Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Exposure to Automated Drug Alerts Over Time
54
Zitationen
5
Autoren
2006
Jahr
Abstract
OBJECTIVE: We tested whether interval exposure to an automated drug alert system that included approximately 2000 drug-drug interaction alerts increased recognition of selected interacting drug pairs. We also examined other perceptions about computerized order entry. RESEARCH DESIGN: We administered cross-sectional surveys in 2000 and 2002 that included more than 260 eligible clinicians in each time period. SUBJECTS: We studied clinicians practicing in ambulatory settings within a Southern California Veterans Affairs Healthcare System and who responded to both surveys (97 respondents). MEASURES: We sought to measure (1) recognition of selected drug-drug and drug-condition interactions and (2) other benefits and barriers to using automated drug alerts. RESULTS: Clinicians correctly categorized similar percentages of the 7 interacting drug-drug pairs at baseline and follow-up (53% vs. 54%, P = 0.51) but improved their overall recognition of the 3 contraindicated drug-drug pairs (51% vs. 60%, P = 0.01). No significant changes from baseline to follow-up were found for the 8 interacting drug-condition pairs (60% vs. 62%, P = 0.43) or the 4 contraindicated drug-condition pairs (52% vs. 56%, P = 0.24). More providers preferred using order entry at follow-up than baseline (63% vs. 45%, P < 0.001). Signal-to-noise ratio remained the biggest reported problem at follow-up and baseline (54 vs. 57%, P = 0.75). In 2002, clinicians reported seeing a median of 5 drug alerts per week (representing approximately 12.5% of prescriptions entered), with a median 5% reportedly leading to an action. CONCLUSIONS: Interval exposure to automated drug alerts had little to no effect on recognition of selected drug-drug interactions. The primary perceived barrier to effective utilization of drug alerts remained the same over time.
Ähnliche Arbeiten
Machine Learning in Medicine
2019 · 3.812 Zit.
Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care
2006 · 3.176 Zit.
Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes
2005 · 2.972 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 · 2.742 Zit.