Research and applications
`
`1Department of Pharmacy,
`Hospital General Universitario
`Gregorio Maran˜o´n, Madrid,
`Spain
`2Department of
`Gastroenterology, Hospital
`General Universitario Gregorio
`Maran˜o´n, Madrid, Spain
`
`Correspondence to
`Carmen Guadalupe
`Rodriguez-Gonzalez, Pharmacy,
`Hospital General Universitario
`Gregorio Maran˜o´n, Madrid
`28007, Spain; crodriguezg.
`hgugm@salud.madrid.org
`
`Received 26 April 2011
`Accepted 8 August 2011
`Published Online First
`2 September 2011
`
`Prevalence of medication administration errors in two
`medical units with automated prescription
`and dispensing
`Carmen Guadalupe Rodriguez-Gonzalez,1 Ana Herranz-Alonso,1
`Maria Luisa Martin-Barbero,1 Esther Duran-Garcia,1 Maria Isabel Durango-Limarquez,2
`Paloma Herna´ndez-Sampelayo,2 Maria Sanjurjo-Saez1
`
`ABSTRACT
`Objective To identify the frequency of medication
`administration errors and their potential risk factors in
`units using a computerized prescription order entry
`program and profiled automated dispensing cabinets.
`Design Prospective observational study conducted
`within two clinical units of the Gastroenterology
`Department in a 1537-bed tertiary teaching hospital in
`Madrid (Spain).
`Measurements Medication errors were measured
`using the disguised observation technique. Types of
`medication errors and their potential severity were
`described. The correlation between potential risk factors
`and medication errors was studied to identify potential
`causes.
`Results In total, 2314 medication administrations to 73
`patients were observed: 509 errors were recorded
`(22.0%)d68 (13.4%) in preparation and 441 (86.6%) in
`administration. The most frequent errors were use of
`wrong administration techniques (especially concerning
`food intake (13.9%)), wrong reconstitution/dilution
`(1.7%), omission (1.4%), and wrong infusion speed
`(1.2%). Errors were classified as no damage (95.7%), no
`damage but monitoring required (2.3%), and temporary
`damage (0.4%). Potential clinical severity could not be
`assessed in 1.6% of cases. The potential risk factors
`morning shift, evening shift, Anatomical Therapeutic
`Chemical medication class antacids, prokinetics,
`antibiotics and immunosuppressants, oral administration,
`and intravenous administration were associated with
`a higher risk of administration errors. No association was
`found with variables related to understaffing or nurse’s
`experience.
`Conclusions Medication administration errors persist in
`units with automated prescription and dispensing. We
`identified a need to improve nurses’ working procedures
`and to implement a Clinical Decision Support tool that
`generates recommendations about scheduling according
`to dietary restrictions, preparation of medication before
`parenteral administration, and adequate infusion rates.
`
`INTRODUCTION AND BACKGROUND
`The importance of proper use of drugs is well
`documented in numerous publications on patient
`safety and quality of healthcare, all of which have
`highlighted the health impact of medication errors
`and the need for effective safety practices. The
`Harvard Medical Practice Study,1 which analyzed
`the damage caused by common errors in medical
`care in New York State in 1984, estimated that
`
`3.7% of hospitalized patients experience an adverse
`event during admission, the most common being
`medication-related complications (19%, of which
`45% were preventable),
`followed by surgical
`wound infections (14%) and technical complica-
`tions (13%). The ENEAS Study in Spain showed
`that 4% of hospitalized patients experienced
`medication-related adverse events, that 37% of all
`adverse events documented were associated with
`medication, and that 35% of these events were
`preventable.2
`The complexity of the medication administra-
`tion process is such that errors can appear at one,
`some, or even all the stages between prescription
`and administration. In fact, the frequency of errors
`has been estimated to be 39% during the prescrip-
`tion process, 12% during the transcription process,
`11% during the dispensing process, and 38% during
`the administration process.3 4 However, most errors
`that actually affect a hospitalized patient occur
`when a dose of medication is incorrectly adminis-
`tered at the bedside. Thus, technologies such as
`automated dispensing cabinets (ADCs) at the point
`of care and the electronic medication administra-
`tion record (e-MAR) verified using barcode medi-
`cation administration (BCMA) aim to reduce
`administration errors.
