Leveraging 10 Days of Alert Malfunction to Improve Mature Organizational Clinical Decision Support Processes

Abstract

Background

Interruptive clinical decision support (CDS) alerts are intended to standardize patient care and prevent harm. However, failures can occur even in organizations with mature CDS governance and advanced analytics. These breakdowns, marked by excessive firings, workflow disruption, and clinician dissatisfaction, can provide insights into systemic weaknesses in CDS design, testing, and monitoring processes.

Objectives

This study aimed to examine a CDS alert malfunction as a lens for identifying system-level gaps and propose strategies to strengthen resilience in CDS operations.

Methods

A retrospective analysis was conducted on an interruptive alert that was developed through a phased, multistakeholder, committee-driven process, but was removed within 10 days due to poor performance, revealing gaps that persisted despite established governance.

Results

The alert fired 1,866 times in 5 days, with a 91% dismissal rate and reports of workflow disruption. Feedback indicated provider frustration and concern for malfunction. Analysis revealed gaps in end-user engagement, testing rigor, committee reviews, and monitoring practices.

Conclusion

CDS failures can serve as catalysts for system improvement. This case highlights actionable lessons, such as operationalizing user-centered design, clarifying testing expectations, and distributing monitoring responsibilities, to enhance CDS reliability. Even well-established governance structures must be continuously evaluated and adapted to keep pace with evolving CDS technologies, and such investments position organizations to maintain responsive, sustainable systems aligned with high-quality care.

Keywords

clinical decision support - alerting - organizational change management - system improvement - process improvement - clinical information systems - sociotechnical aspects of information technology - workflows and human interactions

Protection of Human and Animal Subjects

This case review was undertaken as an improvement initiative and as such does not constitute human subjects research.

Declaration of GenAI Use

During the writing process of this paper, the authors used ChatGPT (OpenAI) in order to improving text flow, reducing redundancy, and enhancing overall readability. The author(s) reviewed and edited the text and take(s) full responsibility for the content of the paper.

Publication History

Received: 27 March 2025

Accepted: 20 January 2026

Accepted Manuscript online:
21 January 2026

Article published online:
05 February 2026

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