While many electronic health record (EHR) alerts have improved patient outcomes, a systematic review found that computerized alerts improved adherence to the intended care process by a median of only 4.2%. Providers override the recommended action in up to 95% of EHR alerts. Routinely overriding alerts habituates providers into ignoring EHR alerts (alert fatigue), leading to patient harm. Reducing alert burden can reduce alert overrides. However, alert burden metrics have not been fully standardized, benchmarks are unknown, and as such, alert burden across institutions and care settings remains unknown. In this didactic panel, we will (1) discuss benefits and challenges in developing a pediatric learning collaborative for clinical decision support benchmarking and sharing of best practices (2) describe the strengths and weaknesses of different approaches to alert burden measurement, (3) demonstrate how alert prioritization can inform quality improvement initiatives to reduce alert burden, (4) examine unique measurement challenges for non-EHR alerts such as phone calls and text messages, and (5) discuss strategies for linking alert burden analytics to governance strategies that facilitate improvement.
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Estimates of the clinical areas with highest alert burden varied substantially by institution and based on the metric used.
Although interruptive alerts have their role in these systems, excessive reliance on or poorly built
interruptive alerts can lead to alert fatigue and other downstream effects. Further refinement of
alert burden metrics is needed as current metrics do not adequately represent the impact on end
users when viewed through different dimensions. The best practices we describe here will allow
institutions to establish monitoring and optimization programs to reduce alert burden.
In this panel, we will describe some of our most inglorious misfires as case vignettes in clinical decision support (CDS) implementation to share hard-earned lessons organized into 8 sociotechnical dimensions.