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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Aug 9, 2020
Open Peer Review Period: Aug 9, 2020 - Aug 16, 2020
Date Accepted: Oct 21, 2020
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Alert Override Patterns With a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study

Yoo J, Lee J, Rhee PL, Chang DK, Kang M, Choi JS, Bates DW, Cha WC

Alert Override Patterns With a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study

JMIR Med Inform 2020;8(11):e23351

DOI: 10.2196/23351

PMID: 33146626

PMCID: 7673981

Alert Override Patterns with a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study

  • Junsang Yoo; 
  • Junghoon Lee; 
  • Poong-Lyul Rhee; 
  • Dong Kyung Chang; 
  • Mira Kang; 
  • Jong Soo Choi; 
  • David W Bates; 
  • Won Chul Cha

ABSTRACT

Background:

Physicians’ alert overriding behavior is known for a most important factor that leads a computerized provider order entry (CPOE) combined with clinical decision support system (CDSS) failure to achieve its potential adverse drug events prevention effect. Previous studies on this subject have focused on specific diseases and/or alert types for well-defined targets as well as specific settings. An emergency department (ED) is an optimal environment to examine physicians’ alert overriding behaviors from a broad perspective because patients have a wider range of severity, and many receive interdisciplinary care in this environment. However, less than one-tenth of the studies targeted the physicians’ behavior in an ED

Objective:

The objective of this study was to describe alert override patterns with a commercial medication CDSS in an academic ED.

Methods:

This study was conducted at a tertiary urban academic hospital in an ED with an annual census of 80,000 visits. We analyzed data about the patients who visited the ED during an 18-month period, the medical staff who treated them, and the prescription and computerized provider order entry alert log. We also performed descriptive analysis and logistic regression for assessing the risk factors for alert overrides.

Results:

During the study period, 611 physicians cared for 71,546 patients with 101,186 visits. The ED physicians encountered 13.75 alerts during every 100 orders entered. Of the total 102,887 alerts, almost two-thirds (63.8%) were overridden. The univariate and multivariate logistic regression analysis identified 21 statistically significant risk factors for ED physicians’ alert override behavior.

Conclusions:

In this retrospective study, we assessed the alert override patterns with a medication CDSS in an academic ED and assessed their contributing factors including physicians’ designation and patient severity.


 Citation

Please cite as:

Yoo J, Lee J, Rhee PL, Chang DK, Kang M, Choi JS, Bates DW, Cha WC

Alert Override Patterns With a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study

JMIR Med Inform 2020;8(11):e23351

DOI: 10.2196/23351

PMID: 33146626

PMCID: 7673981

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