BackgroundMedication errors can occur at any of the three steps of the medication use process: prescribing, dispensing and administration. We aimed to determine the incidence, type and clinical importance of drug administration errors and to identify risk factors.MethodsProspective study based on disguised observation technique in four wards in a teaching hospital in Paris, France (800 beds). A pharmacist accompanied nurses and witnessed the preparation and administration of drugs to all patients during the three drug rounds on each of six days per ward. Main outcomes were number, type and clinical importance of errors and associated risk factors. Drug administration error rate was calculated with and without wrong time errors. Relationship between the occurrence of errors and potential risk factors were investigated using logistic regression models with random effects.ResultsTwenty-eight nurses caring for 108 patients were observed. Among 1501 opportunities for error, 415 administrations (430 errors) with one or more errors were detected (27.6%). There were 312 wrong time errors, ten simultaneously with another type of error, resulting in an error rate without wrong time error of 7.5% (113/1501). The most frequently administered drugs were the cardiovascular drugs (425/1501, 28.3%). The highest risks of error in a drug administration were for dermatological drugs. No potentially life-threatening errors were witnessed and 6% of errors were classified as having a serious or significant impact on patients (mainly omission). In multivariate analysis, the occurrence of errors was associated with drug administration route, drug classification (ATC) and the number of patient under the nurse's care.ConclusionMedication administration errors are frequent. The identification of its determinants helps to undertake designed interventions.

EudraCT Number: 2012-000232-25; clinicaltrials.gov Identifier: NCT02184819.

ContextDrug administration in the hospital setting is the last barrier before a possible error reaches the patient.ObjectivesWe aimed to analyze the prevalence and nature of administration error rate detected by the observation method.Data SourcesEmbase, MEDLINE, Cochrane Library from 1966 to December 2011 and reference lists of included studies.Study SelectionObservational studies, cross-sectional studies, before-and-after studies, and randomized controlled trials that measured the rate of administration errors in inpatients were included.Data ExtractionTwo reviewers (senior pharmacists) independently identified studies for inclusion. One reviewer extracted the data; the second reviewer checked the data. The main outcome was the error rate calculated as being the number of errors without wrong time errors divided by the Total Opportunity for Errors (TOE, sum of the total number of doses ordered plus the unordered doses given), and multiplied by 100. For studies that reported it, clinical impact was reclassified into four categories from fatal to minor or no impact. Due to a large heterogeneity, results were expressed as median values (interquartile range, IQR), according to their study design.ResultsAmong 2088 studies, a total of 52 reported TOE. Most of the studies were cross-sectional studies (N=46). The median error rate without wrong time errors for the cross-sectional studies using TOE was 10.5% [IQR: 7.3%-21.7%]. No fatal error was observed and most errors were classified as minor in the 18 studies in which clinical impact was analyzed. We did not find any evidence of publication bias.ConclusionsAdministration errors are frequent among inpatients. The median error rate without wrong time errors for the cross-sectional studies using TOE was about 10%. A standardization of administration error rate using the same denominator (TOE), numerator and types of errors is essential for further publications.

BackgroundDrug prescribing errors are frequent in the hospital setting and pharmacists play an important role in detection of these errors. The objectives of this study are (1) to describe the drug prescribing errors rate during the patient's stay, (2) to find which characteristics for a prescribing error are the most predictive of their reproduction the next day despite pharmacist's alert (i.e. override the alert).MethodsWe prospectively collected all medication order lines and prescribing errors during 18 days in 7 medical wards' using computerized physician order entry. We described and modelled the errors rate according to the chronology of hospital stay. We performed a classification and regression tree analysis to find which characteristics of alerts were predictive of their overriding (i.e. prescribing error repeated).Results12 533 order lines were reviewed, 117 errors (errors rate 0.9%) were observed and 51% of these errors occurred on the first day of the hospital stay. The risk of a prescribing error decreased over time. 52% of the alerts were overridden (i.e error uncorrected by prescribers on the following day. Drug omissions were the most frequently taken into account by prescribers. The classification and regression tree analysis showed that overriding pharmacist's alerts is first related to the ward of the prescriber and then to either Anatomical Therapeutic Chemical class of the drug or the type of error.ConclusionsSince 51% of prescribing errors occurred on the first day of stay, pharmacist should concentrate his analysis of drug prescriptions on this day. The difference of overriding behavior between wards and according drug Anatomical Therapeutic Chemical class or type of error could also guide the validation tasks and programming of electronic alerts.

Introduction and ObjectivesNumerous studies have assessed cost-effectiveness of different treatment modalities for stable angina. Direct comparisons, however, are uncommon. We therefore set out to compare the efficacy and mean cost per patient after 1 and 3 years of follow-up, of the following treatments as assessed in randomized controlled trials (RCT): medical therapy (MT), percutaneous coronary intervention (PCI) without stent (PTCA), with bare-metal stent (BMS), with drug-eluting stent (DES), and elective coronary artery bypass graft (CABG).MethodsRCT comparing at least two of the five treatments and reporting clinical and cost data were identified by a systematic search. Clinical end-points were mortality and myocardial infarction (MI). The costs described in the different trials were standardized and expressed in US $ 2008, based on purchasing power parity. A network meta-analysis was used to compare costs.ResultsFifteen RCT were selected. Mortality and MI rates were similar in the five treatment groups both for 1-year and 3-year follow-up. Weighted cost per patient however differed markedly for the five treatment modalities, at both one year and three years (P<0.0001). MT was the least expensive treatment modality: US $3069 and 13 864 after one and three years of follow-up, while CABG was the most costly: US $27 003 and 28 670 after one and three years. PCI, whether with plain balloon, BMS or DES came in between, but was closer to the costs of CABG.ConclusionsAppreciable savings in health expenditures can be achieved by using MT in the management of patients with stable angina.

This study strongly suggests that an alert system would be complementary to the pharmacists' activity and contribute to drug prescription safety.

The objective of this case report is to evaluate the use of a clinical data warehouse coupled with a clinical information system to test and refine alerts for medication orders control before they were fully implemented. A clinical decision rule refinement process was used to assess alerts. The criteria assessed were the frequencies of alerts for initial prescriptions of 10 medications whose dosage levels depend on renal function thresholds. In the first iteration of the process, the frequency of the 'exceeds maximum daily dose' alerts was 7.10% (617/8692), while that of the 'under dose' alerts was 3.14% (273/8692). Indicators were presented to the experts. During the different iterations of the process, 45 (16.07%) decision rules were removed, 105 (37.5%) were changed and 136 new rules were introduced. Extensive retrospective analysis of physicians' medication orders stored in a clinical data warehouse facilitates alert optimization toward the goal of maximizing the safety of the patient and minimizing overridden alerts.

No abstract