by 99.4% and 97.9%, respectively.
`Conclusions. The implementation of CPOE resulted
`in almost a complete elimination of MPEs and RVs and a
`significant but less dramatic effect on potential ADEs.
`Pediatrics 2004;113:59 – 63; medication errors, critical care,
`pediatrics, clinical decision support systems; computer-
`assisted drug therapy.
`
`ABBREVIATIONS. ADE, adverse drug event; CPOE, computer-
`ized physician order entry; IOM, Institute of Medicine; PCCU,
`pediatric critical care unit; MPE, medication prescribing error; RV,
`rules violation.
`
`Medication errors are a major concern of
`
`health care professionals and medical insti-
`tutions, especially errors involving chil-
`dren. Children have significant differences in both
`
`From the *Department of Pharmaceutical Services, Vanderbilt Children’s
`Hospital, Nashville, Tennessee; ‡Division of Pediatric Critical Care and
`Anesthesia, Department of Pediatrics, Vanderbilt Children’s Hospital,
`Nashville, Tennessee; and §Department of Biomedical Informatics, Vander-
`bilt University, Nashville, Tennessee.
`Received for publication Oct 28, 2002; accepted Apr 8, 2003.
`Reprint requests to (N.R.P.) Department of Pediatrics, Anesthesiology and
`Biomedical Informatics, Division of Pediatric Critical Care and Anesthesia,
`Vanderbilt Children’s Hospital, 714 Medical Arts Bldg, Nashville, TN
`37212-1565. E-mail: neal.patel@vanderbilt.edu
`PEDIATRICS (ISSN 0031 4005). Copyright © 2004 by the American Acad-
`emy of Pediatrics.
`
`pharmacokinetics and pharmacodynamics compared
`with adults that can make this population more sus-
`ceptible to medication errors and related injuries.
`Several factors make children in a critical care setting
`especially vulnerable to medication errors and ad-
`verse events. These factors include weight-based
`dosing, significant weight changes over a relatively
`short period of time, lack of commercially available
`products leading to dilution of stock medications,
`and the decreased communication ability of critically
`ill patients.1,2 These problems are magnified by the
`use of vasoactive infusions and the emergent use of
`drugs during cardiopulmonary resuscitation. Each
`patient requires complex calculations to determine
`the concentration of many drugs, including vasoac-
`tive agents, to be mixed by the pharmacy and the rate
`of delivery to achieve a desired dose. The process of
`prescribing medications for critically ill children is
`complex and lacks standardization, which can in-
`crease the risk of medication errors and adverse
`events.
`The significance of medication errors in pediatric
`inpatients has only recently been described. Kaushal
`et al1 studied 1120 pediatric patients who were ad-
`mitted to 2 hospitals during a 6-week period. The
`authors analyzed ⬎10 000 medication orders and
`found 616 medication errors, resulting in an error
`rate of 5.7%. This error rate is consistent with the rate
`reported in adults.3 In addition, this study evaluated
`the frequency at which medication errors occurred at
`different points in the medication system.1 Seventy-
`nine percent of potential adverse drug events (ADEs)
`occurred at the time of physician ordering, whereas a
`smaller percentage occurred at the point of transcrip-
`tion or administration.
`Recent trends toward cost containment, standard-
`ization, and accessibility of common medications
`have led to the implementation of various entities of
`automation and technology. Computerized physi-
`cian order entry (CPOE) has been identified by the
`Institute of Medicine (IOM), Leapfrog Group, Insti-
`tute for Safe Medication Practices, American Medical
`Association, American Academy of Pediatrics, and
`others as a tool that may prevent errors that occur
`during the medication ordering process.1,4 –10 The
`Leapfrog Group has also identified CPOE as 1 of 3
`initial hospital safety standards and has described
`several benefits of CPOE that may result in improved
`quality of care and reduced health care costs.5 These
`benefits may include enhanced communication be-
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`tween health care professionals through the elimina-
`tion of illegible or incomplete orders and the in-
`creased efficiency of order processing through
`instantaneous transmission of orders to other hospi-
`tal systems. Computerized decision support associ-
`ated with CPOE systems, such as displaying age-
`specific dosing regimens to the user, checking for
`doses above or below the usual range, providing
`warnings if current laboratory values indicate that
`the drug or regimen would be inappropriate for a
`particular patient, and screening for allergies and
`drug–drug interactions may also improve the order-
`ing process.