`However, very few studies have shown safer
`administration with both these technologies,5e13
`especially with ADCs, for which only three studies
`have been published.5e7 Furthermore, experience
`with these technologies is still limited in Spain,
`where only 13% of hospitals have implemented
`ADCs, 5% have implemented e-MAR, and none use
`the BCMA system throughout the hospital, due to
`the difficulty and cost of developing and main-
`taining such complex infrastructures.14
`Since 2003, our institution has effectively used
`a computerized prescription order entry (CPOE)
`program with online pharmacy validation and
`decentralized profiled ADCs for 900 beds. However,
`administration errors are still a major problem,
`because, unlike BCMA, these technologies cannot
`ensure the five rights of the administration process,
`as it is not possible to automatically cross-check the
`prescription with the prepared medication just
`before each administration.
`
`OBJECTIVE
`The objective was to identify the frequency of
`medication preparation and administration errors
`
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`J Am Med Inform Assoc 2012;19:72e78. doi:10.1136/amiajnl-2011-000332
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`as well as the potential risk factors for these errors in two
`clinical units using a CPOE program and profiled ADCs.
`
`observation period started when a nurse entered the patient’s
`name and began retrieving medication from the ADC.
`
`Research and applications
`
`MATERIALS AND METHODS
`Design
`This was a prospective observational study performed using
`a disguised observation technique.
`
`Setting
`The study was conducted in two gastroenterology units (30 and
`29 beds) in a 1537-bed tertiary teaching hospital in Madrid
`(Spain).
`Since 2005, gastroenterologists have entered the prescription
`in a CPOE system. The pharmacists’ role consists of continuous
`centralized order validation, except during the night shift. Drugs
`are dispensed using profiled-ADCs (Pyxis System), from which
`they can be retrieved by nurses once prescribed and validated by
`the clinical pharmacist. Administration is registered manually in
`a semielectronic paper format (computer-generated, signed by
`hand). This patient-specific medication administration record
`(MAR) is printed once daily and serves as a paper reference for
`the medications to be given to patients and completed admin-
`istrations for that day. The hospital’s CPOE system has to be
`checked regularly for new or modified medication orders. Any
`changes required a new MAR to be printed, as this document is
`used to retrieve medication from the ADC.
`High-volume medication administration times are 09:00,
`12:00, 13:00, 16:00, and 20:00; most medications are adminis-
`tered at 09:00.
`In both units medication is administered by qualified nurses,
`except for oral medication at 13:00 and 20:00, which is admin-
`istered by nursing assistants.
`
`Observation procedures
`Observations were scheduled on weekdays and weekends and
`during all shifts. Six pharmacists and five nurses were trained to
`make the observations unobtrusively and assess the error rate.
`Training consisted of two previous informative sessions devel-
`oped by one of the pharmacists, in which the data collection
`form and examples of medications errors were discussed.
`Before the study began, the team explained the study meth-
`odology to the nursing staff of each unit, namely, that the
`purpose of the study was to examine the functionality of the
`CPOE and ADCs. The term ‘medication error ’ was deliberately
`avoided. Only nursing managers knew the real purpose of the
`study. Nurses were also informed that the observer could not
`answer any medication-related questions and should be referred
`to the satellite pharmacy for answers to medication-related
`questions.
`Since nurses were the subjects of our study, informed consent
`from the patient was not required by the hospital’s institutional
`review board. After contacting the nurse at the beginning of the
`medication administration round, emphasizing that
`study
`participation was entirely voluntary, oral informed consent was
`obtained.
