Factors influencing alert acceptance

• Verfasst von: Seidling, Hanna [VerfasserIn]
• Verfasst von: Phansalkar, Shobha [VerfasserIn]
• Verfasst von: Seger, Diane L [VerfasserIn]
• Verfasst von: Paterno, Marilyn D [VerfasserIn]
• Verfasst von: Shaykevich, Shimon [VerfasserIn]
• Verfasst von: Haefeli, Walter E. [VerfasserIn]
• Verfasst von: Bates, David W [VerfasserIn]
• Titel: Factors influencing alert acceptance
• Titelzusatz: a novel approach for predicting the success of clinical decision support
• Verf.angabe: Hanna M Seidling, Shobha Phansalkar, Diane L Seger, Marilyn D Paterno, Shimon Shaykevich, Walter E Haefeli, David W Bates
• E-Jahr: 2011
• Jahr: [July 2011]
• Umfang: 6 S.
• Fussnoten: Published: 12 May 2011 ; Gesehen am 31.10.2022
• Titel Quelle: Enthalten in: American Medical Informatics AssociationJournal of the American Medical Informatics Association
• Ort Quelle: Oxford : Oxford Univ. Press, 1994
• Jahr Quelle: 2011
• Band/Heft Quelle: 18(2011), 4 vom: Juli, Seite 479-484
• ISSN Quelle: 1527-974X
• DOI: doi:10.1136/amiajnl-2010-000039
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1820347680

Abstract

Background Clinical decision support systems can prevent knowledge-based prescription errors and improve patient outcomes. The clinical effectiveness of these systems, however, is substantially limited by poor user acceptance of presented warnings. To enhance alert acceptance it may be useful to quantify the impact of potential modulators of acceptance.Methods We built a logistic regression model to predict alert acceptance of drug-drug interaction (DDI) alerts in three different settings. Ten variables from the clinical and human factors literature were evaluated as potential modulators of provider alert acceptance. ORs were calculated for the impact of knowledge quality, alert display, textual information, prioritization, setting, patient age, dose-dependent toxicity, alert frequency, alert level, and required acknowledgment on acceptance of the DDI alert.Results 50 788 DDI alerts were analyzed. Providers accepted only 1.4% of non-interruptive alerts. For interruptive alerts, user acceptance positively correlated with frequency of the alert (OR 1.30, 95% CI 1.23 to 1.38), quality of display (4.75, 3.87 to 5.84), and alert level (1.74, 1.63 to 1.86). Alert acceptance was higher in inpatients (2.63, 2.32 to 2.97) and for drugs with dose-dependent toxicity (1.13, 1.07 to 1.21). The textual information influenced the mode of reaction and providers were more likely to modify the prescription if the message contained detailed advice on how to manage the DDI.Conclusion We evaluated potential modulators of alert acceptance by assessing content and human factors issues, and quantified the impact of a number of specific factors which influence alert acceptance. This information may help improve clinical decision support systems design.