`The role of CPOE in preventing medication errors
`and ADEs has been noted in the adult literature.
`Bates et al6 evaluated the medication error rates of 3
`medical units before and after CPOE during a 4-year
`period. The authors concluded that CPOE substan-
`tially decreased the rate of medication errors with
`additional reductions observed after the addition of
`decision support and other features. Another study
`evaluated the use of CPOE in an adult population
`and found that serious medication errors were re-
`duced by 55%.7
`The development of CPOE systems that are adapt-
`able to pediatric critical care environments has been
`problematic. Developing systems
`that provide
`weight-based dosing, as well as age-specific algo-
`rithms, is difficult and applicable only to a small
`proportion of the overall health care market. There
`are limited data on the impact of CPOE on medica-
`tion errors in pediatric patients. Most literature has
`evaluated medication errors and ADEs that have
`resulted in patient injury regardless of the point in
`the system at which the error occurred. We evaluated
`medication errors that occurred specifically at the
`time of prescribing rather than administration or
`dispensing. The objective of this study was to deter-
`mine the impact of CPOE on the frequency of med-
`ication errors at the point of physician ordering in a
`pediatric critical care unit (PCCU).
`
`METHODS
`
`Study Setting
`The study was conducted in a 20-bed multidisciplinary PCCU
`at an academic institution located in a major metropolitan area.
`The institution provides services to a diverse socioeconomic pa-
`tient population. The PCCU has an average daily census of 16.3
`patients, and the average length of stay is 4.1 days. The hospital
`cares for both adult and pediatric patients, but pediatric services
`are both geographically and administratively distinct.
`
`Patient Population
`This study included all patients who were admitted to the
`PCCU during the designated study periods and encompassed
`both medical and surgical patients. Disease states represented in
`this patient population included postoperative congenital heart
`defect repair, metabolic disorders, trauma, respiratory diseases,
`bone marrow and solid organ transplantation, and other child-
`hood illnesses.
`
`Study Design
`In this prospective cohort study, a comparison was made be-
`tween the occurrences of errors in the medication ordering process
`before and after implementation of a CPOE system in the PCCU.
`Approval from the Institutional Review Board at Vanderbilt Uni-
`versity Medical Center was obtained. Data were collected before
`
`CPOE implementation for a 2-month period from October 4, 2001,
`to December 4, 2001. There was a 1-month period when no data
`were collected to allow for CPOE implementation and training of
`all attendings, fellows, residents, and staff. Post-CPOE data col-
`lection then occurred for a 2-month period from January 4, 2002, to
`March 4, 2002.
`
`Computer Systems
`WizOrder is a CPOE system developed in 1994 by the faculty in
`the division of Biomedical Informatics at Vanderbilt University.11
`WizOrder is the precursor to the commercially available Horizon
`Expert Order system (McKesson, Atlanta, GA) and currently in-
`terfaces with the Pyxis Medstation 2000 system (Pyxis Corp, San
`Diego, CA) and the pharmacy computer system, McKesson Series.
`WizOrder provides clinicians with several types of decision sup-
`port, including drug allergy alerts, dose checking, drug interaction
`alerts, and US Food and Drug Administration alerts. In addition,
`WizOrder includes clinical pathways using ⬎900 preprogrammed
`individual order sets and links to drug monographs, evidence-
`based literature sites, and the National Library of Medicine
`PubMed site. This system also interfaces to a computerized ar-
`chive of medical records that serves as a clinical data repository so
`that order-related and laboratory-related alerts can be generated
`for each individual patient. The depth of clinical decision support
`can be adjusted on the basis of predetermined criteria such as age
`or patient location. Recommendations for medication dosage ad-
`justment for impaired renal function, for example, varies between
`adult and pediatric patients. Adjustments are recommended for
`adult patients on the basis of estimates of creatinine clearance
`using standard formulas. Unfortunately, these formulas cannot
`reliably be used in pediatric patients. For these patients, clinical
`decision support provides only recent laboratory values and an
`alert to take renal function into account during the ordering pro-
`cess. Another aspect of clinical decision support that has been
`implemented is information on varying medication dosage by
`clinical indication. The system calculates the dose once the clini-
`cian selects 1 of the recommendations. WizOrder had been imple-
`mented on all adult units and the general medical/surgical pedi-
`atric wards before its implementation in the PCCU.