`To prevent interference with nursing workflow, a maximum of
`two observers were assigned to each study unit during one
`observation session. Each observer studied the preparation and
`administration process with the same nurse during one shift per
`day. The observers were instructed to intervene if they witnessed
`actions that could lead to an adverse event. The prescribed
`medication was determined by printing the paper MAR of each
`observed patient and contrasting it with that of the nurse. The
`
`Definitions
`Medication is defined as any ordered drug (except oxygen) and
`intravenous fluid by any route. A dose of intravenous fluid is the
`unit that is ordered, even if the contents are administered over
`hours.
`An administation error was defined as any discrepancy
`between prescription and administration and was categorized
`according to the Ruiz Jarabo 2008 taxonomy, as follows15: wrong
`patient, wrong drug, wrong dose, wrong pharmaceutical form,
`wrong route, wrong preparation/manipulation/conditioning
`technique, wrong administration technique due to food intake,
`wrong administration technique due to other causes (eg, physi-
`cochemical incompatibilites in parenteral administrations, wrong
`crushing), wrong administration speed, wrong time, wrong
`frequency, wrong treatment duration, wrong store, damaged
`drug, omission, and other. The ‘other ’ category was further
`classified by the investigators after the study was completed. A
`wrong-time-of-administration error was considered as adminis-
`tration more than 15 min before or after the scheduled admin-
`istration in the case of emergency prescriptions, 30 min in the
`case of treatments given every 6 h or more, and 1 h in the case of
`treatments every 8 h or less. Wrong preparation/manipulation/
`conditioning technique, wrong administration technique, and
`wrong administration speed were defined as a discrepancy with
`the recommendations of the summary of product characteristics.
`In cases of doubt, the manufacturer was consulted.
`In addition, the cause and the severity of the error were eval-
`uated by the observer and two senior pharmacists, respectively,
`and according to the Ruiz Jarabo 2008 taxonomy.15 If a disagree-
`ment arose regarding the severity of error, a third evaluator
`reviewed the observation and provided a recommendation.
`This study did not include adverse drug reactions or non-
`preventable adverse events.
`
`Data analysis
`The number of observations needed to adequately power this
`study was based on the results of a previous study investigating
`the administration error rate before and after implementing
`ADC in a French ICU setting.7 Assuming a similar baseline error
`rate after implementing this technology of 13.5%, an a of 0.05,
`and a precision of 61.5%, at least 1994 medication administra-
`tions had to be observed.
`The medication error rate was calculated by dividing the
`number of errors by the total opportunities for error (OEs). OEs
`were defined as the sum of observed administrations and
`omitted medications. As wrong-time errors were generally
`considered less severe than other errors, overall results were
`reported as total errors and errors excluding wrong-time errors.
`The variables registered and entered into the database (MS
`Access 2003) were as follows: patient age and gender; medicine
`(name, dosage form, and Anatomical Therapeutic Chemical
`(ATC) class); administration route; number of medicines per
`shift and patient; whether the expiry date of the medication had
`been checked or not; whether the medication had been labeled
`correctly with patient name, drug and dose or not; whether the
`medication had been retrieved from the ADC just before
`administration or not; whether the medication was adminis-
`tered by the nurse or the nursing assistant; whether the
`administration was documented or not; day and shift of
`administration; age of nurse; type of nurse (career nurse or not);
`experience in the unit (months); number of beds the nurse is
`
`J Am Med Inform Assoc 2012;19:72e78. doi:10.1136/amiajnl-2011-000332
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`Research and applications
`
`responsible for; whether an error has been made or not; error
`category; cause of error; and severity of the error.
`Univariate and multivariate logistic regression analyses were
`performed to study the association between potential risk
`factors and the occurrence of errors. All p values were two-tailed.
`Statistical significance was set at p<0.05.
`The data were analyzed using the Statistical Package for Social
`Sciences (PAWS Statistics) V.18.0.
`
`RESULTS
`Subjects were studied for 1 week in February 2010, during which
`time 2314 OEs were observed.
`Study unit characteristics during the study period and the
`observation characteristics are summarized in tables 1, 2,
`respectively.
