Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The impact of a closed-loop electronic prescribing and administration system on prescribing errors, administration errors and staff time: a before-and-after study
319
Zitationen
5
Autoren
2007
Jahr
Abstract
OBJECTIVES: To assess the impact of a closed-loop electronic prescribing, automated dispensing, barcode patient identification and electronic medication administration record (EMAR) system on prescribing and administration errors, confirmation of patient identity before administration, and staff time. DESIGN, SETTING AND PARTICIPANTS: Before-and-after study in a surgical ward of a teaching hospital, involving patients and staff of that ward. INTERVENTION: Closed-loop electronic prescribing, automated dispensing, barcode patient identification and EMAR system. MAIN OUTCOME MEASURES: Percentage of new medication orders with a prescribing error, percentage of doses with medication administration errors (MAEs) and percentage given without checking patient identity. Time spent prescribing and providing a ward pharmacy service. Nursing time on medication tasks. RESULTS: Prescribing errors were identified in 3.8% of 2450 medication orders pre-intervention and 2.0% of 2353 orders afterwards (p<0.001; chi(2) test). MAEs occurred in 7.0% of 1473 non-intravenous doses pre-intervention and 4.3% of 1139 afterwards (p = 0.005; chi(2) test). Patient identity was not checked for 82.6% of 1344 doses pre-intervention and 18.9% of 1291 afterwards (p<0.001; chi(2) test). Medical staff required 15 s to prescribe a regular inpatient drug pre-intervention and 39 s afterwards (p = 0.03; t test). Time spent providing a ward pharmacy service increased from 68 min to 98 min each weekday (p = 0.001; t test); 22% of drug charts were unavailable pre-intervention. Time per drug administration round decreased from 50 min to 40 min (p = 0.006; t test); nursing time on medication tasks outside of drug rounds increased from 21.1% to 28.7% (p = 0.006; chi(2) test). CONCLUSIONS: A closed-loop electronic prescribing, dispensing and barcode patient identification system reduced prescribing errors and MAEs, and increased confirmation of patient identity before administration. Time spent on medication-related tasks increased.
Ähnliche Arbeiten
Machine Learning in Medicine
2019 · 3.752 Zit.
Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care
2006 · 3.173 Zit.
Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes
2005 · 2.967 Zit.
Studies in health technology and informatics
2008 · 2.903 Zit.
An overview of clinical decision support systems: benefits, risks, and strategies for success
2020 · 2.707 Zit.