`
`Review Process
`All medication orders were included in this analysis except for
`the following: fluids, dialysate, total parental nutrition (TPN)/
`lipids, and chemotherapeutic agents. TPN and lipids had not been
`added to the CPOE system at the time of the study. Fluids,
`dialysate, and chemotherapy orders were entered in the CPOE
`system but will be evaluated at a later date. A designated clinical
`pharmacist reviewed all eligible orders. Errors were entered into a
`database that included information such as patient name, age,
`weight, drug, presence of error, dose, interval, and route. Errors
`were identified and further classified into categories on the basis
`of the definitions and classifications listed in Table 1 and reviewed
`for accuracy and relevance by a second clinical pharmacist. A
`physician reviewer independently evaluated all original medica-
`tion orders for 10% of randomly selected patients in both the
`pre-CPOE and post-CPOE groups to determine level of agreement
`with clinical pharmacists.
`
`Main Outcome Measures
`This study focused on errors that occurred during the medica-
`tion ordering process. An error was determined to have occurred
`when an order was found to be incomplete, incorrect, or inappro-
`priate at the time of physician ordering. Errors were classified as
`potential ADEs, medication prescribing errors (MPEs), or rule
`violations (RVs). A potential ADE was defined as any error that, if
`allowed to reach the patient, could result in patient injury. Poten-
`tial ADEs are those errors in which the ordering physician pro-
`vided incorrect or inappropriate information. They also include
`instances in which the ordering physician failed to account for
`patient-specific information (eg, allergy). MPEs were defined as
`errors in which inadequate information was provided or further
`interpretation (eg, illegibility) was required for the order to be
`processed. RVs were defined as errors that were not compliant
`with standard hospital policies (eg, abbreviations).
`
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`TABLE 1.
`
`Medication error
`
`Potential ADEs
`Duplicate therapy
`
`Inappropriate dose12
`
`Inappropriate interval12
`Inappropriate route12
`Wrong drug
`Wrong units
`
`Error Classifications and Definitions
`Any order that was incomplete, incorrect, or inappropriate at the time of
`physician ordering
`Any error that, if allowed to reach the patient, could result in patient injury
`Same drug prescribed twice or 2 or more drugs from the same class with
`no evidence-based medicine to prove benefit from both
`Based on a 10% difference in published dosing guidelines or our PCCU
`standards of practice
`Based on differences found from published dosing guidelines
`Drug not available or not recommended to be given in the route ordered
`Incorrect drug ordered
`Units are not correct for drug, diagnosis, or dose used (eg, units/kg/min
`vs mcg/kg/min)
`Documented drug interaction between 2 medications that deems drug
`ineffective or contraindicated (eg, beta-blocker with beta-agonist)
`Documented allergy to drug ordered
`
`Drug interaction
`
`Allergy
`MPE
`Missing information
`
`No weight
`Illegible
`RVs
`Abbreviation
`
`Trailing zeros
`
`Missing route, interval, concentration, rate, or dose that results in an
`incomplete order
`Patient’s weight not available
`Unable to read, required further interpretation
`
`Shortened or symbolized representation of a drug name (eg, dopa, epi,
`MSO4). Does not include CaCl2 or NaHCO3.
`Zeros to the right of the decimal point (eg, 1.0 mg)
`
`Statistical Analysis
`A ␹2 analysis and Fisher exact test for smaller sample sizes were
`used for pre-CPOE and post-CPOE data comparison. The STATA
`statistical program was used for analysis (Stata Corp, College
`Station, TX). The interrater reliability was calculated using the
`percentage of agreement and the ␬ statistic. The ␬ statistic for
`interrater reliability between the physician reviewer and clinical
`pharmacist was 0.96. This corresponds to excellent reliability.
`
`RESULTS
`A total of 13 828 medication orders involving 514
`patients were analyzed throughout the study period.