`The total medication error rate was 22.0%d20.7% if 30 cases
`of wrong-time errors were excludeddand errors involved 70
`different drugs. Ten administrations accumulated more than one
`error. Sixty-eight (13.4%) errors occurred in the preparation
`process and 441 (86.6%) in the administration process. The
`inter-rater
`reliability for classifying severity was moderate
`(k¼0.40). Errors were classified as no damage in 95.7% of cases,
`no damage with monitoring in 2.3% of cases, and temporary
`damage in 0.4% of cases. In 1.6% of cases, the potential clinical
`severity could not be assessed. Only 18 interventions were
`deemed necessary by the observer.
`All types of errordexcluding wrong-time errorsdand their
`causes and clinical severity are shown in table 3.
`The most common error was wrong technique due to food
`intake (mainly proton-pump inhibitors (PPIs) (39.9%), immu-
`nosuppressive drugs (20.6%), and prokinetics (15.9%)). The
`main resason was a lack of use of standarized procedures, as
`nurses or nursing assistants often administer the medication
`without separating those with dietary restrictions in a different
`container or warning the patient that it has to be taken on an
`empty stomach.
`The next most common error was wrong reconstitution/
`dilution of parenteral drugs: in 8.6% of intravenous adminis-
`trations, the drug was not reconstituted/diluted according to the
`recommendations of the summary of product characteristics.
`The main drugs involved in this type of error were vancomycin,
`piperacillin/tazobactam, omeprazole, and imipenem.
`Thirty-two cases of omission were detected, due mainly to
`a lack of stock in the ADCs, lapse of concentration, lack of use of
`standardized procedures (when the nurse decided not
`to
`administer the drug scheduled), and problems with communi-
`cation between the physician and the nurse when a modification
`was made on the prescription. Of these 32 errors, one case
`
`Table 1 Study units and staffing characteristics during
`the study period
`No of admissions
`No of patients discharged
`Occupancy (%)
`Length of stay, days
`Patient/bed rotation
`No of deaths
`Admissions to ward from emergency room (%)
`No of nurses observed
`No of beds/nurse, median (p25ep75)
`Career nurses (%)
`Nurse age, median (p25ep75)
`Experience in the unit, months, median (p25ep75)
`
`58
`64
`129.10
`9.19
`3.58
`1
`55.17
`23
`8 (8e10)
`52.17
`39 (26e42)
`24 (9e246)
`
`Table 2 Observation characteristics of study
`No of patients
`Male (%)
`Age, median (p25ep75)
`Total no of OE
`Median (range) OE per patient during the
`observational session (p25ep75)
`Total no of different drugs ordered
`Anatomical Therapeutic Chemical medication class no (%)
`Gastrointestinal
`Anti-infective agents
`Blood
`Cardiovascular
`Respiratory
`Neurological
`Antineoplastic and immunomodulating agents
`Musculoskeletal
`Hormones
`Various
`Gynecological
`Dermatological
`Antiparasitic agents
`No (%) of OE per administration route
`Oral
`Intravenous
`Inhaled
`Subcutaneous
`Continuous intravenous perfusion
`Transdermal
`Rectal
`Topical
`Intramuscular
`Enteral catheter
`No (%) of observations
`Morning
`Evening
`Night
`Weekend observations (%)
`No (%) of observations
`Pharmacist
`Nurse
`
`73
`64.4
`63 (51e75)
`2314
`7 (5e9)
`
`213
`
`857 (37.0)
`297 (12.8)
`286 (12.4)
`230 (9.9)
`171 (7.4)
`171 (7.4)
`116 (5.0)
`73 (3.2)
`57 (2.5)
`27 (1.2)
`15 (0.6)
`6 (0.3)
`8 (0.3)
`
`1560 (67.4)
`402 (17.4)
`125 (5.4)
`121 (5.2)
`71 (3.1)
`17 (0.7)
`9 (0.4)
`6 (0.3)
`2 (0.1)
`1 (0.004)
`
`1134 (49.0)
`1018 (44.0)
`162 (7.0)
`33.8
`
`57.3
`42.6
`
`OE, opportunities for error, defined as the sum of observed administrations and omitted
`medications.
