Objective: The goal was to determine the impact on medication prescribing errors of adding a pediatric medication list (quicklist) to a computerized physician order entry system in a pediatric emergency department.
Methods: The quicklist is a drug dosing support tool that targets the most common medications in our clinical setting. We performed a retrospective comparison of orders from 420 randomly selected visits before and after quicklist introduction. Error rates were analyzed with respect to urgency level, physician training level, and patient age. The quicklist was examined for frequency of use and error rates.
Results: The 840 patient visits (420 before intervention and 420 after intervention) generated 724 medication orders, which contained 156 medication prescribing errors (21%). The groups did not differ with respect to urgency level, physician training level, or patient age. There were significant decreases in the rate of errors per 100 visits, from 24 to 13 errors per 100 visits, and in the rate of errors per 100 orders, from 31 to 14 errors per 100 orders. The decrease in the error rates did not vary according to urgency score, age group, or physician training level. The quicklist was used in 30% of the orders in the postintervention group. In this group, the error rate was 1.9 errors per 100 orders when the quicklist was used, compared with 18.3 errors per 100 orders when the list was not used. Errors of wrong formulation, allergy, drug-drug interaction, and rule violations were eliminated.
Conclusion: The introduction of the quicklist was followed by a significant reduction in medication prescribing errors. A list with dosing support for commonly used pediatric medications may help adapt computerized physician order entry systems designed for adults to serve pediatric populations more effectively.
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http://dx.doi.org/10.1542/peds.2007-3064 | DOI Listing |
Am J Health Syst Pharm
January 2025
Department of Pharmacy, Trinity Health Muskegon Hospital, Muskegon, MI, USA.
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View Article and Find Full Text PDFSpectrochim Acta A Mol Biomol Spectrosc
January 2025
Department of Bioresource Engineering, McGill University, Macdonald Campus, 21111 Lakeshore Road, Ste-Anne-de-Bellevue, QC H9X 3V9, Canada.
This study aims to develop rapid and non-invasive methods based on near-infrared hyperspectral imaging and chemometrics for quantitative prediction of chemical compositions of pea-derived products. Hyperspectral imaging was used to acquire images from pea processing streams, namely pea flour, pea protein concentrate, and pea protein isolate. The PLS algorithm was used to develop quantitative prediction models based on the relationship between the hyperspectral image data and the chemical compositions of the pea products, including moisture, protein, ash, insoluble fiber, and total starch.
View Article and Find Full Text PDFScand J Clin Lab Invest
January 2025
Department of Medical Biochemistry, Health Science University, Istanbul Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.
This study assessed the reliability of Roche Accu-Chek Inform II glucometers in a real-world setting. A retrospective analysis was conducted on 6,695 paired results. Capillary samples were tested using Roche Accu-Chek Inform II glucometers, while venous samples were analyzed using Roche Cobas c503/702 analyzers.
View Article and Find Full Text PDFDisabil Rehabil
January 2025
Faculty of Nursing and Health Sciences, Nord University, Bodø, Norway.
Purpose: The Trunk Impairment Scale-modified Norwegian version (TIS-modNV) measures trunk control for clinical and research purposes. This study examined the validity and reliability of the TIS-modNV in people with multiple sclerosis (pwMS).
Materials And Methods: Sixty-eight pwMS (mild to moderate) participated.
Pharmaceutics
January 2025
Department of Mathematical and Physical Sciences, Catholic University of Temuco, Temuco 4813302, Chile.
: A previous study investigated the in vitro release of methylene blue (MB), a widely used cationic dye in biomedical applications, from nanocellulose/nanoporous silicon (NC/nPSi) composites under conditions simulating body fluids. The results showed that MB release rates varied significantly with the nPSi concentration in the composite, highlighting its potential for controlled drug delivery. To further analyze the relationship between diffusion dynamics and the MB concentration, this study developed a finite element (FE) method to solve Fick's equations governing the drug delivery system.
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