`A total of 268 patients were evaluated during the
`pre-CPOE study period and 246 patients were eval-
`uated during the post-CPOE period. The mean age of
`patients in the pre-CPOE group was 6.5 ⫾ 12.0 years
`and in the post-CPOE group was 5.4 ⫾ 10.3 years.
`This was not a significant difference between the 2
`groups. Overall length of stay in the PCCU for both
`groups was also not significantly different. The mean
`length of stay was 4.2 ⫾ 10.7 days for the pre-CPOE
`group and 4.1 ⫾ 6.6 days for the post-CPOE group.
`
`During pre-CPOE, 6803 orders were analyzed. A
`total of 2662 (39.1 per 100 orders) errors and RVs
`were identified and are described in further detail in
`Table 2. After additional classification, 2.2 per 100
`orders were identified as potential ADEs, 30.1 per
`100 orders were identified as MPEs, and 6.8 per 100
`orders were identified as RVs. The most common
`errors in the last 2 categories were missing informa-
`tion and abbreviations.
`During post-CPOE, 7025 orders were analyzed
`and a total of 110 (1.6 per 100 orders) overall errors
`and RVs were identified (Table 2). Of those, 1.3 per
`100 orders were categorized as potential ADEs. The
`rate for MPEs and RVs was only 0.2 per 100 orders
`and 0.1 per 100 orders, respectively. CPOE signifi-
`cantly reduced the rate of MPEs and RVs (P ⬍ .001;
`Table 2). Because of almost a complete elimination of
`MPEs and RVs, potential ADEs became the most
`common level of error in the post-CPOE period.
`Errors involving medication dosage and interval
`
`TABLE 2.
`
`Overall Medication Error Analysis Before and After CPOE
`Pre-CPOE (n ⫽ 6803)
`Post-CPOE (n ⫽ 7025)
`Total
`Number Per
`Total
`Number Per
`Number
`100 Orders
`Number
`100 Orders
`
`Potential ADEs
`Duplicate therapy
`Inappropriate dose
`Inappropriate interval
`Inappropriate route
`Wrong drug
`Allergy
`Drug interaction
`Wrong units
`MPEs
`Weight not available
`Missing Information
`Illegible
`RVs
`Trailing zeros
`Abbreviation
`
`147
`4
`53
`24
`6
`6
`1
`1
`52
`2049
`22
`1979
`48
`466
`55
`411
`
`2.2
`0.06
`0.78
`0.35
`0.09
`0.09
`0.01
`0.01
`0.76
`30.1
`0.32
`29.09
`0.71
`6.8
`0.81
`6.04
`
`88
`0
`59
`19
`0
`1
`0
`0
`9
`12
`0
`12
`0
`10
`10
`0
`
`1.3
`0
`0.84
`0.27
`0
`0.01
`0
`0
`0.13
`0.2
`0
`0.17
`0
`0.1
`0.14
`0
`
`P Value
`
`⬍0.001
`⬍.001
`.69
`.39
`.01
`.07
`.49
`.49
`⬍.001
`⬍.001
`⬍.001
`⬍.001
`⬍.001
`⬍.001
`⬍.001
`⬍.001
`
`
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`were the most prevalent potential ADEs. The reduc-
`tion in error rates for dosing (P ⫽ .69) and interval
`(P ⫽ .39) after CPOE implementation was not signif-
`icant.
`Overall, CPOE resulted in a 95.9% (P ⬍ .001) re-
`duction in all types of errors associated with medi-
`cation ordering. Figure 1 shows a significant reduc-
`tion in MPEs (99.4%; P ⬍ .001) and RVs (97.9%; P ⬍
`.001). A smaller but still significant reduction was
`found with potential ADEs (40.9%; P ⬍ .001) after
`CPOE implementation.
`
`DISCUSSION
`During the past decade, the prevention of medica-
`tion errors and ADEs has become a major focus of
`medical institutions. Public knowledge regarding the
`frequency and seriousness of medication errors and
`the steps that patients can take to prevent such
`events from happening has increased accordingly. In
`addition, improving patient safety through reduc-
`tion of medication errors and ADEs has received the
`attention of government officials at both state and
`national levels.