`
`(omission of transdermal fentanyl) was categorized as potential
`temporary damage and five cases (omission of parenteral
`vitamin K, inhaled ipratropium, propranolol, and two doses of
`intravenous metoclopramide) as no damage but potential
`monitoring could have been required. In three cases, the clinical
`severity could not be determined.
`Twenty-seven cases of wrong infusion speed were detected,
`with albumin, levofloxacin, and paracetamol as the main drugs
`involved.
`The remaining errors had an incidence of less than 1%. In the
`case of wrong dose, the main causes were withdrawal from the
`ADC of an amount less than that prescribed due to a lapse of
`concentration or because the nurse forgot to dispense the exact
`dose prescribed after retrieval from the ADC. The error would
`not have harmed the patient, except for the administration of
`sodium bicarbonate 1 M instead of 1/6 M in one case and near
`administration of half the dose prescribed for albumin in two
`cases. Twelve errors of wrong adherence were detected, because
`the nurse did not verify whether the patient had taken the
`medication. In the case of wrong route, six out of seven errors
`were due to the administration of ondansetron intravenously
`
`74
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`Table 3 Administration errors classified by type of error, cause and clinical severity
`Error
`rate (%)
`
`Type of error excluding wrong-time errors
`
`N
`
`Cause
`
`Wrong technique due to food intake
`
`321
`
`13.9
`
`Wrong preparation
`Wrong reconstitution (volume, fluid)
`Wrong dilution (volume, fluid)
`Omission
`
`40
`8
`32
`32
`
`1.7
`0.3
`1.4
`1.4
`
`Wrong infusion speed
`
`27
`
`1.2
`
`Wrong dose
`
`19
`
`0.8
`
`Wrong patient adherence
`Wrong route
`
`Wrong duration of treatment
`
`Wrong drug
`
`Wrong frequency
`
`Wrong technique other reasons
`
`Wrong store
`
`Wrong pharmaceutical form
`
`13
`7
`
`6
`
`5
`
`3
`
`3
`
`2
`
`1
`
`0.6
`0.3
`
`0.3
`
`0.2
`
`0.1
`
`0.1
`
`0.1
`
`0.0
`
`Lack of standardized procedures
`Lack of knowledge about the drug
`Lack of knowledge about the drug
`
`Lack of stock in the ADCs
`Lapse of concentration
`Lack of standardized procedures
`Communication problems
`Lack of knowledge about the patient
`
`Stress
`Error in infusion speed calculation
`
`Lapse of concentration
`Communication problems
`Lack of knowledge about the drug
`Error in preparing the drug
`Lack of knowledge about the patient
`Lack of knowledge about the drug
`Lack of standardized procedures
`Lapse of concentration
`Communication problems
`
`Communication problems
`Lack of standardized procedures
`Lack of stock in the ADCs
`Lack of stock in the ADCs
`Communication problems
`Stress
`Lack of knowledge about the drug
`
`Lack of standardized procedures
`Lack of packing in unit doses
`Error in preparing the drug
`
`Research and applications
`
`N
`
`272
`49
`40
`
`9
`8
`8
`3
`2
`
`2
`27
`
`14
`2
`2
`1
`13
`6
`1
`3
`3
`
`2
`2
`1
`2
`1
`1
`2
`
`1
`1
`1
`
`Clinical severity
`
`No damage
`
`No damage
`
`No damage
`
`No damage but
`monitoring was required
`
`Temporary damage and
`monitoring was required
`Unknown
`No damage
`No damage but monitoring
`was required
`Unknown
`No damage
`
`No damage but monitoring
`was required
`
`No damage
`No damage
`
`No damage
`Temporary damage and
`monitoring was required
`No damage
`
`Unknown
`No damage
`
`No damage
`No damage but monitoring
`was required
`No damage
`
`No damage but monitoring
`was required
`e
`
`N
`
`321
`
`40
`
`23
`
`5
`
`1
`
`3
`21
`2
`
`4
`16
`
`3
`
`13
`7
`
`5
`1
`
`4
`
`1
`3
`
`2
`1
`
`2
`
`1
`
`479
`
`Total
`
`479
`
`20.7
`
`e
`
`479
`
`ADCs, automated dispensing cabinet.
