Reducing Interruptive Alert Burden Using Quality Improvement Methodology

Abstract

Background Increased adoption of electronic health records (EHR) with integrated clinical decision support (CDS) systems has reduced some sources of error but has led to unintended consequences including alert fatigue. The “pop-up” or interruptive alert is often employed as it requires providers to acknowledge receipt of an alert by taking an action despite the potential negative effects of workflow interruption. We noted a persistent upward trend of interruptive alerts at our institution and increasing requests for new interruptive alerts. Objectives Using Institute for Healthcare Improvement (IHI) quality improvement (QI) methodology, the primary objective was to reduce the total volume of interruptive alerts received by providers. Methods We created an interactive dashboard for baseline alert data and to monitor frequency and outcomes of alerts as well as to prioritize interventions. A key driver diagram was developed with a specific aim to decrease the number of interruptive alerts from a baseline of 7,250 to 4,700 per week (35%) over 6 months. Interventions focused on the following key drivers: appropriate alert display within workflow, clear alert content, alert governance and standardization, user feedback regarding overrides, and respect for user knowledge. Results A total of 25 unique alerts accounted for 90% of the total interruptive alert volume. By focusing on these 25 alerts, we reduced interruptive alerts from 7,250 to 4,400 per week. Conclusion Systematic and structured improvements to interruptive alerts can lead to overall reduced interruptive alert burden. Using QI methods to prioritize our interventions allowed us to maximize our impact. Further evaluation should be done on the effects of reduced interruptive alerts on patient care outcomes, usability heuristics on cognitive burden, and direct feedback mechanisms on alert utility.

Celebrating Clinical Informatics as a Specialty Practice

“…The invited paper by Chaparro et al, "Reducing Interruptive Alert Burden Using Quality Improvement Methodology," examines the value of managing CDS and alert fatigue using process improvement methods. 8 Another must-read is McGreevey et al's paper, "Reducing Alert Burden in Electronic Health Records: State of the Art Recommendations from Four Health Systems," which describes the risks of alert fatigue that lead to feelings of burnout and presents actionable recommendations from four clinical informatics leaders from diverse health care organizations. 9 Lomotan et al's paper, "To Share is Human!…”

Algorithmic Detection of Boolean Logic Errors in Clinical Decision Support Statements

“…These types of errors could lead CDS to fire in cases where it should not, or not fire in cases where it should, which could lead users to make an error (or omission) that could lead to patient harm 9,24 and contribute to alert fatigue. 25,26 We developed a portable, effective software tool to identify these classes of logic errors. The results are easily interpretable and actionable.…”

Developing an Ophthalmology Clinical Decision Support System to Identify Patients for Low Vision Rehabilitation

“…Although standardization is the foundation for promoting physician compliance, streamlining clinic flow, and improving system cost-effectiveness, [25][26][27] customization to user requirements including more refined firing criteria by subspecialty may benefit user engagement and sustainability. [28][29][30] Lack of such consideration may result in alert overlook or underutilization of referral. 31 An optimally sensitive and specific CDS system may need to be customized to accommodate each subspecialty, or even at the individual user level.…”

“…For long-term quality improvement use, the "hard stop" restriction could be eliminated to minimize workflow interruptions. 28,35 The second challenge involves the timing of the alert appearance during the patient encounter. Several studies have pointed to the importance of user satisfaction with workflow and usability as measures of effectiveness of CDS implementation.…”