`In 1999, the impact of medical errors was dramat-
`ically publicized by an IOM report, which estimated
`that between 44 000 and 98 000 people die each year
`partly as a result of medical errors.8 This report laid
`out a comprehensive strategy by which government,
`health care providers, and consumers could reduce
`medication errors. Another report of the IOM re-
`leased in March 2001, Crossing the Quality Chasm: A
`New Health System for the 21st Century, focused on
`improving and redesigning the health care system.13
`Prepared by the IOM’s Committee on the Quality of
`Health Care in America, this report recommends the
`use of automated systems for order processing and
`the elimination of handwritten clinical information
`by the end of this decade.
`ADEs are associated with significant morbidity
`and mortality and are often preventable. Classen et
`al14 reported a 2-fold increase in death associated
`
`Fig 1. Comparison of rates of potential ADEs, MPEs, and RV is
`between pre-CPOE and post-CPOE phases. All categories of errors
`decreased significantly (P ⬍ .001) after CPOE implementation. The
`overall reduction was 40.9% (P ⬍ .001) for potential ADEs, 99.4%
`(P ⬍ .001) for MPEs, and 97.9% (P ⬍ .001) for RVs.
`
`with ADEs as well as prolonged hospitalization. In
`another study, Bates et al15 found that 28% of ADEs
`were preventable and that 56% of those occurred at
`the point of medication prescribing. The overall cost
`of ADEs has been estimated to exceed $2000 per
`event, with preventable ADEs associated with an
`annual national cost of ⬎$2 billion.14,16 The Ameri-
`can Academy of Pediatrics has also stated that med-
`ication errors in particular are associated with signif-
`icant morbidity and mortality and increased health
`care costs by an estimated $1900 per patient.9,17 This
`figure does not reflect the additional emotional costs
`incurred by patients and their families.
`Most guidelines that address methods to reduce
`medication errors recommend that institutions im-
`plement CPOE systems. However, there are limited
`data evaluating the impact of CPOE on medication
`errors in the pediatric population. In this study, we
`evaluated errors that occur only during the medica-
`tion ordering process. In addition, the separation of
`potential ADEs, MPEs, and RVs provides for a de-
`tailed analysis of the specific impact of CPOE on
`different types of errors.
`In this study, CPOE significantly reduced all cate-
`gories of errors. MPEs and RVs were virtually elim-
`inated, and potential ADEs were reduced by 40.9%.
`In addition, during the study, there were no reports
`of errors caused by the CPOE system, including no
`reports of orders being entered on the wrong patient.
`MPEs and RVs often lead to confusion and lack of
`efficiency as a result of incorrect or missing informa-
`tion that requires interpretation and clarification by
`pharmacy and nursing personnel. Our study dem-
`onstrated that a major benefit of CPOE is the en-
`hancement of communication between health care
`professionals that subsequently decreases the possi-
`ble misinterpretation of medication orders.
`Potential ADEs were significantly reduced (P ⬍
`.001) but not nearly to the extent of MPEs and RVs.
`Potential ADEs were identified as errors in which
`incorrect or inappropriate information was provided
`or patient-specific factors were not taken into ac-
`count and potential injury could occur to the patient
`if the medication were received as ordered. Overall,
`most types of potential ADEs, including duplicate
`therapy, wrong drug, wrong units, allergy, and drug
`interactions, were eliminated or significantly re-
`duced. This error reduction, when extrapolated an-
`nually, would equate to a decrease of approximately
`300 instances per year in which a potential ADE was
`prevented. However, errors involving dose and in-
`terval showed no significant difference between pre-
`CPOE and post-CPOE. This may be explained by the
`lack of decision support, on initial CPOE implemen-
`tation, that would assist the prescriber in choosing an
`age- and indication-specific dose and interval for the
`patient. This is an area in which additional enhance-
`ments to CPOE systems are needed. Targeted deci-
`sion support associated with CPOE was shown to be
`effective in adult inpatients with renal insufficiency
`by Chertow et al.18 Decision support tools focused on
`pediatric issues such as weight-based calculations for
`infusions and age-specific dosing guidelines may re-
`sult in additional reductions in these types of errors.