`
`rather than orally, because nurses were unaware that the vials
`could be administered by this route. Six cases of wrong duration
`of treatment and five cases of wrong drug were detected, mainly
`because the treatment had been modified by the physician but
`not reported to the nurse (eg, vitamin K was going to be
`administered despite having being stopped in the CPOE, or
`tiotropium was stopped by the physician, and the nurse
`administered tiotropium and ipratropium at the same time).
`Another error worthy of mention was the administration of
`intravenous ipratropium solution by inhalation.
`Finally, although considered less severe than other errors, 30
`cases of wrong-time errors were detected. Antibiotics and fluids
`were the main drugs involved, and the causes were accumula-
`tion of workload, nurse’s decision to make her job easier, and
`lack of drug stock in the ADC.
`The correlation between occurrence of administration errors
`and potential risk factors is shown in table 4 (univariate and
`multivariate analysis). In the multivariate analysis, the factors
`associated with a higher risk of administration errors were as
`follows: morning shift (OR 2.36), evening shift (OR 2.08), ATC
`medication class antacids (OR 18.09), ATC medication class
`prokinetics (OR 16.75), ATC medication class antibiotics (OR
`
`3.10), ATC medication class immunosuppressants (OR 17.26),
`oral administration (OR 2.40), and intravenous administration
`(OR 2.48).
`
`DISCUSSION
`rates and the
`This study focuses on administration error
`potential risk factors that can persist in a manual administration
`process
`that benefits
`from automated prescription and
`dispensing. The study was performed in two units with 10 years
`of experience using this technology.
`The methodology used was direct observation of medication
`administration, which is the most efficient and practical medi-
`cation-error-detection method and one that produces valid and
`reliable results.16e18 Since a common language was necessary to
`standardize diagnosis and systematize the detection, analysis,
`and recording of medication errors, we followed the Ruiz Jarabo
`Group medication-error taxonomy,15 which is an adaptation of
`the National Coordinating Council
`for Medication Error
`Reporting and Prevention taxonomy in the Spanish health
`system. Widely used by hospitals and other healthcare settings
`within the external medication errors reporting system of the
`ISMP-Spain, this taxonomy makes it possible to standardize
`
`J Am Med Inform Assoc 2012;19:72e78. doi:10.1136/amiajnl-2011-000332
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`Research and applications
`
`Table 4 Correlation of administration errors with potential risk factors
`Univariate OR (95% CI)
`
`Multivariate OR (95% CI)
`
`Patient characteristics
`Age (in years)
`Gender
`Female
`Male
`Medication characteristics
`Anatomical Therapeutic
`Chemical medication class
`Antacids
`Prokinetics
`Antibiotics
`Immunosuppressants
`Administration route
`Oral
`Intravenous
`No of medicines/shift/patient
`Organization characteristics
`Expiry date not checked
`Medication labeled incorrectly
`Medication not retrieved from the
`automated dispensing cabinet just
`before administration
`Administration by nursing assistant
`Administration not documented
`Time characteristics
`Working day
`Shift
`Night
`Morning
`Evening
`Nurse’s characteristics
`Age (years)
`Not career nurse
`Experience in the unit (months)
`No of beds under charge
`
`0.99 (0.99 to 1.00)
`
`0.99 (0.99 to 1.00)
`
`Reference category
`1.19 (0.96 to 1.49)
`
`Reference category
`0.97 (0.73 to 1.30)
`
`10.42 (7.57 to 14.34)
`7.52 (4.77 to 11.86)
`1.36 (1.00 to 1.86)
`8.12 (5.31 to 12.44)
`
`1.81 (1.44 to 2.28)
`1.15 (0.88 to 1.47)
`0.97 (0.94 to 1.00)
`
`3.61 (0.47 to 27.50)
`0.53 (0.36 to 0.81)
`0.64 (0.52 to 0.79)
`
`18.09 (12.60 to 25.96)
`16.75 (10.10 to 27.79)
`3.10 (1.98 to 4.85)
`17.26 (10.80 to 27.59)
`
`2.40 (1.34 to 4.30)
`2.48 (1.28 to 4.81)
`0.99 (0.95 to 1.03)
`
`3.30 (0.31 to 34.75)
`1.05 (0.64 to 1.72)
`0.79 (0.56 to 1.10)
`
`0.99 (0.80 to 1.22)
`1.40 (0.82 to 2.39)
`
`0.94 (0.63 to 1.40)
`1.22 (0.61 to 2.42)
`
`1.23 (0.99 to 1.52)
`
`1.57 (0.99 to 2.49)
`
`Reference category
`2.75 (1.58 to 4.77)
`2.93 (1.69 to 5.07)
`
`0.99 (0.98 to 1.00)
`1.08 (0.87 to 1.33)
`1.00 (0.99 to 1.01)
`0.97 (0.94 to 1.00)
`
`Reference category
`2.36 (1.10 to 5.04)
`2.08 (1.02 to 4.22)
`
`1.01 (0.99 to 1.03)
`1.34 (0.97 to 1.86)
`0.97 (0.95 to 1.00)
`1.01 (0.95 to 1.09)
`
`Statistically significant correlations in the multivariate analysis are shown in bold.
`
`description of the errors detected, the drugs involved, the cause
`of error, and the consequences and contributing factors involved.
`The total error rate was high, as approximately one in five
`administrations were imprecise. However, this high incidence
`was due to wrong-technique errors (dietary restrictions); the
`incidence of other errors, excluding wrong-time errors, was
`significantly lower (6.8%). The main reason for such a high error
`rate was the lack of correct nursing working procedures, which
`generates three problems. First, the time schedule for medication
`is defined by nurses who often fail to consult administration
`guidelines; neither the CPOE nor the ADCs provide information
`about which medicines need to be administered on an empty
`stomach. Second, even though staff is aware of dietary restric-
`tions, all the medication needed for the shift is retrieved from
`the ADCs at the beginning of the shift, without separating them
`in a different container. Third, although all the medication is
`removed from the ADCs by nurses using their personal finger-
`print, oral medication at 13:00 and 20:00 is administered by
`nursing assistants, who have less knowledge about dietary
`restrictions.
`Other considerations should be taken into account. Since
`these errors were not preventeddthe observers were instructed
`to prevent only those errors that could produce an adverse
`eventdthe same error was repeated throughout the study;
`hence such a high error rate (128 times for PPIs and 39 and 27
`times for tacrolimus and mycophenolate). In clinical terms,
`
`these errors could not be considered severe, as, in the case of
`PPIs, a reduction in bioavailability or a lack of effectiveness is not
`expected when they are co-administered with food, even though
`the summary of product characteristics recommends adminis-
`tration on an empty stomach. With immunosuppressive drugs,
`the clinical significance would have been significantly higher, but
`plasma concentrations were monitored in all cases. For these
`drugs, nursing staff did follow the schedule established (09:00
`(administration every 24 h) and 09:00 and 21:00 (administration
`every 12 h)), as this is the schedule that best adapts to the
`patient’s lifestyle outside the hospital.
`In any case, we believe it is necessary to improve training in
`oral administration techniques and to change the way nurses
`work in the institution (ie, separating medication with dietary
`restrictions routinely and ensuring that all medications are
`administered by the nurse responsible for the patient). As
`a result of this study, the Pharmacy Department has started to
`adapt and implement the Guidance on the Interdisciplinary Safe
`Use of Automated Dispensing Cabinets, elaborated by the ISMP,
`which includes strict quality monitoring of nursing practice
`using data from the ADC management software.