`
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`Our study evaluated medication errors that occur
`at the time of physician ordering. The prevention of
`actual ADEs involves multiple facets of the medica-
`tion delivery process. Kaushal et al1 showed that the
`frequency of preventable ADEs is very low (0.05 per
`100 orders). Despite the significant number of errors
`in the ordering phase of medication delivery, our
`study was not appropriately powered to evaluate the
`impact of CPOE on overall preventable ADEs. An
`appropriately powered study would require a sam-
`ple size that is 20 times the number evaluated in our
`study. Another limitation of our study is that we did
`not investigate how these errors were detected by
`other components of the medication use system, such
`as verification of the order by a pediatric pharmacist
`or review of the order by nursing staff before admin-
`istration.
`Medication error rates have not been well studied
`in pediatrics. The rate reported in this study may
`seem elevated because of our conservative definition
`of errors in the medication ordering process. Limited
`data are available on error rates associated with med-
`ication ordering in the pediatric critical care setting.
`With this study, we have established an error rate for
`a multidisciplinary PCCU that serves a patient pop-
`ulation that is broad in both age and disease state.
`Although CPOE offers significant advantages in
`almost eliminating MPEs and RVs, CPOE is not the
`sole solution for preventing potential ADEs. The ad-
`dition of decision support has previously been
`shown to increase the effectiveness of CPOE in pre-
`venting medication errors in adult patients.6,18 De-
`veloping features that accommodate the wide range
`of ages and weights found in pediatric patients is
`complex.
`Incorporating pediatric-specific dosing
`guidelines and calculators for continuous infusions
`may prove to reduce the incidence of these types of
`errors. Additional evaluation is needed to determine
`the benefits of enhancing CPOE with additional de-
`cision support designed for the pediatric population.
`Specifically, the issues of gestational age, postnatal
`age, and rapid weight changes in neonatal patients
`are currently being incorporated into WizOrder in
`preparation for implementation in our neonatal in-
`tensive care unit. Unfortunately, pediatrics is a small
`portion of the overall CPOE market and limited fi-
`nancial rewards may prevent commercial vendors
`from committing the necessary resources for devel-
`opment of these tools.
`
`CONCLUSIONS
`In conclusion, CPOE significantly reduced and al-
`most completely eliminated MPEs and RVs while
`still demonstrating a significant reduction in the fre-
`quency of potential ADEs. CPOE offers significant
`
`benefits, including ensuring legible and complete
`physician orders. Incorporation of pediatric-specific
`decision support tools into CPOE systems may result
`in even further reductions of potential ADEs leading
`to improved patient safety. Additional evaluation of
`these safety features is needed and will be the focus
`of future studies.
`
`ACKNOWLEDGMENTS
`We do not have any financial ties or obligations to the com-
`mercialization process of WizOrder. This study was not supported
`in any manner by McKesson (Atlanta GA).
`We acknowledge Fred R. Hargrove, RPh, for valuable technical
`assistance with the CPOE WizOrder system and data retrieval.
`
`REFERENCES
`1. Kaushal R, Bates DW, Landrigan C, et al. Medication errors and adverse
`drug events in pediatric inpatients. JAMA. 2001;285:2114–2120
`2. Kaushal R, Barker KN, Bates DW. How can information technology
`improve patient safety and reduce medication error in children’s health
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`3. Bates DW, Boyle DL, Vander Vliet MB, Schneider J, Leape L. Relation-
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`ARTICLES
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`Petition for Inter Partes Review of US 8,648,106
`Amneal Pharmaceuticals LLC – Exhibit 1041 – Page 63
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`Computerized Physician Order Entry and Medication Errors in a Pediatric
`Critical Care Unit
`Amy L. Potts, Frederick E. Barr, David F. Gregory, Lorianne Wright and Neal R.
`Patel
` 2004;113;59
`Pediatrics
`
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`
`Computerized Physician Order Entry and Medication Errors in a Pediatric
`Critical Care Unit
`Amy L. Potts, Frederick E. Barr, David F. Gregory, Lorianne Wright and Neal R.
`Patel
` 2004;113;59
`Pediatrics
`
`The online version of this article, along with updated information and services, is
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`PEDIATRICS is the official journal of the American Academy of Pediatrics. A monthly
`publication, it has been published continuously since 1948. PEDIATRICS is owned,
`published, and trademarked by the American Academy of Pediatrics, 141 Northwest Point
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