`Errors that may have been of greater clinical significance were
`much less frequent. No cases of wrong patient were detected,
`and the low incidence of wrong drug and dose was related to the
`introduction of profiled ADCs in the organization. However,
`despite this barrier control in dispensing, these errors still occur
`
`76
`
`J Am Med Inform Assoc 2012;19:72e78. doi:10.1136/amiajnl-2011-000332
`
`Petition for Inter Partes Review of US 8,338,470
`Amneal Pharmaceuticals LLC – Exhibit 1043 – Page 76
`
`

`

`because nurses do not check the electronic prescription just
`before administration; this could have prevented two drug
`errors, 18 dose errors, three treatment duration errors, and four
`omission errors.
`The analysis of potential error severity revealed that almost
`96% of errors would cause no harm (Ruiz Jarabo 2008 taxonomy
`category C). Few of the errors were severe, because, as
`mentioned above, most errors were due to incorrect technique
`and dietary considerations, and very few errors were due to
`wrong drug or dose after implementing ADCs. Although this
`could indicate an excessively precise semantic structure for error
`reporting, it is the only way to detect non-severe errors that
`could be indicators of failures in the medication administration
`process and potentially lead to more severe errors in the long
`term. Our study is limited in that it did not take adverse events
`into account.
`As for the potential risk factors involved, other than the
`positive correlation for PPIs, immunosuppressants, and proki-
`netics, a correlation was found for antibiotics due to problems
`with the reconstitution and dilution technique; this also
`explains the positive correlation for the parenteral route. We did
`not find any correlation between administration errors and
`nurses’ age, category (career or not), or experience, or between
`the number of medicines per shift or number of beds under
`charge. Such a correlation could have been associated with
`understaffing. Finally, although a statistical association could
`not be found between organizational characteristics and error
`rate, we believe it is necessary to improve working procedures in
`units with automated prescription and dispensing (eg, the
`expiry date had been checked in only 0.7% of administrations,
`and 53% of drugs were not retrieved from the ADC just before
`administration). Another critical point was the poor communi-
`cation between the physician and the nurse when treatment
`was modified in the CPOE. This could explain the positive
`correlation between the morning shift and the evening shiftd
`when more treatment modifications were madedand the error
`rate. Also important is the fact that nurses do not cross-check
`the medication prepared with the prescription online just before
`administration.
`Our results cannot generally be compared with those of other
`studies, mainly because of the error-detection method used (ie,
`direct observation versus voluntary reporting or medical chart
`review). Even with direct observation, reported error rates differ.
`These differences could be related to how medication errors are
`defined (eg, many studies define the error in relation to food
`intake as wrong time error, which is then excluded from the
`overall analysis due to its scant clinical relevance), the denomi-
`nator used to calculate the error rate (eg, total doses administered
`vs 1000 patient-days), the type of medication use process (manual
`or automated), and the specific population evaluated (eg, adults,
`children, medical patients, surgical patients, ICU patients).
`In a multicenter study in six hospitals in Catalonia,19 only 2%
`of the 1500 observed administrations involved an error. Omis-
`sion was the most common, representing 40% of the total,
`followed by wrong time and wrong frequency. Only nine wrong
`infusion speed errors were detected, and wrong technique errors
`were not mentioned. These results differ considerably from ours,
`possibly because all the errors found were preventeddmaking it
`difficult to repeat the same type of errordand its undisguised
`methodology and multicenter design could have made it
`difficult to observe and detect the errors consistently in different
`hospitals. However, other studies show a closer error rate: Barker
`et al20 reported a 19% administration error rate in 36 healthcare
`facilities in Georgia and Colorado (USA). This rate is very similar
`
`Research and applications
`
`to ours, except for the 43% in cases of omission, which was an
`uncommon error in our study. Fontan et al21 reported a 23%
`error rate after implementing electronic prescribing and ADC in
`a pediatric nephrology unit, and Bruce and Wong22 reported
`a 25% rate of parenteral drug administration errors by nursing
`staff on an acute medical admissions unit. Three studies
`analyzing the effect of implementing ADCs showed a 10.4%,
`10.6%, and 13.5% error rate after implementation.6 5 7
`The optimal solution for ensuring safety in the administration
`process today seems to be implementation of a BCMA system,
`which makes it possible to check the five rights at the bedside
`(right patient, right drug, right dose, r